Noor Shadid, Wells Fargo | AnsibleFest 2022
(melodic music) >> Good afternoon. Welcome back to Chicago. Lisa Martin here with John Furrier. Day one of our coverage of Ansible Fest 2022. John, it's great to be back in person. People are excited to be here. >> Yeah. We've had some great conversations with folks from Ansible and the community and the partner side. >> Yeah. One of the things I always love talking about John, is talking with organizations that have been around for a long time that maybe history, maybe around nearly a hundred years, how are they embracing technology to modernize? Yeah, we got a great segment here with the financial services leader, end user of Ansible. So it's be great segment. >> Absolutely. Please welcome Noor Shadid to the program, the senior SVP, excuse me, senior technology manager at Wells Fargo. Noor it's great to have you on theCUBE. Thank you for joining us. >> Of course. Happy to be here. >> Thanks. >> Talk a little bit about technology at Wells Fargo. I was mentioning to you I've been a longtime customer and I've seen the bank evolve incredibly so in the years I've been with it. But... >> Yeah. >> ...talk about Wells Fargo was a technology-driven company. >> Yeah. So I like to consider Wells, right? Being in a financial institution company. So I consider us a technology company that does banking as a customer, right? Like we were talking about. There's so much that we've been able to release over the couple of years, right? I mean, decades worth of automation and technology has been coming out, but lately, right? The way we provide for our customers, how fast at scale, what we're doing for our customers, it's been, it's been significant, right? And I think our goal is always how can we enhance the process for our customers and how can we provide them the next best thing? And I think technology has really allowed us to evolve with our customers. >> The customers. We are so demanding these days. Right? I think one of the things that short supplied in the last two years was patience and tolerance. >> Yes. >> People. And I don't think that's going to rubber band back? >> Yeah. No, I don't think so. >> So how, talk to us about how Wells is using automation to really drive innovation and, surprise and delight those customers on a minute by minute basis. >> Yeah. And so, you know, if you think about banking, we've been able, with automation, we've been able to bring banking into the 21st century. You do not have to go to a branch to manage your money anymore. You do not have to go, you know, go to deposit your check inside of a branch. You can do it through your mobile app, right? That's driven by automation and innovation, right? And, you know, we have all of these back ends tools working for us to help get us to this next generation of, of banking. We can instantly send money to each other. We don't have to worry about, I need to go and figure out how I'm going to get money to this person and I need to wait, you know, X amount of days. You, you have the ability and you have, you feel safe being able to manage your money at the organization. And so automation has really allowed us to get to this place where we can constantly enhance and provide features and reliability to our customers. >> It's interesting you mentioned that you guys are a technology can have it do banking reminds me of the old iPhone analogy. It's a computer that happens to make phone calls. >> Yeah. >> So like, this is the similar mindset. How do you guys keep up? >> Yeah. >> With the technology? >> So it's tough, right? Because there's so much that comes out. And I think the only thing that's constant in technology is change, right? Because it's constantly evolving. But what we do is we, integrate very well with these new tools. We do proof of concepts where we try to, you know, what's on the market, what's hot, how can we involve, like, how can we involve these new tools in our processes? How can we provide a better end result for our customers by bringing in these new tools? So we have a lot of different teams that bring, you know, their jobs are to like, do these proof of concepts and help us build and evolve our own strategies, right? So it keeps us, it keeps us on our toes and I think it keeps, you know, all these new things that are coming out in the market. We're a part of it. We want to evolve with those, what the latest and greatest is. And it's, it's been working right as customers of financial services and us managing our money through, you know, through banks. It's been great. >> So the business is the application. >> Yes. >> And how do you guys make that happen when it comes down to getting the teams aligned? What's the culture like? Explain. >> Yeah. So at Wells we have evolved so much over the, over the last few years. The culture right now is we want to make changes. You know, we are making changes. We want to drive through innovation. We want to be able to provide our, you know, it's a developer centric approach right now, right? We want to push to the next and the greatest. And so everybody is excited and everybody's adapting to all of what's happening in the environment right now. So it's been great because we are able to use all of these new features and tools and things that we were just talking about by allowing our developers to do that work and allowing people to learn these new skills and be able to apply them in their jobs, which is now creating this, you know, a better result for our customers because we're releasing at such a faster pace. And at scale. >> Talk about how, you talked about multiple groups in the organization really investing in innovative technology. How do you get buy-in? What's that sort of pyramid like up to the top level? >> Yeah. >> Because to your point, you're making changes very quickly and consumers demand it. >> Yep. >> You can do everything from home these days. >> Yep. >> You don't have to go into a branch. >> Yeah, yeah. >> Which has changed dramatically in the last it's. >> Powerful few years. Yeah. >> But how, what's that buy-in conversation like from our leadership? >> Yeah. If you don't have leadership buy-in, it's very difficult to make those changes happen. But we at Wells have such a strong support from our leadership to be a part of the change and be, you know, constantly evolve and get better. So the way we work, cause we're such a large organization, you know, we bring in our business, you know, our business teams and we talk to them about what is it that's best going to better our customers. How do we also not just support external but internal, right? How do we provide these automated tools or processes for people to want to do this next work and, and do these, you know, these new releases for our customers. And so we bring in our business partners and, and we bring in our leadership and, our stakeholders and we kind of present to them, you know, this is what we're trying to do. This is the return that you'll get. This is what our customers will also receive. And this is, you know, this is how we keep evolving with that. >> How has the automation culture changed? Because big discussion here is reuse, teamwork, I call it multiplayer kind of organizations where people are working together. 'Cause that's a big theme of automation. >> Yeah. >> Reuse, leverage. >> Yep. >> Can you explain how you guys look at that? >> Yeah. It's changed the way that we do banking because we're eliminating a lot of the repetitive tasks in the toil because we have partners that are developing these, you know, services. So specifically with Ansible, we have these playbooks, rather than having every customer write the same playbook but with their own little, you know, flavor to it, we're able to create these generic patterns that customers can just consume simply by just going into a tool, filling out you know, filling out that playbook template, credentials, or whatever it is that they need and executing it. They don't have to worry about developing something from scratch. And it also allows our customers to feel safe because they don't have to have those skills out the box to be able to use these automation tools, right? They can use what's already been written and executed. >> So that make things go faster with the benefits or what? Speed? >> Faster stability, right? We're now speed, stability, scalability, because we're now able to use this at scale. It's not just individual teams trying to do this within small spaces. We're able to reliable, right? Automation allows us to be reliable internally and for our customers. Because you're not asking, there's no human intervention when you're automating, right? You have these opportunities now for people to just, it's one click, you know, one click solution or you're, you're end to end. You got self-healing involved. It's really driving the way that we do our work today. >> So automation sounds like it's really fueling the internal employee experience at Wells... >> Yes. >> ...as well as the customer experience. And those two things are like this to me. They're inextricably linked. >> A hundred percent because if you need it, they need to be together, right? You want your internal to also be happy because they want to be able to develop these solutions and provide these automation opportunities for our teams, right? And so with the customers, they're constantly seeing these great features come out, right? We can, you know, with AIML today, we're now able to detect fraud significantly. What we would've, what we could've done a couple years ago. And, and developers are excited to be able to do that, right? To be able to learn all these new tools and new technologies. >> What's interesting Wells is you guys are like an edge application. Obviously everyone's got banking in their hand. FinTech obviously money's involved. So there's people interested in getting that money. >> Yeah. >> Security hackers or whatnot. So when you got speed and you got the consistency, I get that. As you look at securing the app, that becomes a big part of what, what's the conversations like there? >> Yeah. >> 'Cause that's the number one concern. And it's an Edge app. I got my mobile, I got my desktop. >> Yeah. >> Everything's in the cloud on premise. >> Yeah. And, and I think for us, security is number one. You know, we want to make sure that we are providing the best for our customers and that they feel safe. Banking, whatever financial service you're working with, you want to feel like you can trust that your money with those services. Right? So what we do is we make sure that our security partners are with us from day one. They're a part of the process. They're automating their pieces as well. We don't want to rely on humans to do a lot of the manual work and do the checking and the logging. You want it to be through automation and new tools, right? You want it to be done through trusted services. You don't, you know, security is right there with us. They're part of our technology organization. They are in the technology org. So they're the ones that are helping us get to that next generation to provide, you know, more secure processes and services for customers. >> And that's key for trust. >> Yes. >> And trust is critical to reduce churn and to, you know, increase the customer lifetime value. But, but people, I mean, especially with the amount of generations that are alive today in banking, you need to be able to deliver that trust intrinsically to any customer. >> Yes, a hundred percent. And you want to be able to not only trust the service but yourself that you can do it. You know, when you go into your app and you make a payment, or when you go in and you want to send, you know, you want to send money to a different, you know, a different bank account, you want to be able to know that what you just did is secure and is where you plan to send it. And so being able to create that environment and provide those services is, is everything right for our customers. >> What are some of the state-of-the-art kind of techniques or trade craft around building apps? 'Cause I mean, basically you're digitally transformed. I mean, you guys are technology first. >> Yeah. >> The app is the company. >> Yeah. >> That's, that's the bank. How do you stay current? What's some of the state of the art things that you guys do that wasn't around just a few years ago? >> Yeah, I mean, right now just using, we're using tools like Terraform and Ansible. We're making sure that those two are hand in hand working well together. So when we work on provisioning, when we, during provisioning where it's all, you know, it's automated, fully end to end, you know, AI ops, right? Being able to detect reoccurring issues that are happening. So if you have a incident we want to learn from that incident and we want to be able to create, you know, incident tickets without having to rely on a human to find that, you know, that problem that was occurring and self-healing, right? All of this is starting to evolve and bringing in the, the proper alerting tools, bringing in the pro, you know, the right automation tools to allow that self-healing to work. That's, you know, these are things that we didn't have, you know, year, decade ago. This is all coming out now as we're starting to progress and, and really take innovation and, you know, automation itself.... >> What's the North star internally when you guys say, hey, you know, down five years down the road, bridge to the future, we're transforming, we've continued to innovate. Scale is a big deal. Data, data sovereignty, all these things are coming up. And what's the internal conversation like when you talk about a future state? >> Yeah, I think right now we're on our cloud transformation journey, right? We're moving right now. We have workloads into our two CSPs or public cloud. Also providing a better service for infrastructure and being able to provide services internally at a faster space, right? So moving into the public cloud, making sure everything's virtualized, moving away from hard, you know, physical hardware or physical servers. That's kind of the journey that we're on right now. Right? Also, machine learning. We want to be able to rely on these, you know, bots. We want to be able to rely on, on things learning from what we're doing so that we don't make the same mistakes again. >> Where would you say the most value or the highest ROI that you've gotten from automation today? Where is that in the organization? >> There's so much, but what I mean because of all of the work that we're doing, there's a lot that I could list, but what I will say is that the ability to allow self-healing in our environments without causing issues is a very big return. Automating failovers, right? I think a lot of our financial institutions have made that a priority where they want to make sure that their applications are active, active and also that when things do go wrong, there is something in place to make sure that that incident actually doesn't, you know, take down any problems. I think it's just also investing in people. Right now, the market is hot and we want to make sure that people feel like they're being able to contribute, they're using the latest and greatest tools. They're able to upskill within our own environments at the firm. And I think our organization does an amazing job of prioritizing people. And so we see the return because we're prioritizing people. And I think, you know, a lot of institutions are trying, you know, people first, people first. But I can say that at Wells, because we are actually driving this, we're allowing, you know, we're enforcing that. We want our engineers to get the certifications. We're providing, you know, vouchers so that people can get those clouds certifications. It's when you do that and you put people first, everything kind of comes together. And I think, you know, a lot of what we see in our industry, it's not really the technology that's the problem, it's process because you're so, you know, we're working at large scales. Our environments are massive. So, you know, my three years at Wells have seen a significant amount of change that has really driven us to be.... >> On that point better. How about changing of the roles? IT, I mean, back in the day, IT serves the business, you know, IT is the business now, right? As, as you've been pointing out. What does the roles change of as automation scales in, is it the operator? I mean, we know what's going on with dev's devs are doing more IT in the CICD pipe lining. >> Yep. >> So we see that velocity check, good cloud native development. What's the op scene look like? It seems to be a multi-tool role. >> Yeah. >> Where the versatility of the skill set... >> Yep. >> ...is the quick learner. >> Yep, able to adapt. >> And yeah, what's your view on this new persona that's emerging from this new opportunity? >> Yeah, and I think it's a great question because if you think about where we're going, and even the term DevOps, right? It means so many things to different people. But literally when you think about what DevOps is allowing our developers and our operations to work together on one team, it's allowing, you know, our operation engineers aren't, you know, years ago, ops engineers were not doing the development work. They were relying on somebody to do the development work and they were just supporting making sure our systems were always available, right? Our engineers are ops are now doing the development work. They're able to contribute and to get, they're writing their own playbooks. They're able to take them into production and ensure that they're, being used correctly. We are change driven execution organization. Everything is driven through change and allowing our ops engineers or production score engineers to write their own playbooks, right? And they know what's happening in the environment. It's powerful. >> Yeah. You're seeing DevOps become a job title. >> Yeah (laughs). >> Used to be like a function of philosophy... >> Yeah, yeah. >> ... and then SRE's... >> SRE's. >> SRE are like how many servers do you have? I don't know, a cloud, what's next? (all laugh) >> What's next? Yeah, I think with SREs it's, you know, it's important that if you have site reliability engineers, you're working towards, you know, those non-functional requirements... >> Yeah. >> ...making sure that you're handling those key components that are required to ensure that our systems, our applications and our integrations, you know, are up there and they're meeting the standards that we set for those other faults. >> And, and I think Red Hat Ansible nailed it here because infrastructure is code. We get that infrastructure has configuration as code, but OPS says code really is that SRE outcome. SRE also came from the Google background, but that means infrastructure's just doing, it's thing. >> Yes. >> The ops is automated. >> Yes. >> That's an interesting concept. >> Yeah, because it's not, you know, it's still new, right? A lot of organizations used to see, and they probably still see operations as being the, you know, their role is just to make sure that the lights are on and they have specific access so they, you know, they're not touching code, but the people that are doing the work and know the environment should really be the ones under creating the content for it. So yeah, I mean it's crazy what's happening now. >> So I got an analogy that's going to be banking analogy, but for tech, you know, back in the automation, Oh, going to put my job out of business, ATMs are going to put the teller out of business as more tellers now than there are before the ATMs. So that metaphor applies into tech where people are like, "What am I auto? What's automating away? Is it my job?" And so actually people know it's not. >> Yeah. >> But what does that free up? So if you assume, if you believe that's good, you say, okay, all the grunt work and the low level on differentiated heavy lifting gets automated away. >> Yeah. >> Great. What does that free up the talent to do? >> Yeah, so when you, and that's great that you bring it up because I think people fear, you know, of automation, especially people that weren't doing automation in the past and now their roles are now they're able to automate those roles out. They're fearful that they don't have a space, a role anymore. But that's not the case at all. What we prioritize is now that those new engineers have this new skill set, apply them. Start using it to be a part of this transformation, right? We're moving from, we went from physical to virtual to now, you know, we're moving into the public, moving into the cloud, right? And that, that transformation, you need people who are ramping up their skill sets, you know, being a part of one of the tools that I own is terraform at Wells that, you know, right now our priority is we're trying to ramp up the organization to learn terraform, right? We want people to learn, you know, this new syntax, this new, you know, HCL and it's, you know, people have been automating some of the stuff that they're doing in their day to day and now trying to learn something new so that they can contribute to this new transformation. >> So new functionality, higher value services? >> Yes, yeah. >> It brings tremendous opportunity for those folks involved in automation. >> Yes. >> or on so many levels. >> Yep. >> Last question, Noor for you is what, you know, as we are rounding out calendar year 2022, entering into 2023, that patience is, that we talked about is still not coming back. What's next for Wells as a technology company that does banking? >> I mean, you name it, we're working on it, because we want to be able to deliver the best for our customers. And I think right now, you know, our digital transformation strategy and, and moving into the public cloud and getting our applications re-architected so that we are moving into microservice driven apps, right? We're moving these workloads into the public cloud in a seamless way. We're not lifting and shifting so that we're not causing more problems into the environment. Right. And I think our, our, our goal is right, Like I was saying earlier, people and evolving with the technology that's coming out. We're not, you know, we are a part of the change and we are happy to be a part of that change and making those changes happen. >> People first. >> Awesome, awesome stuff. >> Automation first sounds outstanding and I will never look at Wells Fargo as a bank again. >> Yeah. (laughter) >> Perfect. Perfect. >> Yeah, that's awesome. >> It's been such a pleasure having you on the program, talking about how transformative Wells has been and continues to be. >> Yeah. >> We appreciate your insights and your time. >> Thank you. >> Thank you so much. It was lovely being her. Pleasure here. Thank you guys. >> For our guest and John Furrier, I'm Lisa Martin. You've been watching theCUBE all day, I'm sure, live from Chicago at Ansible Fest 2022. We hope you have a wonderful rest of your day and John and I will see you tomorrow morning.
SUMMARY :
John, it's great to be back in person. and the community and the partner side. One of the things I always Noor it's great to have you on theCUBE. Happy to be here. I was mentioning to you I've ...talk about Wells Fargo So I like to consider Wells, right? short supplied in the last that's going to rubber band back? So how, talk to us about You do not have to go, you know, mentioned that you guys are a How do you guys keep up? teams that bring, you know, And how do you guys make that provide our, you know, How do you get buy-in? Because to your point, You can do everything dramatically in the last it's. Yeah. the change and be, you know, How has the automation culture changed? out the box to be able to it's one click, you know, it's really fueling the internal things are like this to me. We can, you know, with AIML today, is you guys are like an edge So when you got speed and 'Cause that's the number one concern. generation to provide, you know, reduce churn and to, you know, to a different, you know, you guys are technology first. the art things that you guys do bringing in the pro, you know, you know, down five years down the road, on these, you know, bots. And I think, you know, you know, IT is the business now, right? It seems to be a multi-tool role. of the skill set... aren't, you know, years ago, Yeah. Used to be like a with SREs it's, you know, integrations, you know, SRE also came from the Google background, access so they, you know, but for tech, you know, So if you assume, if you believe What does that free up the talent to do? HCL and it's, you know, those folks involved in automation. for you is what, you know, I think right now, you know, I will never look at Yeah. Perfect. having you on the program, We appreciate your Thank you so much. We hope you have a wonderful
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Kristina Draper, Wells Fargo | WiDS 2019
>> Live, from Stanford University, it's theCUBE! Covering Global Women in Data Science Conference, brought to you by SiliconANGLE Media. >> Welcome back to the CUBE, continuing coverage of the forth annual Women in Data Science Conference or WiDS, I am Lisa Martin, we are live at Stanford University but WiDS is going on at a 150 plus regional events in more than 50 countries. In fact there are 20 thousand people expected to be engaging with our livestream today. Joining us on the program is Kristina Draper, the chief technology officer at Wells Fargo, Wells Fargo, one of the sponsors, Kristina welcome to theCUBE. >> Thank you so much Lisa, it's a real pleasure to be here. >> So this is the forth annual WiDS, and as I was mentioning some of the numbers, it's incredible, the momentum that this event has generated, we'd like to call it a movement. Tell a little bit about your involvement in WiDS, as well as Wells Fargo's involvement as a sponsor. >> Yes, um, so we are really honored to be able to be a part of WiDS. I was introduced to WiDS from an employee of mine, Catherine Lee, she joined our team just about a year ago, and she's been part of WiDS since the Inception. So working with Margo and the team and we believe so strongly that in the consumer bank space we have a tremendous opportunity and responsibility to understand how our customers interact with Wells Fargo and that will require a discipline around data science and so we had an opportunity, and had asked this year to be an executive sponsor and we jumped at it and I think we'll continue to be here at that sponsor level in future years. >> So you've been in Wells Fargo for a long time, tell me a little bit about your background of rising to become the chief technology officer. >> Sure, thank you so much for the question. It's been an interesting journey, I haven't always been at Well. So I did a few start ups here in the Silicon Valley. Um, kind of middle of my career and I came back to Wells Fargo. Most recently, I have a responsibility for the consumer bank technology space, that's the majority of branch technology. It's all of the ATMs, the point of sale network for customers. It also is a lot of business services, so how we think about services oriented architecture to ensure that we're always thinking about our customer and their accounts, in a consistent way regardless of how customers interact with Wells Fargo. So, all channels consistently trusted, so that data set's really important. And then, I also have the customer feedback and customer complaints so the idea that from survey all the way through complaints are being able to understand how our customers are interacting with us. >> And data is an interesting topic, because it's to broad. And I think so many people now across generations understand data privacy, to some degree you can think of you know, the baby-boomers that were affected by the Facebook information and things being shared. From a financial perspective, tell as a little bit about the discipline of data science, not just from the technology background and understanding that your team needs to have, but also other skills such as empathy, communication, negotiation, how are all of those contribute to what your team is delivering? >> Yeah, I would tell you we are in the business of trust. And three years ago, after sales practice came into Wells Fargo, was a very interesting time for our company. We kind of lost our way. And the opportunity with data science is an opportunity to reestablish trust with our customers. And so, you've seen a lot of the rebranding that Wells Fargo is doing in about... We were invented in 1852, but we're reinventing ourselves now. And we have to understand our customers, we have to know our responsibilities to be that trusted advisor to really care for our customers in every interaction. And so, I would think empathy, absolutely. Trust is all about every interaction consistent every time. And so, you think about even just a personal relationship and how you establish trust. It's very hard to reestablish trust, and so for us right now, the commitment to data science is about that reestablishing trust and to really thinking about every interaction with every customer and ensuring we're getting it right. >> You've been there a long time as I've mentioned, I'd love to understand your, some of the things that you've seen along the way as technology changes in terms of more females becoming interested, as we know that there was you know, from where we were in the 80s, where it has been a downwards spiral but you were recently named one of the 50 most powerful women in technology. What are some of the things as you think of how technology in Wells Fargo is re-imagining data and trust? What are the things that you've seen in terms of the evolution of females in technology and in leadership roles? >> Sure, absolutely. Thank you so much. You know think about industry recognition, and I think about how important it is to recognize women's value in the industry. So the recognition women in technology and most powerful women for me, it's an opportunity to really demonstrate that we should be very confident in the value that we bring as leaders, and that confidence as a woman is hard to come by. I think of my own personal career and the way that doors were opened for me along the way often we are our own worst enemies we second guess ourselves, we second guess our value, and we have to really work for that seat at the table. There's certainly been, I wouldn't have come back to Wells if I didn't believed that I had the right sponsors and the right mentors that were not only willing to help me kind of see the doors to walk through but to walk through those doors. And so my coming back to Wells was really about a opportunity as a leader in technology. I just had two start ups here in Silicon Valley, and so I was invited to come back and it was really the leaders and the leadership that brought me back to Wells. I felt I could make a real impact and I think that there's, when I think about the couple of jobs I've had since my second return to Wells Fargo it's really been about impact and recognizing my voice and starting to step into that accountability. When I think about what we can do as women leaders in technology and in data science a lot of it is owning that accountability to leadership and to really kind of paving the way for leaders behind us. There comes a part in a career certainly mine, where you no longer thinking about the next job for yourself and you know, I'm really fortunate that I've been able to get to a CTO level a tech division executive level, I have, you know the recognition on most powerful woman. But I don't do that alone. I do that with a team of women and men who've helped to really create value in the space that we're in. And we're in a consumer banking space and financial services and so there's certainly a lot of places to innovate, there's a lot of places to think about how technology can help to serve a Wells Fargo customer and if you think about when you need your bank you need your bank throughout your entire life. And whether you are thinking about a home purchase, an auto purchase, college for your children, retirement, there's so many big markers in life and that's where I get excited about, not only the leadership role that I have now, but I have the opportunity to bring a team with me to contribute real value. And so that's for me what really brought me back was an opportunity to have that impact to think about data science and technology in a way that there's true visible value being added to the market place to the industry. >> So it's almost like can we have pay it forward added to, how are you using that to expand your team with the right skills and the right people regardless of gender, regardless of any of that, to continue this big movement, this re-imagination that Wells Fargo is a business in undergoing. >> Yeah, well I would tell you WiDS is one way. WiDS is certainly a tremendous network opportunity if you think about the breadth and the reach across countries, across landscapes, across geographies, this is just one example of how I think about that. There's real power in relationships. There's real power in ability to establish not only a strong industry network a strong personal brand, but also a personal network. Even in the last couple of hours, WiDS started today, so inspired by the keynote speaker, so inspired about how they're turning data science and really thinking about different problems, different ways that we can improve, not only our lives, but the lives of future generations to come. I think part of how I think about it is finding that inspiration, because we have to inspire future generations of leaders, of women, and of men to really tackle the problem and have the right skills and confidence to be able to jump into that space. >> I agree with you. I think one of my favorite things in this, theCUBE has been covering WiDS since the beginning for four years and I always love coming here because you walk in and you immediately feel inspired. But you also feel that sense of collaboration, you talked about how important that is, not just for people that are in academia but in industry as well, you know I can't do what I do, you can't be a successful CTO at anywhere, at Wells Fargo let alone, any organization, without that collaborative spirit and I think I always feel that very strongly every time I walked in the door at a WiDS event, that people, they really do live up to their mission statement which is to inspire and educate women in data science and people in data science in general. >> Yeah, and I would offer that there's a lot of magic in the empty space, so the space in between and the way I would describe that is that so you come in to WidS data conference and certainly I come from a financial services background that the primary, you know, my primary professional background has been in financial services and technology, but the problems that our future generations will face can't be solved with just one lens. You can't solve problems with just a financial services expertise or just a technical expertise. You need to really look for how do you... It's the AND, and sometimes the space in between and bringing art and science. It's an ability to bring to think across industry and to apply solutions and innovation that have been brought forward through other industries, through other companies, through other academia and thinking about how that could apply in solving the problems that we're faced with in the financial services space. And so, to me coming to WiDS conference or spending time with the women that we'll meet in the room or the men that we'll meet in the room it's really about listening to their stories, listening to their passions, thinking about the problems they're solving and stepping back and identifying well, gosh if I really turned some of the problems that we're faced with upside down and thought about it with that perspective of with that lens, and maybe invited some people to your point, the collaboration to help solve problems with us, we might come up with a better answer, it's the space that's in between that might have called the difference. >> I like that! The space in between, there's so much applicability, I mean there's 2.5 quintillion data generated everyday across every industry. Whether it's you know, personal banking information or what we eat or where we travel, we do everything through mobile these days, and companies like Wells Fargo have such potential to be able to utilize that data to you know, create solutions that helps so many people. But you're right it's what can, how can financial services and the data that you deal with and to help customers and that sense, with the opportunity to influence all these other disciplines. I think that's one of the things that excites me about data science, it's how broad and symbiotic this discipline really is. >> Totally agree with you. And I have a new leader, Jason Strle, who just came in to Wells Fargo, just over a year ago, and he talks about a vision where we are 100 percent transparent in our data with our customers, so think about that value proposition in financial services, where there's a 100 percent data symmetry. What we know, you know. What you know, we know, when you want us to know it. And that can be so powerful, and that's really how we're thinking about the transformation around technology, the investment that we're going to make in data science, an AI and machine learning, because that 100 percent data symmetry comes back to trust. If we're a 100 percent transparent with everyone of our customers about what we know think about how that establishes trust. I mean that is a rock solid foundation for trust in the future, and I think that's really something that can be very powerful if we capitalize it, but we can't to it alone, we're going to need partners. We're going to need partners like so many of the companies in the academics that are in this room today. And we'll have to reach even broader because some of the solutions won't be found if we just look internal to Wells Fargo. >> Exactly. That diversity in so many ways is so impactful. Kristina, thank you so much for stopping by theCUBE and sharing with us some of the things that you're doing, how you've ascended to the CTO at Wells Fargo and how Wells Fargo is sponsoring in contributing to this WiDS movement, we appreciate your time. >> It's a real honor, thank you so much Lisa. >> Thank you! >> Pleasure! >> We want to thank you for watching the CUBE live at Stanford University, from the forth annual Women in Data Science Conference. I'm Lisa Martin. Stick around, my next guest will be here momentarily. (upbeat music)
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Rich Baich, Wells Fargo & Jason Cook, The Chertoff Group | Security in the Board Room
(clicking) >> Hey welcome back everybody. Jeff Freck here with theCUBE. We're in Palo Alto, California at the Chertoff Event. It's called Security in the Boardroom and it's really about elevating the security conversation beyond the IT folks and the security folks out in the application space and out on the edge and really, what's the conversation going on at the boardroom, 'cause it's an important conversation. And one you want to have before your name shows up in the Wall Street journal on a Monday morning for not all the right reasons. So we're excited to have a real practitioner, Rich Baich. He's a chief information security officer for Wells Fargo. Welcome Rich. And in the company of Jason Cook who's the managing director with the Chertoff group. Great to see you Jason. So we talked a little bit off camera Rich. You've been in a lot of different seats in this game from consulting to now you're at Wells Fargo, and a few more that you ripped on this, but I can't remember them all. From your perspective, integrating this multi-dimensional approach. How do you see this conversation changing at the boardroom? >> Well I think most importantly, the board is a topic of discussion, one of the top discussions over the last couple of years. There's been a lot of guidance recently that's been put out to board directors through the National Association for Corporate Directors, as well as various consulting firms providing guidance. Board members need to be able to take this complex topic and simplify it down so that they can do their jobs. It's expected of them, and sometimes that can be a language barrier. So I think what I see happening is boards are beginning to hire individuals with some cybersecurity expertise. My example at Wells Fargo, we hired a retired general Suzanne Vautrino to come in as one of our cybersecurity, obviously experts in the board. And it's great having her in that board seat because often times, she can help me translate some of the issues and gain a different perspective from the board. >> So that's a pretty interesting statement. So they're actually putting security expertise in a formal board seat. >> Yes. >> That's a pretty significant investment in the space. >> But if you think about this. I mean why? >> Right. >> Right. >> Well most institutions today when you break them down are really technology companies that's just a business platform rolls on. So security is becoming part of not only the institution today but the institution of the future as organizations move towards digitalization. So having that ability to have someone who understands risk management side of cybersecurity as well as the practitioner side will only make, I think a boardroom that much stronger. So what's your experience in terms of trying to communicate the issues to a board? Just down and dirty. Where do you find the balance as to what they can absorb? What can they not absorb? How do you outlay the risks if you will and how they should think about driving investment in these areas? >> Well great points, the first and most important thing with boards is gaining trust. Did you have the expertise and you had the information. By no means could I bring all my data to a board meeting because it's just not digestible. So there's a little bit of an art of taking that down and building the trust and focusing on certain areas. But a point you made I think it's really important is one you have to help them understand what are the top risks and why. But when you're talking to a board, you have to be able to say, and this is what we're doing to address them and here is the time frame and here is the risk associated with this. Because in their minds, they're thinking what can I do to help you? And then secondly, Stu point was the decisioning regarding prioritization. in this particular space, there's always going to be risks but it's really the art of deciding which ones are more important. I'll talk to the board and I'll highlight things like probability of occurrence. So the higher the probability of occurrence of something happening really drives our prioritization. >> Then Jason from your perspective. You're coming in from outside the board trying to help out. How have you seen the security conversation and priority change over time, especially in the context of this other hot topic that everybody is jumping on, which is probably the agenda item, just before Rich comes in the room, which is digital transformation. We got to go, we got to go, we got to go. Everybody is evolving. We got to go, we're getting left behind, and then oh by the way. We're just going to come on afterwards and tell us what some of these risks are. >> Yeah and I think actually Rich started to touch on it. All organizations especially when you're looking at the Fortune 500 and around that shape and size are global. And they're all on a digital journey, whether they acknowledge they're actually a digital product company. All of them now, digitizing is happening. So as a result of that security is an absolute critical component of anything linked to that for all of the reasons that you can just read the headlines around. And actually at the boardroom level, it's more now, hopefully becoming a conversation that's about how do we as board members take responsibility and accountability for how to protect our organization. And it's framed now more and more so in a risk management conversation. Rather than just saying security 'cause security is like outside. But actually the reality is security and cyber activity because you're a digital organization. It's embedded into everything whether you realize it or not so the board needs to be education to what that means. How do you take risks in the context of digital activity and assign it to a risk management program approach rather than just saying it's the security guy that's got to come in and do that. And the security guy is most probably going to be the guy that absolutely has to understand that boardroom issue, and then execute upon it and bring options to the table every time in and around that space. But the main message I would say is take this from a risk management perspective and start using the language like that. And that's probability the other point that we were discussing just earlier in the security series today, that actually it's about risk management, and educating everyone very clearly as to what do we mean. What are we actually protecting. How are we protecting it and what are we doing as a set of board members, and as a leadership team to actually take forward enablement of the business. From a security perspective, understanding it but then also protecting the business. >> Right, so are you building models then for them to help them assign a value to that risk, so now they know how much that they have to invest. 'Cause the crazy thing about security, I'm sure you could always invest more right. You can always use a little bit more budget. There's a little bit more that you can do to make yourself a little bit more secure than you were without that investment. But nobody has infinite resources so as you said bad things can happen, it's really risk mitigation and knowing the profile and what to do about it. So how do help them model that? >> I can answer that and I know Rich can jump in, so what you're seeing is a brand new leader role emerging from the traditional IT security guy to now, the guy that isn't or person should I say more accurately that's engaged at the boardroom. That's there to talk about risks in the context of how the board sees it. And so what does that means? It means that absolutely, you need to know what you've got from a digital perspective. Everything from the traditional network to all of the IT assets and everything there. The key thing is you need to know what you've got, but you have then contextualize all of that against business risks. And pulling those two things together is the challenge that you see across the industry today 'cause there have been silos. And usually underneath that silos and many other silos so bringing that together is really important. And I think if you look at how we're going to see disrupt it is and how things are managed in the risk management perspective. Actually, that's what you're going to see come together. How do you bring those models together to give actionable intelligence that the board can react to or predict against, and that's not an easy thing to pull together. >> Yeah, and to take it more down to a tactical arena so you know at some point, like you said, you can't asking for more money. Because you're not practicing good business attributes because everybody can ask for more money. So I think as organizations mature their security programs, they're going to go to the board with issues like this. Endpoint security, there's so many different Endpoints security products out there that you could buy. But if you're practicing good risk management. You're starting off by saying what is the risk. Let's just talk about malware. So malware is the risk, well how much malware gets to your Endpoint. Unless just say in this particular instance, you're here. You go into a program where you're enhancing your tools, your techniques, you're shutting down USB ports. You're not allowing people to connect to the internet unless they go through the VPN. You're buying endpoint solutions to put on there. You're encrypting the endpoint, you're doing all these things and you suddenly see your monthly average of malware go from here to here. And then when you do that and you walk into a boardroom, and you can show them that and you say this is kind of our risk appetite. 'Cause we're never going to be able to reduce it but I could go spend some more money. I could go spend five million more dollars that I'm going to move it this much. I'd rather take that five million move it over to this risk which is right here to reduce it to that area. So I think that goes hand in hand with what Jason's saying but when you can get to that level to the board to help them understand their decision. They have a greater comfort level that the money is being spent and prioritization is occurring. >> Yeah, so if I may so that one of the things that you just touch on, I think is really useful for us kind of expand upon more. One of the advise points Chertoff Group had in our series session was around bringing cybersecurity experts to the boardroom. I know obviously, you're very active in the whole finance sector, providing advice and direction in that space. Can you tell us more about that? >> Sure so, what's particular in my world also as the chair or the financial services sector coordinating council. What we do is we work closely with the government, with policy and doctrine and then the FSI sector, financial services sector, analysis center is the group that really goes out, and kind of operationalize it through information sharing and that sort. But what we've seen is a desire to have, honestly more security professionals on boards. So CISOs potentially being asked to sit on public and private company boards to provide that expertise back to the company. So that the boardroom can help understand and transcend what is going on. Again from my standpoint, I feel very privileged to have one of them on my board today. And she's been just a wonderful addition, not only does she bring cyber expertise, but being a retired general brings a lot it to other additional. So I would predict, we'll see more and more CISOs being asked to sit on public and private boards. They bring that perspective as the business models move to digitalization. >> We can go on forever, forever and ever but we can't unfortunately, but I have one more question for you Rich. Is kind of this change in attitude amongst the CISO community and other people ideal security in terms sharing information. You mentioned on this group and you use to be, we didn't want to share if we got attacked for a lot of different reasons, but there's a real benefit to sharing information even across industries about the profile of some of these things that are happening. How are we seeing that kind of change and how much more valuable is it to have some other input from some other peers, than just kind of you with you're jewels that they're trying to protect. >> Sure so in general, from an industry standpoint, the financial services are much further ahead than a lot of the other industries 'cause we've been doing it along time. So sharing occurs officially through the FSI site but also you'll pick you phone up and call a friend right a way, and say hey, I've just seen some of you're IP space associated with so and so. So that informal sharing is there. It's a very tight community, in particularly from the financial services. You don't think of security as a differentiator necessarily because the reality of it is when an adversary chooses to point their direction at you. It's just a matter of time before they get around to your institution. So sharing occurs and secondly, the government been doing a great job of trying to break down those barriers. Work through all the issues that are related with sharing of classified, unclassified information. So there exists a model today, it seems to be working pretty well. Formal as well as informal and if you look at some of the past history. That sharing has really helped a lot of organizations. I see they only getting better and better as time goes by. >> And the point, I'd add to that is the financial services I said for example is one of the most mature out there. In fact, it is probably the most mature or global even out there. But that's taken time to establish the trust and the collaboration there. And the one recommendation that we would all give out to the industry as a whole is you need to be getting those types of things stood up. And you have to invest time into them to generate the collaboration and trust. You're not going to get it over night but you have to start somewhere in doing the same. Because really what good work is happening here, needs to be happening across the global industry as a whole. >> Right, alright Rich and Jason, we'll have to leave it there unfortunately. Really great insight and thanks for sharing your insight with us. >> Rich: And thank you. >> Alright, I'm Jeff Freck. You're watching theCUBE. We're at Security in the Boardroom at the Chertoff event, Palo Alto. Thanks for watching. (clicking)
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and it's really about elevating the security conversation and simplify it down so that they can do their jobs. So that's a pretty interesting statement. But if you think about this. So having that ability to have someone and here is the risk associated with this. You're coming in from outside the board trying to help out. so the board needs to be education to what that means. and knowing the profile and what to do about it. intelligence that the board can react to or predict against, Yeah, and to take it more down to a tactical arena Yeah, so if I may so that one of the things So that the boardroom can help understand but there's a real benefit to sharing information and if you look at some of the past history. And the point, I'd add to that is the financial services Right, alright Rich and Jason, We're at Security in the Boardroom
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Rhonda Crate, Boeing | WiDS 2023
(gentle music) >> Hey! Welcome back to theCUBE's coverage of WiDS 2023, the eighth Annual Women In Data Science Conference. I'm your host, Lisa Martin. We are at Stanford University, as you know we are every year, having some wonderful conversations with some very inspiring women and men in data science and technical roles. I'm very pleased to introduce Tracy Zhang, my co-host, who is in the Data Journalism program at Stanford. And Tracy and I are pleased to welcome our next guest, Rhonda Crate, Principal Data Scientist at Boeing. Great to have you on the program, Rhonda. >> Tracy: Welcome. >> Hey, thanks for having me. >> Were you always interested in data science or STEM from the time you were young? >> No, actually. I was always interested in archeology and anthropology. >> That's right, we were talking about that, anthropology. Interesting. >> We saw the anthropology background, not even a bachelor's degree, but also a master's degree in anthropology. >> So you were committed for a while. >> I was, I was. I actually started college as a fine arts major, but I always wanted to be an archeologist. So at the last minute, 11 credits in, left to switch to anthropology. And then when I did my master's, I focused a little bit more on quantitative research methods and then I got my Stat Degree. >> Interesting. Talk about some of the data science projects that you're working on. When I think of Boeing, I always think of aircraft. But you are doing a lot of really cool things in IT, data analytics. Talk about some of those intriguing data science projects that you're working on. >> Yeah. So when I first started at Boeing, I worked in information technology and data analytics. And Boeing, at the time, had cored up data science in there. And so we worked as a function across the enterprise working on anything from shared services to user experience in IT products, to airplane programs. So, it has a wide range. I worked on environment health and safety projects for a long time as well. So looking at ergonomics and how people actually put parts onto airplanes, along with things like scheduling and production line, part failures, software testing. Yeah, there's a wide spectrum of things. >> But I think that's so fantastic. We've been talking, Tracy, today about just what we often see at WiDS, which is this breadth of diversity in people's background. You talked about anthropology, archeology, you're doing data science. But also all of the different opportunities that you've had at Boeing. To see so many facets of that organization. I always think that breadth of thought diversity can be hugely impactful. >> Yeah. So I will say my anthropology degree has actually worked to my benefit. I'm a huge proponent of integrating liberal arts and sciences together. And it actually helps me. I'm in the Technical Fellowship program at Boeing, so we have different career paths. So you can go into management, you can be a regular employee, or you can go into the Fellowship program. So right now I'm an Associate Technical Fellow. And part of how I got into the Fellowship program was that diversity in my background, what made me different, what made me stand out on projects. Even applying a human aspect to things like ergonomics, as silly as that sounds, but how does a person actually interact in the space along with, here are the actual measurements coming off of whatever system it is that you're working on. So, I think there's a lot of opportunities, especially in safety as well, which is a big initiative for Boeing right now, as you can imagine. >> Tracy: Yeah, definitely. >> I can't go into too specifics. >> No, 'cause we were like, I think a theme for today that kind of we brought up in in all of our talk is how data is about people, how data is about how people understand the world and how these data can make impact on people's lives. So yeah, I think it's great that you brought this up, and I'm very happy that your anthropology background can tap into that and help in your day-to-day data work too. >> Yeah. And currently, right now, I actually switched over to Strategic Workforce Planning. So it's more how we understand our workforce, how we work towards retaining the talent, how do we get the right talent in our space, and making sure overall that we offer a culture and work environment that is great for our employees to come to. >> That culture is so important. You know, I was looking at some anitab.org stats from 2022 and you know, we always talk about the number of women in technical roles. For a long time it's been hovering around that 25% range. The data from anitab.org showed from '22, it's now 27.6%. So, a little increase. But one of the biggest challenges still, and Tracy and I and our other co-host, Hannah, have been talking about this, is attrition. Attrition more than doubled last year. What are some of the things that Boeing is doing on the retention side, because that is so important especially as, you know, there's this pipeline leakage of women leaving technical roles. Tell us about what Boeing's, how they're invested. >> Yeah, sure. We actually have a publicly available Global Diversity Report that anybody can go and look at and see our statistics for our organization. Right now, off the top of my head, I think we're hovering at about 24% in the US for women in our company. It has been a male majority company for many years. We've invested heavily in increasing the number of women in roles. One interesting thing about this year that came out is that even though with the great resignation and those types of things, the attrition level between men and women were actually pretty close to being equal, which is like the first time in our history. Usually it tends on more women leaving. >> Lisa: That's a good sign. >> Right. >> Yes, that's a good sign. >> And we've actually focused on hiring and bringing in more women and diversity in our company. >> Yeah, some of the stats too from anitab.org talked about the increase, and I have to scroll back and find my notes, the increase in 51% more women being hired in 2022 than 2021 for technical roles. So the data, pun intended, is showing us. I mean, the data is there to show the impact that having females in executive leadership positions make from a revenue perspective. >> Tracy: Definitely. >> Companies are more profitable when there's women at the head, or at least in senior leadership roles. But we're seeing some positive trends, especially in terms of representation of women technologists. One of the things though that I found interesting, and I'm curious to get your thoughts on this, Rhonda, is that the representation of women technologists is growing in all areas, except interns. >> Rhonda: Hmm. >> So I think, we've got to go downstream. You teach, I have to go back to my notes on you, did my due diligence, R programming classes through Boeings Ed Wells program, this is for WSU College of Arts and Sciences, talk about what you teach and how do you think that intern kind of glut could be solved? >> Yeah. So, they're actually two separate programs. So I teach a data analytics course at Washington State University as an Adjunct Professor. And then the Ed Wells program is a SPEEA, which is an Aerospace Union, focused on bringing up more technology and skills to the actual workforce itself. So it's kind of a couple different audiences. One is more seasoned employees, right? The other one is our undergraduates. I teach a Capstone class, so it's a great way to introduce students to what it's actually like to work on an industry project. We partner with Google and Microsoft and Boeing on those. The idea is also that maybe those companies have openings for the students when they're done. Since it's Senior Capstone, there's not a lot of opportunities for internships. But the opportunities to actually get hired increase a little bit. In regards to Boeing, we've actually invested a lot in hiring more women interns. I think the number was 40%, but you'd have to double check. >> Lisa: That's great, that's fantastic. >> Tracy: That's way above average, I think. >> That's a good point. Yeah, it is above average. >> Double check on that. That's all from my memory. >> Is this your first WiDS, or have you been before? >> I did virtually last year. >> Okay. One of the things that I love, I love covering this event every year. theCUBE's been covering it since it's inception in 2015. But it's just the inspiration, the vibe here at Stanford is so positive. WiDS is a movement. It's not an initiative, an organization. There are going to be, I think annually this year, there will be 200 different events. Obviously today we're live on International Women's Day. 60 plus countries, 100,000 plus people involved. So, this is such a positive environment for women and men, because we need everybody, underrepresented minorities, to be able to understand the implication that data has across our lives. If we think about stripping away titles in industries, everybody is a consumer, not everybody, most of mobile devices. And we have this expectation, I was in Barcelona last week at a Mobile World Congress, we have this expectation that we're going to be connected 24/7. I can get whatever I want wherever I am in the world, and that's all data driven. And the average person that isn't involved in data science wouldn't understand that. At the same time, they have expectations that depend on organizations like Boeing being data driven so that they can get that experience that they expect in their consumer lives in any aspect of their lives. And that's one of the things I find so interesting and inspiring about data science. What are some of the things that keep you motivated to continue pursuing this? >> Yeah I will say along those lines, I think it's great to invest in K-12 programs for Data Literacy. I know one of my mentors and directors of the Data Analytics program, Dr. Nairanjana Dasgupta, we're really familiar with each other. So, she runs a WSU program for K-12 Data Literacy. It's also something that we strive for at Boeing, and we have an internal Data Literacy program because, believe it or not, most people are in business. And there's a lot of disconnect between interpreting and understanding data. For me, what kind of drives me to continue data science is that connection between people and data and how we use it to improve our world, which is partly why I work at Boeing too 'cause I feel that they produce products that people need like satellites and airplanes, >> Absolutely. >> and everything. >> Well, it's tangible, it's relatable. We can understand it. Can you do me a quick favor and define data literacy for anyone that might not understand what that means? >> Yeah, so it's just being able to understand elements of data, whether that's a bar chart or even in a sentence, like how to read a statistic and interpret a statistic in a sentence, for example. >> Very cool. >> Yeah. And sounds like Boeing's doing a great job in these programs, and also trying to hire more women. So yeah, I wanted to ask, do you think there's something that Boeing needs to work on? Or where do you see yourself working on say the next five years? >> Yeah, I think as a company, we always think that there's always room for improvement. >> It never, never stops. >> Tracy: Definitely. (laughs) >> I know workforce strategy is an area that they're currently really heavily investing in, along with safety. How do we build safer products for people? How do we help inform the public about things like Covid transmission in airports? For example, we had the Confident Traveler Initiative which was a big push that we had, and we had to be able to inform people about data models around Covid, right? So yeah, I would say our future is more about an investment in our people and in our culture from my perspective >> That's so important. One of the hardest things to change especially for a legacy organization like Boeing, is culture. You know, when I talk with CEO's or CIO's or COO's about what's your company's vision, what's your strategy? Especially those companies that are on that digital journey that have no choice these days. Everybody expects to have a digital experience, whether you're transacting an an Uber ride, you're buying groceries, or you're traveling by air. That culture sounds like Boeing is really focused on that. And that's impressive because that's one of the hardest things to morph and mold, but it's so essential. You know, as we look around the room here at WiDS it's obviously mostly females, but we're talking about women, underrepresented minorities. We're talking about men as well who are mentors and sponsors to us. I'd love to get your advice to your younger self. What would you tell yourself in terms of where you are now to become a leader in the technology field? >> Yeah, I mean, it's kind of an interesting question because I always try to think, live with no regrets to an extent. >> Lisa: I like that. >> But, there's lots of failures along the way. (Tracy laughing) I don't know if I would tell myself anything different because honestly, if I did, I wouldn't be where I am. >> Lisa: Good for you. >> I started out in fine arts, and I didn't end up there. >> That's good. >> Such a good point, yeah. >> We've been talking about that and I find that a lot at events like WiDS, is women have these zigzaggy patterns. I studied biology, I have a master's in molecular biology, I'm in media and marketing. We talked about transportable skills. There's a case I made many years ago when I got into tech about, well in science you learn the art of interpreting esoteric data and creating a story from it. And that's a transportable skill. But I always say, you mentioned failure, I always say failure is not a bad F word. It allows us to kind of zig and zag and learn along the way. And I think that really fosters thought diversity. And in data science, that is one of the things we absolutely need to have is that diversity and thought. You know, we talk about AI models being biased, we need the data and we need the diverse brains to help ensure that the biases are identified, extracted, and removed. Speaking of AI, I've been geeking out with ChatGPT. So, I'm on it yesterday and I ask it, "What's hot in data science?" And I was like, is it going to get that? What's hot? And it did it, it came back with trends. I think if I ask anything, "What's hot?", I should be to Paris Hilton, but I didn't. And so I was geeking out. One of the things I learned recently that I thought was so super cool is the CTO of OpenAI is a woman, Mira Murati, which I didn't know until over the weekend. Because I always think if I had to name top females in tech, who would they be? And I always default to Sheryl Sandberg, Carly Fiorina, Susan Wojcicki running YouTube. Who are some of the people in your history, in your current, that are really inspiring to you? Men, women, indifferent. >> Sure. I think Boeing is one of the companies where you actually do see a lot of women in leadership roles. I think we're one of the top companies with a number of women executives, actually. Susan Doniz, who's our Chief Information Officer, I believe she's actually slotted to speak at a WiDS event come fall. >> Lisa: Cool. >> So that will be exciting. Susan's actually relatively newer to Boeing in some ways. A Boeing time skill is like three years is still kind of new. (laughs) But she's been around for a while and she's done a lot of inspiring things, I think, for women in the organization. She does a lot with Latino communities and things like that as well. For me personally, you know, when I started at Boeing Ahmad Yaghoobi was one of my mentors and my Technical Lead. He came from Iran during a lot of hard times in the 1980s. His brother actually wrote a memoir, (laughs) which is just a fun, interesting fact. >> Tracy: Oh my God! >> Lisa: Wow! >> And so, I kind of gravitate to people that I can learn from that's not in my sphere, that might make me uncomfortable. >> And you probably don't even think about how many people you're influencing along the way. >> No. >> We just keep going and learning from our mentors and probably lose sight of, "I wonder how many people actually admire me?" And I'm sure there are many that admire you, Rhonda, for what you've done, going from anthropology to archeology. You mentioned before we went live you were really interested in photography. Keep going and really gathering all that breadth 'cause it's only making you more inspiring to people like us. >> Exactly. >> We thank you so much for joining us on the program and sharing a little bit about you and what brought you to WiDS. Thank you so much, Rhonda. >> Yeah, thank you. >> Tracy: Thank you so much for being here. >> Lisa: Yeah. >> Alright. >> For our guests, and for Tracy Zhang, this is Lisa Martin live at Stanford University covering the eighth Annual Women In Data Science Conference. Stick around. Next guest will be here in just a second. (gentle music)
SUMMARY :
Great to have you on the program, Rhonda. I was always interested in That's right, we were talking We saw the anthropology background, So at the last minute, 11 credits in, Talk about some of the And Boeing, at the time, had But also all of the I'm in the Technical that you brought this up, and making sure overall that we offer about the number of women at about 24% in the US more women and diversity in our company. I mean, the data is is that the representation and how do you think for the students when they're done. Lisa: That's great, Tracy: That's That's a good point. That's all from my memory. One of the things that I love, I think it's great to for anyone that might not being able to understand that Boeing needs to work on? we always think that there's Tracy: Definitely. the public about things One of the hardest things to change I always try to think, live along the way. I started out in fine arts, And I always default to Sheryl I believe she's actually slotted to speak So that will be exciting. to people that I can learn And you probably don't even think about from anthropology to archeology. and what brought you to WiDS. Tracy: Thank you so covering the eighth Annual Women
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AnsibleFest 2022 theCUBE Report Summary
(soft music) >> Welcome back to Chicago guys and gals. Lisa Martin here with John Furrier. We have been covering Ansible Fest '22 for the last two days. This is our show wrap. We're going to leave you with some great insights into the things that we were able to dissect over the last two days. John, this has been an action packed two days. A lot of excitement, a lot of momentum. Good to be back in person. >> It's great to be back in person. It was the first time for you to do Ansible Fest. >> Yes. >> My first one was 2019 in person. That's the last time they had an event in person. So again, it's a very chill environment here, but it's content packed, great active loyal community and is growing. It's changing. Ansible now owned by Red Hat, and now Red Hat owned by IBM. Kind of see some game changing kind of movements here on the chess board, so to speak, in the industry. Ansible has always been a great product. It started in open source. It evolved configuration management configuring servers, networks. You know, really the nuts and bolts of IT. And became a fan favorite mainly because it was built by the fans and I think that never stopped. And I think you started to see an opportunity for Ansible to be not only just a, I won't say niche product or niche kind of use case to being the overall capabilities for large scale enterprise system architectures, system management. So it's very interesting. I mean I find it fascinating how, how it stays relevant and cool and continues to power through a massive shift >> A massive shift. They've done a great job though since the inception and through the acquisition of being still community first. You know, we talked a lot yesterday and today about helping organizations become automation first that Ansible has really stayed true to its roots in being community first, community driven and really that community flywheel was something that was very obvious the last couple of days. >> Yeah, I mean the community thing is is is their production system. I mean if you look at Red Hat, their open source, Ansible started open source, good that they're together. But what people may or may not know about Ansible is that they build their product from the community. So the community actually makes the suggestions. Ansible's just in listening modes. So when you have a system that's that efficient where you have direct working backwards from the customer like that, it's very efficient. Now, as a product manager you might want to worry about scope creep, but at the end of the day they do a good job of democratizing that process. So again, very strong product production system with open source, very relevant, solves the right problems. But this year the big story to me is the cultural shift of Ansible's relevance. And I think with multicloud on the horizon, operations is the new kind of developer kind of ground. DevOps has been around for a while. That's now shifted up to the developer themselves, the cloud native developer. But at cloud scale and hybrid computing, it's about the operations. It's about the data and the security. All of it's about the data. So to me there's a new ops configuration operating model that you're seeing people use, SRE and DevOps. That's the new culture, and the persona's changing. The operator of a large scale enterprise is going to be a lot different than it was past five, 10 years. So major cultural shift, and I think this community's going to step up to that position and fill that role. >> They seem to be having a lot of success meeting people where they are, meeting the demographics, delivering on how their community wants to work, how they want to collaborate. But yesterday you talked about operations. We talked a lot about Ops as code. Talk about what does that mean from your perspective, and what did you hear from our guests on the program with respect that being viable? >> Well great, that's a great point. Ops as code is the kind of their next layer of progression. Infrastructure is code. Configuration is code. Operations is code. To me that means running the company as software. So software influencing how operators, usually hardware in the past. Now it's infrastructure and software going to run things. So ops as code's, the next progression in how people are going to manage it. And I think most people think of that as enterprises get larger, when they hear words like SRE, which stands for Site Reliable Engineer. That came out of Google, and Google had all these servers that ran the search engine and at scale. And so one person managed boatload of servers and that was efficient. It was like a multiple 10x engineer, they used to call it. So that that was unique to Google but not everyone's Google. So it became language or parlance for someone who's running infrastructure but not everyone's that scale. So scale is a big issue. Ops as code is about scale and having that program ability as an operator. That's what Ops as code is. And that to me is a sign of where the scale meets the automation. Large scale is hard to do. Automating at large scale is even harder. So that's where Ansible fits in with their new automation platform. And you're seeing new things like signing code, making sure it's trusted and verified. So that's the software supply chain issue. So they're getting into the world where software, open source, automation are all happening at scale. So to me that's a huge concept of Ops as code. It's going to be very relevant, kind of the next gen positioning. >> Let's switch gears and talk about the partner ecosystem. We had Stefanie Chiras on yesterday, one of our longtime theCUBE alumni, talking about what they're doing with AWS in the marketplace. What was your take on that, and what's the "what's in it for me" for both Red Hat, Ansible and AWS? >> Yeah, so the big news on the automation platform was one. The other big news I thought was really, I won't say watered down, but it seems small but it's not. It's the Amazon Web Services relationship with Red Hat, now Ansible, where Ansible's now a product in AWS's marketplace. AWS marketplace is kind of hanging around. It's a catalog right now. It's not the most advanced technical system in the world, and it does over 2 billion plus revenue transactions. So even if it's just sitting there as a large marketplace, that's already doing massive amounts of disruption in the procurement, how software is bought. So we interviewed them in the past, and they're innovating on that. They're going to make that a real great platform. But the fact that Ansible's in the marketplace means that their sales are going to go up, number one. Number two, that means customers can consume it simply by clicking a button on their Amazon bill. That means they don't have to do anything. It's like getting a PO for free. It's like, hey, I'm going to buy Ansible, click, click, click. And then by the way, draw that down from their commitment to AWS. So that means Amazon's going into business with Ansible, and that is a huge revenue thing for Ansible, but also an operational efficiency thing that gives them more of an advantage over the competition. >> Talk what's in it for me as a customer. At Red Hat Summit a few months ago they announced similar partnership with Azure. Now we're talking about AWS. Customers are living in this hybrid cloud world, often by default. We're going to see that proliferate. What do you think this means for customers in terms of being able to- >> In the marketplace deal or Ansible? >> Yeah, the marketplace deal, but also what Red Hat and Ansible are doing with the hyperscalers to enable customers to live successfully in the hyper hybrid cloud world. >> It's just in the roots of the company. They give them the choice to consume the product on clouds that they like. So we're seeing a lot of clients that have standardized on AWS with their dev teams but also have productivity software on Azure. So you have the large enterprises, they sit on both clouds. So you know, Ansible, the customer wants to use Ansible anyway, they want that to happen. So it's a natural thing for them to work anywhere. I call that the Switzerland strategy. They'll play with all the clouds. Even though the clouds are fighting against each other, and they have to to differentiate, there's still going to be some common services. I think Ansible fits this shim layer between clouds but also a bolt on. Now that's a really a double win for them. They can bolt on to the cloud, Azure and bolt on to AWS and Google, and also be a shim layer technically in clouds as well. So there's two technical advantages to that strategy >> Can Ansible be a facilitator of hybrid cloud infrastructure for organizations, or a catalyst? >> I think it's going to be a gateway on ramp or gateway to multicloud or supercloud, as we call it, because Ansible's in that configuration layer. So you know, it's interesting to hear the IBM research story, which we're going to get to in a second around how they're doing the AI for Ansible with that wisdom project. But the idea of configuring stuff on the fly is really a concept that's needed for multicloud 'Cause programs don't want to have to configure anything. (he laughs) So standing up an application to run on Azure that's on AWS that spans both clouds, you're going to need to have that automation, and I think this is an opportunity whether they can get it or not, we'll see. I think Red Hat is probably angling on that hard, and I can see them kind of going there and some of the commentary kind of connects the dots for that. >> Let's dig into some of news that came out today. You just alluded to this. IBM research, we had on with Red Hat. Talk about what they call project wisdom, the value in that, what it also means for for Red Hat and IBM working together very synergistically. >> I mean, I think the project wisdom is an interesting dynamic because you got the confluence of the organic community of Ansible partnering with a research institution of IBM research. And I think that combination of practitioners and research groups is going to map itself out to academic and then you're going to see this kind of collaboration going forward. So I think it's a very nuanced story, but the impact to me is very clear that this is the new power brokers in the tech industry, because researchers have a lot of muscle in terms of deep research in the academic area, and the practitioners are the ones who are actually doing it. So when you bring those two forces together, that pretty much trumps any kind of standards bodies or anything else. So I think that's a huge signaling benefit to Ansible and Red Hat. I think that's an influence of Red Hat being bought by IBM. But the project itself is really amazing. It's taking AI and bringing it to Ansible, so you can do automated configurations. So for people who don't know how to code they can actually just automate stuff and know the process. I don't need to be a coder, I can just use the AI to do that. That's a low code, no code dynamic. That kind of helps with skill gaps, because I need to hire someone to do that. Today if I want to automate something, and I don't know how to code, I've got to get someone who codes. Here I can just do it and automate it. So if that continues to progress the way they want it to, that could literally be a game changer, 'cause now you have software configuring machines and that's pretty badass in my opinion. So that thought that was pretty cool. And again it's just an evolution of how AI is becoming more relevant. And I think it's directionally correct, and we'll see how it goes. >> And they also talked about we're nearing an inflection point in AI. You agree? >> Yeah I think AI is at an inflection point because it just falls short on the scale side. You see it with chatbots, NLP. You see what Amazon's doing. They're building these models. I think we're one step away from model scaling. I think the building the models is going to be one of these things where you're going to start to see marketplace and models and you start to composability of AI. That's where it's going to get very interesting to see which cloud is the best AI scale. So I think AI at scale's coming, and that's going to be something to watch really closely. >> Something exciting. Another thing that was big news today was the event driven Ansible. Talk about that, and that's something they've been working on in conjunction with the community for quite a while. They were very proud of that release and what that's going to enable organizations to do. >> Well I think that's more meat on the bone on the AI side 'cause in the big trend right now is MLAI ops. You hear that a lot. Oh, data ops or AI ops. What event driven automation does is allows you to take things that are going on in your world, infrastructure, triggers, alarms, notifications, data pipelining flows, things that go on in the plumbing of infrastructure. are being monitored and observed. So when events happen they trigger events. You want to stream something, you send a trigger and things happen. So these are called events. Events are wide ranging number of events. Kafka streaming for data. You got anything that produces data is an event. So harnessing that data into a pipeline is huge. So doing that at scale, that's where I think that product's a home run, and I think that's going to be a very valuable product, 'cause once you understand what the event triggers are, you then can automate that, and no humans involved. So that will save a lot of time for people in the the higher pay grade of MLAI ops automate some of that low level plumbing. They move their skill set to something more valuable or more impactful. >> And we talked about, speaking of impact, we talked about a lot of the business impact that organizations across industries are going to be able to likely achieve by using that. >> Yeah, I mean I think that you're going to see the community fill the gap on that. I mean the big part about all this is that their community builds the product and they have the the playbooks and they're shareable and they're reusable. So we produce content as a media company. They'd talk about content as is playbooks and documentation for people to use. So reuse and and reusing these playbooks is a huge part of it. So as they build up these catalogs and these playbooks and rules, it gets better by the community. So it's going to be interesting to see the adoption. That's going to be a big tell sign for what's going to happen. >> Yep, we get definitely are going to be watching that space. And the last thing, we got to talk to a couple of customers. We talked to Wells Fargo who says "We are a tech company that does banking," which I loved. We got to talk with Rockwell Automation. What are some of your takeaways from how the customers are leveraging Ansible and the technology to drive their businesses forward to meet demanding customers where they are? >> I think you're seeing the script flipping a little bit here, where the folks that used to use Ansible for configuration are flipping to be on the front edge of the innovation strategy where what process to automate is going to drive the profitability and scale. Cause you're talking about things like skill gaps, workflows. These are business constructs and people These are assets so they have economic value. So before it was just, IT serve the business, configure some servers, do some stuff. When you start getting into automation where you have expertise around what this means, that's economic value. So I think you're going to see the personas change significantly in this community where they're on the front lines, kind of like developers are. That's why ops as code is to me a developer kind of vibe. That's going to completely change how operations runs in IT. And I think that's going to be a very interesting cultural shift. And some will make it, some won't. That's going to be a big thing. Some people say, I'm going to retire. I'm old school storage server person, or no, I'm the new guard. I'm going to be the new team. I'm going be on the right side of history here. So they're clearly going down that right path in my opinion. >> What's your overall summary in the last minute of what this event delivered the last couple of days in terms of really talking about the transformation of enterprises and industries through automation? >> I think the big takeaway from me in listening and reading the tea leaves was the Ansible company and staff and the community together. It was really a call for arms. Like, hey, we've had it right from the beginning. We're on the right wave and the wave's getting bigger. So expand your scope, uplevel your skills. They're on the right side of history. And I think the message was engage more. Bring more people in because it is open source, and if they are on that track, you're going to see more of hey, we got it right, let's continue. So they got platform release. They got the key products coming out after years of work. So you know, they're doing their work. And the message I heard was, it's bigger than we thought. So I think that's interesting. We'll see what that means. We're going to unpack that after the event in series of showcases. But yeah, it was very positive, I thought. Very positive. >> Yeah, I think there was definitely some surprises in there for them. John, thank you so much. It's been a pleasure co-hosting with you the last couple of days, really uncovering what Ansible is doing, what they're enabling customers in every industry to achieve. >> Been fun. >> Yes. All right for my co-host, John Furrier, I'm Lisa Martin. You've been watching theCUBE's coverage of Ansible Fest 2022 live from Chicago. We hope you take good care and we'll see you soon.
SUMMARY :
for the last two days. It's great to be back in person. on the chess board, so to the last couple of days. of the day they do a good job on the program with So that's the software supply chain issue. in the marketplace. in the marketplace means We're going to see that proliferate. in the hyper hybrid cloud world. I call that the Switzerland strategy. of the commentary kind of the value in that, what it but the impact to me is very clear And they also talked and that's going to be something enable organizations to do. and I think that's going to about a lot of the business So it's going to be interesting and the technology to drive And I think that's going to be and staff and the community together. in every industry to achieve. and we'll see you soon.
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Yolande Piazza & Zac Maufe, Google Cloud
(upbeat music) >> Hello, and welcome to this Cube conversation. I'm Dave Nicholson, and this is part of our continuing coverage of Google Cloud Next 2021. We have a very interesting subject to discuss. I have two special guests from Google to join me in a conversation about the financial services space. I'm joined by Yolande Piazza, vice president of financial services sales for Google Cloud and Zac Mauf, managing director for global financial services solutions for Google Cloud. Yolande and Zac, welcome to the Cube. >> Thank you for having us. Looking forward to it. >> Well it's great to have you here. You know, financial services is really an interesting area when you talk about cloud because I'm sure you both remember a time, not that long ago, when we could ask a financial services organization, what their plans for cloud or what their cloud strategy was, and they would give a one word answer and that answer was, never. (laughing) So Zac, let's start out with you, what has changed? Are you and Yolande going to tell us that in fact, financial services organizations are leveraging cloud now? >> Yeah, it's a very exciting time to be in the cloud space, in financial services, because you're exactly right David. People are starting to make the transition to cloud in a real way. And a lot has gone into that, as you know, it's a highly regulated space and so there were a lot of legitimate reasons around getting kind of the regulatory frameworks in place and making sure that the risk and compliance pieces were addressed. But then there was also, as you know, technology is a major backbone for financial services. And so there's also this question of, how do we transition? And a lot of work and time has gone into moving workloads, thinking about like, what is the sort of the right migration strategy for you to get from the current situation to a more cloud native world. And to your point, we're really early, we're really early, but we're very excited and we've been investing heavily on our side to get those foundational pieces in place. But we also realized that we have to think about what are the business cases, that we want to build on top of cloud. It's not just a kind of IT modernization, which is a big part of the story, but the other part of the story is once you get all of this, technology onto the cloud platform, there are things that you can do that you couldn't do in on-prem situations. And a lot of that for us is around the data, AI and ML space. And we really see that being the way to really unlock huge amounts of value. Both of them require massive amounts of compute and breaking down all of these silos that have really developed over time within financial institutions. And really moving to the cloud is the way to unlock a lot of that. So we're really excited about a lot of those use cases that are starting to come to life now. >> Yeah. So I want to dig a little deeper on some of that Zac, but before we do, Yolande make this real for us. Give me some examples of actual real-life financial services organizations and what they're doing with Google Cloud now. >> Yeah, absolutely. And I think we're really proud to be able to announce, a number of new partnerships across the industry. You think about Wells Fargo, you think about Scotia Bank, you think about what we're doing with HSBC. They really are starting to bring to life and recognized that it's not just internally, you have to look at that transformation to cloud, it's really, how do you use this platform to help you go on the journey with your customers? I think a move to a multi-cloud common approach for our customers and our clients, is exactly what we need to be focused on. And the other- >> Hold on, hold on, Yolande. I'm sorry. Did the Google person just say multi-cloud? Because multi- cloud doesn't sound like, only Google Cloud to me. Can you- >> No, and I think Wells, absolutely, and I think Wells announced it's taking a multi-cloud approach to its digital infrastructure strategy, leveraging both Google Cloud and Microsoft Azure. And the reason being is they've openly communicated that a locked in and preparatory systems, isn't the way to go for them. They want that open flexibility. They want the ability to be able to move workloads across the different industries. And I think it's well known that this aligns completely with our principles and at Google we've always said that we support open multi and hybrid cloud strategies because we believe our customers should be able to run what they want, where they want it. And that was exactly the philosophy that that Wells took. So, and if you look at what they were trying to do is they're looking to be able to serve their customers in a different way. I think that it's true now that customers are looking for personalized services, instant gratification, the ability to interact, where they want and when they want. So we're walking with the Wells teams to really bring to life through AI, our complex AI and data solutions to really enable them to move at speed and serve their customers in a rapidly changing world. >> So Yolande, part of the move to cloud includes the fact that we're all human beings and perception can become reality. Issues like security, which are always at the forefront of someone's mind in financial services space, there is the perception, and then there is the reality. Walk us through today where perception is in the financial services space. And then Zac, I'm going to go back to you to tell us what's the reality. And is there a disconnect? Because often technology in this space has been ahead of people's comfort level for rational reasons. So Yolande, can you talk about from a perception perspective where people are. >> So I have to tell you, we are having conversations with both the incumbents and traditional organizations, as well as, the uprising, the fintechs, and the neobanks around how does technology really unlock and unleash a new business model. So we're talking about things like how does technology and help them grow that organization. How does it take out costs in that organization? How do you use all cloud platform to think about managing risks, whether that's operational, whether it's reputational, industry or regulatory type risk? And then how do we enable our partners and our customers to be able to move at speed? So all of those conversations are now on the table. And I think a big shift from when Zac and I both were sitting on the other side of the table in those financial services industries is a recognition that this couldn't and shouldn't be done alone, that it's going to require a partnership, it's going to require, really shifting to put technology at the forefront. And I think when you talk about perception, I would say a couple of years ago, I think it was more of a perception that they were really technology companies. And I think now we're really starting to see the shifts that these are technology companies serving their customers in a banking environment. >> So Zac, can you give us some- Yeah. Yeah. Zac, can you give us some examples of how that plays out from a solutions perspective? What are some of the things that you and Yolande are having conversations with these folks in? >> Yeah. - I mean, absolutely. I think there's three major trends that we're seeing, where I think we can bring the power of sort of the Google ecosystem to really change business models and change how things are done. The first is really this massive change that's been happening for like over 10 years now, but it's really this change in customers, expecting financial institutions to meet them where they are. And that started with information being delivered to them through mobile devices and online banking. And then it went to payments, and now it's going into lending and it's going into insurance. But it changes the way that financial services companies need to operate because now they need to figure out how to deliver everything digitally, embedded into the experience that their customers are having in all of these digital ecosystems. So there's lot that we're doing in that space. The second is really around modernizing the technology environment. There is still a massive amount of paper in these organizations. Most of it has been transferred to digital paper, but the workflows and the processes that are still needing to be streamlined. And there's a lot that we can do with our AI model and technology to be able to basically take unstructured data and create structured data. Thank Google Photos, you can now search for your photo library and find, pictures of you on bridges. The same thing we can now do with documents and routine interactions with chat bot. People are expecting 24/7 service. And a lot of people want to be able to interact through chat versus through voice. And the final part of this that we're seeing a lot of use cases in is in the kind of risk and regulatory space. Coming out of the financial crisis, there was this need to massively upgrade everybody's data capabilities and control and risk environments, because so much it was very manual, and a lot of the data to do a lot of the risk and control work was kind of glued together. So everybody went off and built data lakes and figured out that that was actually a really difficult challenge and they quickly became data swamps. And so really how do you unlock the value of those things? Those three use cases, and there's lots of things underneath those, are areas that we're working with customers on. And it's, like you said, it's really exciting because the perception has changed. The perception has changed that now cloud is the sort of future, and everybody is kind of now realized they have to figure out how to engage. And I think a lot of the partnership things that Yolande was talking about is absolutely true. They're looking for a strategic relationship versus a vendor relationship, and those are really exciting changes for us. >> So I just imagined a scenario where a Dave, Zac, and Yolande are at the cloud pub talking after hours over a few pints, and Dave says, "Wow, you know, 75%, 80% of IT is still on-premises." And Yolande looks at me and says, "On-premises? We're dealing with on-paper still." Such as the life of a financial services expert in this space. So Yolande, what would you consider sort of the final frontier or at least the next frontier in cloud meets financial services? What are the challenges that we have yet to overcome? I just mentioned, the large amount of stuff that's still on premises, the friction associated with legacy applications and infrastructure. That's one whole thing. But is there one thing that in a calendar year, 2022, if you guys could solve this for the financial services industry, what would it be? And if I'm putting you on the spot, so be it. >> No, no. I'm not going to hold it to just one thing. I think the shift, I think the shift to personalization and how does the power of, you know, AI and machine learning really start to change and get into way more predictive technologies. As I mentioned, customers want to be a segmentation of one. They don't want to be forced fit into the traditional banking ecosystems. There's a reason that customers have on average 14 different financial services apps on their phones. Yep. Less than three to 5% of their screen time is actually spent on them. It's because something is missing in that environment. There's a reason that you could go to any social media site and in no time at all, be able to pull up over 200 different communities of people trying to find out financial services information in layman's terms that is relevant to them. So the ability and where we're really doubling down is on this personalization. Being way more predictive, understanding where a customer is on their journey and being able to meet them at that point, whether that's the bright offers, whether that's recognizing, to Zac's point, that they've come in on one channel but they now want to switch to another channel. And how do they not have to start again every time? So these are some of the basics things, so we really doubled down on how do we start to solve in those areas. I think also the shift, I think in many cases, especially in the risk space, it's been very much what I would call, a people process technology approach, start to imagine what happens if you turn that around and think about how technology can help you be more predictive internally in your business and create better outcomes. So I think there's so many areas of opportunities, and what's really exciting is we're not restricted, we're having conversations that are titled, the art of the possible, or the future of, or help us come in and reinvent. So I think you're going to see a lot of shift probably in the next 12 to 18 months, I would say, and the capabilities and the ability to service the customer differently and meet them on their journey. >> Well, it sounds like the life of a cloud financial services person is much more pleasurable than back when it consisted of primarily running into brick walls constantly. This conversation five or 10 years ago would have been more like, please trust us, please. Just give us a shot. >> I think Zac and I both reminisce that we couldn't have joined at a more exciting time. It's the locker or whatever you want to call it, but it is a completely different world and the conversations are fun and refreshing, and you can really start to see how we have the ability to partner to change the landscape, across all of the different financial services industries. And I think that's what keeps Zac and I going every day. >> And you said earlier that you alluded to the idea that you used to be on the other side of the table, in other words, in the financial services industry on the customer side. So you pick the right time to come across. >> Without a doubt, without a doubt. Yes. >> Well, with that, I want to thank both of you for joining me today. This is really fascinating. Financial services is something that touches all of us individually in our daily lives. It's something that everyone can relate to at some level. And it also represents, that tip of the spear, the cutting edge of cloud. So very interesting. Thank you both again, pleasure to meet you both. Next time, hopefully it will be in-person and we can compare our steps that we've taken during the conference. With that I'll sign off. This has been a fantastic Cube conversation, part of our continuing coverage of Google Cloud Next 2021. I'm Dave Nicholson, Thanks again for joining us. >> Thank you. (upbeat music)
SUMMARY :
subject to discuss. Looking forward to it. Well it's great to have you here. and making sure that the risk and what they're doing to help you go on the only Google Cloud to me. the ability to interact, And then Zac, I'm going to go back to you And I think when you of how that plays out from and a lot of the data So Yolande, what would you consider and how does the power of, you Well, it sounds like the life and you can really start to that you alluded to the idea Without a doubt, without a doubt. pleasure to meet you both. Thank you.
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Mark Hinkle | KubeCon + CloudNativeCon NA 2021
(upbeat music) >> Greetings from Los Angeles, Lisa Martin here with Dave Nicholson. We are on day three of the caves wall-to-wall coverage of KubeCon CloudNativeCon North America 21. We're pleased to welcome Mark Hinkle to the program, the co-founder and CEO of TriggerMesh. Mark welcome. >> Thank you, It's nice to be here. >> Lisa: Love the name. Very interesting TriggerMesh. Talk to us about what TriggerMesh does and what, when you were founded and what some of the gaps were that you saw in the market. >> Yeah, so TriggerMesh actually the Genesis of the name is in, cloud event, driven architecture. You trigger workloads. So that's the trigger and trigger mesh, and then mesh, we mesh services together, so cloud, so that's why we're called TriggerMesh. So we're a cloud native open source integration platform. And the idea is that, the number of cloud services are proliferating. You still have stuff in your data center that you can't decommission and just wholesale lift and shift to the cloud. So we wanted to provide a platform to create workflows from the data center, to the cloud, from cloud to cloud and not, and use all the cloud native design principles, but not leave your past behind. So that's, what we do. We're, very, we were cloud, we are cloud operators and developers, and we wanted the experience to be very similar to the way that DevOps folks are doing infrastructure code and deploying that we want to make it easy to do integration as code. So we follow the same design patterns, use the same domain languages, some of those tools like Hashi corpse, Terraform, and that that's what we do and how we go about doing it. >> Lisa: And when were you guys founded? >> September, 2018. >> Oh so your young, your three years young. >> Three years it's feels like 21 >> I bet. >> And startup years it's a lot has happened, but yeah, we my co-founder and I were former early cloud folks. We were at cloud.com worked through the OpenStack years and the CloudStack, and we just saw the pattern of, abstraction coming about. So first you abstract the hardware, then you abstract the operating system. And now at with the Kubernetes container, you know, evolution, you're abstracting it up to the application layer and we want it to be able to provide tooling that lets you take full advantage of that. >> Dave: So being founded in 2018, what's your perception of that? The shift that happened during the pandemic in terms of the drive towards cloud adoption and the demands for services like you provide? >> Mark: Yeah, I think it's a mixed blessing. So we, people became more remote. They needed to enable digital transformation. Biggest thing, I think that that for us is, you know, you don't go to the bank anymore. And the banking industry is doing, you know, exponentially more remote, online transactions than in person. And it's very important. So we decided that financial services is where we were going to start with first because they have a lot of legacy architecture. They have a lot of need to move to the cloud to have better digital experiences. And we wanted to enable them to, you know, keep their mainframes online while they were still doing cutting edge, you know, mobile applications, that kind of thing. >> Lisa: And of course the legacy institutions like the BFA's the Wells Fargo, they're competing with the fintechs who are much more nimble, much more agile and able to sort of disrupt the financial services industry. Was that part of also your decision to start in financial services? >> It was a little bit of luck because we started with our network and it turned out the, you know, we saw, we started talking to our friends early on, cause we're a startup and said, this is what we're going to do. And where it really resonated was PNC bank was our, one of our first customers. You know, another financial regulatory company was another one, a couple of banks in Europe. And we, you know, as we started talking about what we were doing, that we just gravitated there because they had the, the biggest need, even though everybody has the need, their businesses are, you know, critically tied to digital transformation. >> So starting with financial services. >> It's, it's counter intuitive, isn't it? >> It was counterintuitive, but it lends credibility to any other industry vertical that you're going to approach. >> Yeah, yeah it does. It's a, it's a great, they're going to be our hardest customers and they have more at stake than a lot of like transactions are millions and millions of dollars per hour for these folks. So they don't want to play around, they, they have no tolerance for failure. So it's a good start, but it's sort of like taking up jogging and running a marathon in your first week. It's very very grilling in that sense, but it really has made us a lot better and gave us a lot of insight into the kinds of things we need to do from not just functionality, but security and that kind of thing. >> Where are you finding these customers with respect to adoption of Kubernetes? Are they leading? Are they knowing we've got to get there eventually from an infrastructure perspective? >> So the interesting thing is Kubernetes is a platform for us to deliver on, so we, we don't require you to be a Kubernetes expert we offer it as a SaaS, but what happens is that the Kubernetes folks are the ones that we end up really engaging with earlier on. And I think that we find that they're in this phase of they're containerizing their apps, that's the first step. And then they're putting them on Kubernetes and then their next step is a security and integration path. So once she, I think they call it and this is my buzzword of the show day two operations, right? So they, they get to day two and then they have a security and an integration concern before they go live. So they want to be able to make sure that they don't increase their attack face. And then they also want to make sure that this newly deployed containerized infrastructure is as well integrated as the previous, you know, virtualized or even, you know, on the server infrastructure that they had before. >> So TriggerMesh, doesn't solely work in the containerized world, you're, you're sort of you're bridging the divide. >> Mark: Yes. >> What percentage of the workloads that you're seeing are the result of modernization migration, as opposed to standing up net new application environments in Kubernetes? Do you have a sense for that? >> I think we live in a lot in the brown field. So, you know, folks that have an existing project that they're trying to bridge to it versus the Greenfield kind of, you know, the, the huge wins that you saw in the early cloud days of the Netflix and the Twitter's Dwayne scale. Now we're talking to the enterprises who have, you know, they have existing concerns. So I would say that it's, it's mostly people that are, you know, very few net new projects, unless it's a modernization and they're getting ready to decommission an old one, which is. >> Dave: So Brownfield financial services. You just said, you know, let's just, let's just go after that. >> You know, yeah. I mean, we had this dart forward and we put up buzzwords, but no, it was, it was actually just, and you know, we're still finding our way as far as early on where we're open source folks. And we did not open source from day one, which is very weird when everybody's new, your identity is, you know, I worked, I was the VP of marketing for Linux foundation and no JS and all these open source projects. And my co-founder and I are Apache committers. And our project wasn't open yet because we had to get to the point where it could be open and people could be productive in the use and contribution. And we had to staff up engineers. And now I think this week we open-sourced our entire platform. And I think that's going to open up, you know, that's where we started because it was not necessarily the lowest hanging fruit, but the profitable, less profitable, lowest hanging fruit was financial services. Now we are letting our code out into the wild. And I think it'll be interesting to see what comes back. >> So you just announced that this week TriggerMesh integration platform as an open source project here at KubeCon, what's been some of the feedback? >> It's all been positive. I haven't heard anything negative. We did it, so we're very, very, there's a very, the culture around open source is very tough. It's very critical if you don't do it right. So I think we did a good job, we used enough, we used a OSI approved. They've been sourced, licensed the Apache software, a V2 license. We hired someone who was well-respected in the DevREL world from a chef who understands the DevOps sort of culture methodologies. We staffed up our engineers who are going to be helping the free and open source users. So they're successful and we're betting that that will yield business results down the road. >> Lisa: And what are the two I see on your website, two primary use cases that you guys support. Can you dig into details on that? >> So the first one is sort of a workflow automation and a really simple example of that is you have a, something that happens in one cloud. So for example, you take a picture on your phone and you upload it and it goes to Amazon and there is a service that wants to identify what's in that picture. And once you put it on the line and the internship parlance, you could kick off a workflow from TensorFlow, which is artificial intelligence to identify the picture. And there isn't a good way for clouds to communicate from one to the other, without writing custom blue, which is really what, what we're helping to get rid of is there's a lot of blue written to put together cloud native applications. So that's a workflow, you know, triggering a server less function is the workflow. The other thing is actually breaking up data gravity. So I have a warehouse of data, in my data center, and I want to start replicating some portion of that. As it changes to a database as a service, we can based on an event flow, which is passive. We're not, we're not making, having a conversation like you would with an API where there's an event stream. That's like drinking from the fire hose and TriggerMesh is the nozzle. And we can direct that data to a DBaaS. We can direct that data to snowflake. We can direct that data to a cloud-based data lake on Microsoft Azure, or we can split it up, so some events could go to Splunk and all of the events can go to your data lake or some of those, those things can be used to trigger workloads on other systems. And that event driven architecture is really the design pattern of the individual clouds. We're just making it multi-cloud and on-prem. >> Lisa: Do you have a favorite customer example that you think really articulates that the value of that use case? >> Mark: Yeah I think a PNC is probably our, well for the, for the data flow one, I would say we have a regular to Oracle and one of their customers it was their biggest SMB customer of last year. The Oracle cloud is very, very important, but it's not as tool. It doesn't have the same level of tooling as a lot of the other ones. And to, to close that deal, their regulatory customer wanted to use Datadog. So they have hundreds and hundreds of metrics. And what TriggerMesh did was ingest the hundreds and hundreds of metrics and filter them and connect them to Datadog so that, they could, use Datadog to measure, to monitor workloads on Oracle cloud. So that, would be an example of the data flow on the workflow. PNC bank is, is probably our best example and PNC bank. They want to do. I talked about infrastructure code integration is code. They want to do policy as code. So they're very highly regulatory regulated. And what they used to do is they had policies that they applied against all their systems once a month, to determine how much they were in compliance. Well, theoretically if you do that once a month, it could be 30 days before you knew where you were out of compliance. What we did was, we provided them a way to take all of the changes within their systems and for them to a server less cluster. And they codified all of these policies into server less functions and TriggerMesh is triggering their policies as code. So upon change, they're getting almost real-time updates on whether or not they're in compliance or not. And that's a huge thing. And they're going to, they have, within their first division, we worked with, you know, tens of policies throughout PNC. They have thousands of policies. And so that's really going to revolutionize what they're able to do as far as compliance. And that's a huge use case across the whole banking system. >> That's also a huge business outcome. >> Yes. >> So Mark, where can folks go to learn more about TriggerMesh, maybe even read about more specifically about the announcement that you made this week. >> TriggerMesh.com is the best way to get an overview. The open source project is get hub.com/triggermesh/trigger mesh. >> Awesome Mark, thank you for joining Dave and me talking to us about TriggerMesh, what you guys are doing. The use cases that you're enabling customers. We appreciate your time and we wish you best of luck as you continue to forge into financial services and other industries. >> Thanks, it was great to be here. >> All right. For Dave Nicholson, I'm Lisa Martin coming to you live from Los Angeles at KubeCon and CloudNativeCon North America 21, stick around Dave and I, will be right back with our next guest.
SUMMARY :
the co-founder and CEO of TriggerMesh. Talk to us about what the data center, to the cloud, Oh so your young, So first you abstract the hardware, I think that that for us is, you know, like the BFA's the And we, you know, but it lends credibility to any So they don't want to play around, as the previous, you know, the containerized world, it's mostly people that are, you know, You just said, you know, to open up, you know, So I think we did a good that you guys support. So that's a workflow, you know, we worked with, you know, announcement that you made this week. TriggerMesh.com is the and me talking to us about you live from Los Angeles at
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Vicki Harris, Chevron | UiPath FORWARD IV
>>From the Bellagio hotel in Las Vegas, it's the cube covering UI path forward for brought to you by >>Hello from Las Vegas, live at the Bellagio. Lisa Martin, with Dave Volante. We are at UI path forward for, like I said, in Las Vegas. So great to be in person, sitting at an anchor desk with a co-anchor. And I guess we're going to be talking about deploying new technologies and a large global enterprise. Nikki Harris is here. Manage your application, performing platform engineering services at Chevron Vicky. Welcome to the program. Hey, thank >>You. Happy to be >>Here. So isn't it great to be we're outdoors. Nice that everyone's nice and safe, but great to be back at an in-person event where so many hallway conversations can spark more innovation. That's one of the things I think a lot of us have been missing in the last 18 months. You've been with Chevron almost 15 years, but this is, we're talking about 142 year old organization. Talk to me about the evolution of it that you've seen. >>Very happy to do that. Um, a lot of, uh, I would say the greatest jump forward we saw in cloud and we started our cloud transformation before digital transformation came along. Uh, but it was the, really the thing that enabled us to, uh, be ready, I would say for the extra value, the extra push. And so we were so happy to be well positioned. So we started our cloud journey in 2017 and, uh, between 2018 and 19, because of the investments in automation, it just took off and today we're still receiving the benefits of that. Um, but prior to that, it took a little bit longer. Uh, also we had an agile transformation, which was very helpful because we can't really afford to move at waterfall speed anymore. Um, and so cloud and agile really helped boost that and get us started. >>So whenever we get a practitioner on, we have a million questions. So, so can we start with your role? Are you in it, that's where you're in that organization or >>I am in it. So I'm a product line manager. We support really the core for software engineers and citizen developers. So on the software engineering side, CICB pipeline, dev ops tooling, code frameworks, all of that to make our software engineers more productive and on the citizen development side, same philosophy, we want to make them more productive, not worry about how do I do it, just how to apply their business logic. So we support the citizen development programs and the underlying platforms. >>So they gave, when you talked about cloud in 2017, are you talking about infrastructure as a service platform, as a service SAS, all of the above, cause cause you have to do, I'm sure you were doing SAS before then, but how do you think about cloud? >>So that's a great question. Yes. We were always doing SAS and we continue to do SAS. Uh, so, and Chevron was one of the earlier adopters of UI path for cloud. We do want to be cloud first, always, always, always. And we are trying to really reduce and restrict our on-prem footprint. Um, but the automation we started in kind of 20 17, 20 18 is, um, I would call it infrastructure as code. Uh, so deploying everything with code, um, the same way all the time, uh, which was partly a technical shift, but also a really big cultural shift that instead of having people doing the same task, you know, 400 different ways, which is hard to sustain, it's hard to troubleshoot. Uh, so we took the pain in, in building that and there's a lot of pain in, in the transformation itself, but the upside when you're finished is amazing. >>Yeah. So that's what you just answered. My next question, which was what is the catalyst? It was seeing the clouds potential for programmable infrastructure. And that sounds like it was a game changer. >>It was a huge game changer. And that really, uh, on the software engineering side, the whole way we do infrastructure, the way we program everything. Uh, but we also found we're not touching part of the organization with that transformation. And that's where the citizen development programs and RPA comes in is, you know, Hey, we're really proud of ourselves. We did so well, but how do we get to the edge, uh, where we haven't been able to have the same impact with that automation >>For an organization that I mentioned 142 years young will say, I guess you could say old for an organization young for a person where in, in terms of the cultural change, that's hard to, to manifest across such a historic history institution. Talk to me about the appetite for automation. You said you guys started doing automation, bringing it into the organization and in the last five years or so, what's been the appetite across different lines of business to embrace it, to see it as an advantage rather than taking jobs away. >>Uh, so there's never appetite for automation on its own because you're changing someone's process. Um, but what there is appetite for is the results. Uh, and also, uh, we went through a large organizational transformation. So in addition to value, um, you know, bottom line cost savings, we have people who are just improving their, their workflow for themselves. And so there's also a sense of empowerment for them. So I would say the empowerment and then the results are much bigger drivers. And then you say, oh, if you want that, yes, by the way, this is how we get that. But it's not, you know, automation for automation sake. Uh, but people understand, they understand now the value of it and they, the more they learn, they understand that, um, doing one process 25 ways, it's not a way to run your business, >>Right. How to actually drive this outcomes that they're looking for. >>So how did it start? When did it start in? It was an it led initiative or was it a department? >>It led, >>Yes. Okay. And so, so focused on the it department. So you automating certain tasks within it or, or not necessarily >>Necessarily. So, um, it led, but as the foundation for all the business units. So again, we focus on the core, but we also focus on enablement. So anybody who's a builder maker, developer out there in the business units, we just want to make their job easier, better, faster, um, just for the business logic. So then we'd bring them in and say, here's how you do it. Um, but they bring the best ideas, right? They know their business processes. I don't know their business processes. If I sat down and said, here's where automation value is, um, we wouldn't be doing so well. They know where it is. Uh, we just give them the tools to, to find that value. And you know, it's extraordinary how they find it. If there's a lot of manual processes out there, >>A common story, when you talk to UI path, customers, that'll start maybe one person in a department and then people looking over her shoulder going, oh, I want some of that. And then it explodes. It sounds like you were taking a much more whole house approach. >>We are taking a whole house approach, but we did start early with POC. Uh, and so, and then those proved their value pretty easily and pretty quickly. And so then it was a determination of, Hey, we would like to do something bigger here than just leave this technology out there. We're just leaving all this value on the table. We're leaving all this skill sets, all this passion, all this enthusiasm in our citizen community. We don't think we can transform as a corporation. If we leave that energy motivation skill on the table >>And some color to the ROI. Have you said to POC, you're a good, quick hit, obviously. Could you give us some details on that? What can you tell us? >>What can I tell you? Okay, well, so, um, from when we started the program three years, I think we're showing about $6 million of return. Um, we, we see the value just in time savings like everybody else does. And we have, so that's with about, um, 300 automations, six over 600,000 hours I think saved. Uh, but first year it's just so easy. You can see it. It's not hard to calculate it, the hour saving, very simple calculation. So anybody who's concerned about ROI, it's so simple, it's so easy. You should be able to find it in your first year if you're not finding it in your first year. Um, I mean, obviously it grows, but if you're not finding some return in the first year, I would say, you know, take a look at what you need to adjust because it's not that hard >>CFO. Sorry. One more question. If I may, and your CFO saw that, okay. Time-savings essentially was the business result, but it wasn't necessarily it, was it hard or were they, did your CFO say, ah, that's kind of soft dollars or is it >>Both hard and soft? So, and yeah, we would never put a dollar sign next to something that doesn't hit the income statement. So I'm very careful about that. Right. Um, but yeah, it's both because some times, um, somebody actually changed their group first and they're feeling the process pain after. And so the healing of automating something. So the, just the two people can do it. Uh, we've seen that use case as well. It's harder to capture any savings because it's not really savings there, but it's, it's um, more of a job satisfaction. So there's a lot of soft benefits that go with it, but we don't usually, you know, commit, turn that into dollars. That's not very valuable. Yeah. >>Use those employee Mo employees that are far more productive are eventually helping the customers be more productive as well. I think they're directly linked. Well, you said you found ROI quickly and that's something that you iPad says about itself that customers are generally achieving an ROI of a break even within months alone. So when you talk to other professionals in oil and gas, how do you talk to them about automation being really a critical driver of that business's success and transformation? >>Uh, I think in large enterprises, whether they're in our sector or not, some of them just struggle with the sheer scale, it's almost like, where do I start? So they do see the value. Uh, but it's more about how do I, how do I start this thing? How do I scale this thing? How do I structure a program? Um, I have not found anyone that says, I don't believe the value proposition again, it's pretty easy to do. >>And the RPA POC started after cloud. Right. So it was, am I right about that? It was 18, 19 timeframe. >>Uh, I would say actually starting around the same time were done in, in 2017. So yeah. >>And so, uh, was there anything specific in your industry that you targeted? I mean, you obviously wanted to hit the high value items first. Was there anything particular there? >>Um, that's a really good question. I think we, our journey looks like other companies kind of, they start with the back office. Those are the easiest processes to, for people to understand. And just in terms of, you know, where do I have a heavy manual load? Uh, so some of our first work was with finance in currency conversion. So pretty, pretty manual intensive for a global company. Pretty big deal, lots of immediate value. Uh, but if you think of, let's talk about Wells. So, you know, we have systems for mapping, Wells drilling, Wells, uh, you'd be surprised some of those systems look kind of like your ERP. They have kind of the same challenges. So, um, as we extend outside of traditional kind of HR finance audit practices into the rest of our business, the use cases are similar. Um, I've got disparate documents. I have systems that don't talk to each other. Well, I have somebody who S and we have a lot of partners. So if you're in a project with five partners and everybody's producing a different type of document or something, how do you make some sense out of that? Uh, so use cases like that, um, we're finding in our upstream and downstream businesses also, >>And you did an RFP at the time, wrote a bunch of vendors and ran them through the cycles or >>Comparisons yeah. Early on >>While UI path, what was it about >>Strong user experience? So, uh, because this is primarily citizen enabled and so that feedback, Hey, could I learn this quickly? Was it easy to use? Those were really the most important things in selection. I mean, we always look at costs that's important too. Um, but also a company's position. So their ability to scale and grow. Um, there's a lot of people in this market, uh, because of the interest in automation. Uh, so part of it is also understanding the strength of the company behind as well. >>One of the things that was mentioned in the keynote this morning, I think it was a stat from Gartner that in 2016, or was about 2% of, um, automateable processes were automated fast forward. Now it's about 25%. There's still a tremendous amount of potential for organizations and any industry to deploy automation. You've said, you've got about 300 plus automation so far. What are some of the things that are coming next that you can see, >>Sure. What is our upside, or where do we stop or our growth taper? Um, I don't think we know, uh, we get so much from our user community in terms of what can we do now? Um, there are so empowered, so I wouldn't want to set limits on ourselves in terms of what we can do. Uh, but certainly we're looking at, um, text analytics, really, how do we manage that document? How do we extract that data, use models to get that into our data lake? Uh, but there's still always the work of finding still that last mile of process. There's many parts of our business still untouched. And so we don't, we don't let, or we don't want to let up on that. That's still important to go after all of that and keep the programs going >>W Chevron huge company. And you've got probably one of everything that's ever been invented in technology. We're seeing a trend where a lot of these, these software companies are embedding RPA into their platforms. You see it with the ERP vendors, uh, uh, acquisitions being made for service management, you know, big cloud guys ha have, uh, you know, on and on and on. And, and so how do you think about those sort of vertically integrated stacks versus what you're doing with UI path? >>So for me, I think of them the same as a code extension. So, because that was more popular a few years ago on those big platforms and you're right, we have one of everything. Um, but it's important to when you think of investment and ROI, uh, where do we actually spend money? It's in maintaining the capability, keeping the programs, doing the training, that's an investment. And so when someone comes to me and says, can you support some other tool? Um, I usually say maybe not, is there a business case for that because we want to be able to deploy to the whole enterprise, um, that isn't to say that somebody who's got a workflow that stays within that platform, that that might be inappropriate use for them, but a very sure it's not an appropriate use to extend it out of that platform somewhere else. >>Uh, and so we draw the line really, what do we, enterprise automation. We want to be very careful about the tools we use for that. And, and the reason for that is not just security, reliability, and the ability to scale those programs. Because when someone calls me and says, my stuff doesn't scale, it's like ours does. Um, and so, but the org capability investment is also it's, it's not small. Uh, and so if you've got to believe in this, you have to keep feeding it. You have to keep training new people, bringing them on. Uh, and so you can't really do that across 12 platforms, right? >>You're creating your own flywheel and that's how you can accelerate ROI. Right? >>Correct. Although, you know, the citizen developers are driving the wheel for sure. >>You, as in Chevron mean not Vicki, Inc. >>Vicky, thank you so much. We are out of time, but thanks for stopping by talking to us about automation in a large global enterprise at Chevron. I won't look at Chevron at the same again. Now I know how forward-thinking they are and how much they are embracing technology. We appreciate your time. >>It's been my pleasure. Thank you both. >>All right. For Dave Volante and Lisa Martin, we live at the Bellagio in Las Vegas UI path forward for we'll be right back.
SUMMARY :
So great to be in person, Nice that everyone's nice and safe, but great to be back at an in-person And so we were so happy to be well positioned. we start with your role? So we support the citizen development programs and Um, but the automation we started in And that sounds like it was a game changer. Uh, but we also found we're not touching part of the organization with that transformation. and in the last five years or so, what's been the appetite across different lines of business to embrace it, So in addition to value, um, you know, bottom line cost savings, How to actually drive this outcomes that they're looking for. So you automating certain tasks within So then we'd bring them in and say, here's how you do it. A common story, when you talk to UI path, customers, that'll start maybe one person in a department And so then it was a determination of, Hey, we would like to do something bigger here And some color to the ROI. And we have, so that's with about, was it hard or were they, did your CFO say, ah, that's kind of soft dollars or So there's a lot of soft benefits that go with it, but we don't usually, you know, commit, So when you talk to other professionals in oil and gas, Um, I have not found anyone that says, I don't believe the value proposition And the RPA POC started after cloud. Uh, I would say actually starting around the same time were done in, that you targeted? Uh, but if you think of, let's talk Comparisons yeah. So their ability to scale and grow. What are some of the things that are coming next that you can see, And so we don't, we don't let, or we don't want to let up on that. And, and so how do you think about those sort of vertically integrated stacks versus Um, but it's important to Uh, and so you can't really do that across 12 platforms, You're creating your own flywheel and that's how you can accelerate ROI. Although, you know, the citizen developers are driving the wheel for sure. Vicky, thank you so much. Thank you both. UI path forward for we'll be right back.
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Liz Dennett, AWS and Johan Krebbers, Shell | AWS Executive Summit 2020
>> Narrator: From around the globe, it's theCUBE. With digital coverage of AWS Reinvent Executive Summit 2020. Sponsored by Accenture and AWS. >> Welcome everyone to theCUBE virtual coverage of the Accenture Executive Summit part of AWS Re-invent 2020. I'm your host, Rebecca Knight. We are talking today about reinventing the energy data platform. We have two guests joining us. First, we have Johan Krebbers. He is the GM Digital Emerging Technologies and VP of IT Innovation at Shell. Thank you so much for coming on the show, Johan. >> You're welcome. >> Rebecca: And next we have Liz Dennett. She is the Lead Solution Architect for OSDU on AWS. Thank you so much Liz. >> Happy to be here. >> So I want to start our conversation by talking about OSDU. Like so many great innovations, it started with a problem. Johann, what was the problem you were trying to solve at Shell? >> Yeah, let's go back a couple of the years. We started summer 2017, where we had a meeting with the guys from exploration in Shell. And the main problem they had of course they got lots and lots of data, but aren't unable to find the right data they need to work from. Well the data was scattered and is scattered, it was scattered it's all over the place. And so the real problem trying to solve is how that person working in exploration could find their proper data, not just the data also the data really needed. That's what we probably talked about in summer 2017. And we said, "Okay, the only way we see this moving forward is to start pulling that data into a single data platform." And that was at the time that we called it OSDU, the Open Subsurface Data Universe, and that was what the Shell name was. So, in January 2018, we start a project with Amazon to start creating and confronting the building that OSDU environment, that subservient the universe. So that single data platform to put all your exploration and wealth data into a single environment that was the intent. And then we said, already in March of that same year, we said, 'Well, from a Shell point of view, we would be far better off if we could make this an industry solution and not just a Shell solution." Because Shell will be, if you can make this an industry solution, but people start developing applications for it also, it's far better than for Shell to say, we have it Shell special solution. Because we don't make money out of how we store the data we can make money out of we have access to the data, we can exploit the data. So storing the data, we should do as efficiently possibly can. So in March we reached out to about eight or nine other large oil and gas operators, like the ECONOS, like the Totals, like the Chevrons of this world they said, "Hey, we in Shell are doing this, do you want to join this effort?" And to our surprise, they all said yes. And then in September 2018 we had our kick-off meeting with the open group, where we said, "Okay, if you want to work together with lots of other companies, we also need to look a bit at how we organize that." Because if you start working with lots of large companies you need to have some legal framework around it. So that's why, we went to the open group and said," Okay, let's form the OSDU forum." As we call it at the time. So in September, 2018 where I had a Galleria in Houston we had a kick off meeting for the OSDU forum with about 10 members at the time. So there's, just over two years ago, we started to exercise formally we called it OSDU, we kicked it off. And so that's really where we coming from and how we got there also. >> The origin story. >> Yes. >> What, so what, digging a little deeper there, what were some of the things you were trying to achieve with the OSDU? >> Well, a couple of things we've tried to achieve with OSDU. First is really separating data from applications. But what is the biggest problem we have in the subsurface space that the data and applications are all interlinked. They are all tied together and if you have then a new company coming along and say, "I have this new application, and needs access to the data." That is not possible because the data often interlinked with the application. The first thing we did is, really breaking the link between the application and the data. So that was the first thing we did. Secondly, put all the data to a single data platform, take the silos out because what was happening in the subsurface space I mean, they got all the data in what we call silos, in small little islands out there. So we try to do is, first, break the link. Two, create, put the data in a single data platform. And then third part, put a standard layer on top of that the same API layer on top of the created platform so we could create an ecosystem out of companies to start developing software applications on top of that data platform. Because you might have a data platform, but you aren't successful if you have a rich ecosystem of people start developing applications on top of that. And then you can exploit the data like small companies, large companies, universities, you name it. But you have to create an ecosystem out of there. So the three things was, first break the link between the application data, just break it and put data at the center. And also make sure that data, this data structure would not be managed by one company. But it would be managed the data structures, by the OSDU forum. Secondly then, put the data, single data platform. Thirdly then, have an API layer on top and then create an ecosystem, really go for people, say, "Please start developing applications." Because now you have access to the data, because the data is no longer linked to somebody's application was all freely available for an API layer. That was all September, 2018, more or less. >> Liz I want to bring you, in here a little bit. >> Yeah. >> Can you talk a little bit some of the imperatives from the AWS standpoint in terms of what you were trying to achieve with this? >> Yeah, absolutely. And this whole thing is Johan said, started with a challenge that was really brought out at Shell. The challenges that geoscientists spend up to 70% of their time looking for data. I'm a geologist I've spent more than 70% of my time trying to find data in these silos. And from there, instead of just figuring out, how we could address that one problem, we worked together to really understand the root cause of these challenges. And working backwards from that use case, OSDU and OSDU on AWS has really enabled customers to create solutions that span not just this in particular problem. But can really scale to be inclusive of the entire energy value chain and deliver value from these used cases to the energy industry and beyond. >> Thank you. Johan, so talk a little bit about Accenture's Cloud First approach and how it has helped Shell work faster and better with speed. >> Well, of course Accenture Cloud First approach, really works together with Amazon environment, AWS environment. So we really look at Accenture and Amazon together, helping Shell in this space. Now the combination of the two is what we're really looking at where access of course can bring business knowledge to that environment, operate support knowledge to an environment and of course Amazon will be bring that to this environment, that underpinning services, et cetera. So we would expect of that combination, a lot of goods when we started rolling out in production, the other two or three environment. And probably our aim is, when a release fee comes to the market, in Q1 next year of OSDU have already started going out in production inside Shell. But as the first OSDU release which is ready for prime time production across an enterprise. Well we have released our one just before Christmas, last year, released two in May of this year. But release three is the first release we want to use for full scale production and deployment inside Shell and also all the operators around the world. And there is what Amazon, sorry and there when Accenture can play a role in the ongoing, in the deployment building up, but also support environment. >> So one of the other things that we talk a lot about here on theCUBE is sustainability and this is a big imperative at so many organizations around the world in particular energy companies. How does this move to OSDU, help organizations become how is this a greener solution for companies? >> Well, first we make, it's a great solution because you start making a much more efficient use of your resources, which is a really important one. The second thing we're doing is also we started with OSDU in very much in the oil and gas space, within the export development space. We've grown OSDU but in our strategy, we've grown OSDU now also to an alternative energy source. So obviously we'll all start supporting next year things like solar farms, wind farms, the geothermal environment, hydrogen. So it becomes an open energy data platform not just for the oil and gas industry, but for any type of industry, any type of energy industry. So our focus is to create, bring the data of all those various energy data sources together into a single data platform. You're going to use AI and other technology on top of that, to exploit the data to be together into a single data platform. >> Liz, I want to ask you about security, because security is such a big concern when it comes to data. How secure is the data on OSDU? >> Actually, can I talk, can I do a follow-up on the sustainability talking? >> Absolutely by all means. >> I mean, I want to interject, though security is absolutely our top priority I don't mean to move away from that but with sustainability, in addition to the benefits of the OSDU data platform. When a company moves from on-prem to the cloud they're also able to leverage the benefits of scale. Now, AWS is committed to running our business in the most environmentally friendly way possible. And our scale allows us to achieve higher resource utilization and energy efficiency than a typical on-prem data center. Now, a recent study by 451 research found that, AWS's infrastructure, is 3.6 times more energy efficient than the median of surveyed enterprise data centers. Two thirds of that advantage is due to a higher server utilization and a more energy efficient server population. But when you factor in the carbon intensity of consumed electricity and renewable energy purchases 451 found that, AWS performs the same task with an 88% lower carbon footprint. Now that's just another way that AWS and OSDU are working to support our customers as they seek to better understand their workflows and make their legacy businesses less carbon intensive. >> That's, those statistics are incredible. Do you want to talk a little bit now about security? >> Absolutely yeah. Security will always be AWS's top priority. In fact, AWS has been architected to be the most flexible and secure cloud computing environment available today. Our core infrastructure is built to satisfy the security requirements for the military, global banks and other high sensitivity organizations. And in fact, AWS uses the same secure hardware and software to build and operate each of our regions. So that customers benefit from the only commercial cloud that's had hit service offerings and associated supply chain vetted and deemed secure enough for top secret workloads. That's backed by a deep set of cloud security tools with more than 200 security compliance and governmental service and key features. As well as an ecosystem of partners like Accenture, that can really help our customers to make sure that their environments for their data meet and or exceed their security requirements. >> Johann, I want you to talk a little bit about how OSDU you can be used today. Does it only handle subsurface data? >> Today is 100 subsets of wells data we go to add that to that production around the middle of next year. That means that the whole upstream business we got included every piece goes from exploration all the way to production, you bring it together into a single data platform. So production will be added around Q3 of next year. Then in principle, we have a typical elder data, a single environment and we're going to extend them to other data sources or energy sources like solar farms, wind farms, hydrogen, hydro, et cetera. So we're going to add a whole list of other day energy source to that and bring all the data together into a single data platform. So we move from an oil and gas data platform to an energy data platform. That's really what our objective is because the whole industry if you look at our companies all moving in that same direction of course are very strong in oil and gas but also increasingly go into other energy sources like solar, like wind, like hydrogen et cetera. So we move exactly with the same method, that the whole OSDU, can really support that whole energy spectrum of energy sources, of course. >> And Liz and Johan, I want you to close us out here by just giving us a look into your crystal balls and talking about the five and 10 year plan for OSDU. We'll start with you, Liz. What do you see as the future holding for this platform? >> Honestly, the incredibly cool thing about working at AWS is you never know where the innovation and the journey is going to take you. I personally am looking forward to work with our customers wherever their OSDU journeys, take them whether it's enabling new energy solutions or continuing to expand, to support use cases throughout the energy value chain and beyond but really looking forward to continuing to partner as we innovate to slay tomorrow's challenges. >> Johan. >> Yeah, first nobody can look that far ahead anymore nowadays, especially 10 years. I mean, who knows what happens in 10 years? But if you look what our objective is that really in the next five years, OSDU will become the key backbone for energy companies for storing your data, new artificial intelligence and optimize the whole supply, the energy supply chain in this world out here. >> Johan Krebbers, Liz Dennett thank you so much for coming on theCUBE virtual. >> Thank you. >> Thank you. >> I'm Rebecca Knight stay tuned for more of our coverage of the Accenture Executive Summit. (tranquil music).
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AWS Executive Summit 2020
>>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome to cube three 60 fives coverage of the Accenture executive summit. Part of AWS reinvent. I'm your host Rebecca Knight. Today we are joined by a cube alum, Karthik, Lorraine. He is Accenture senior managing director and lead Accenture cloud. First, welcome back to the show Karthik. >>Thank you. Thanks for having me here. >>Always a pleasure. So I want to talk to you. You are an industry veteran, you've been in Silicon Valley for decades. Um, I want to hear from your perspective what the impact of the COVID-19 pandemic has been, what are you hearing from clients? What are they struggling with? What are their challenges that they're facing day to day? >>I think, um, COVID-19 is being a eye-opener from, you know, various facets, you know, um, first and foremost, it's a, it's a hell, um, situation that everybody's facing, which is not just, uh, highest economic bearings to it. It has enterprise, um, an organization with bedding to it. And most importantly, it's very personal to people, um, because they themselves and their friends, family near and dear ones are going through this challenge, uh, from various different dimension. But putting that aside, when you come to it from an organization enterprise standpoint, it has changed everything well, the behavior of organizations coming together, working in their campuses, working with each other as friends, family, and, uh, um, near and dear colleagues, all of them are operating differently. So that's what big change to get things done in a completely different way, from how they used to get things done. >>Number two, a lot of things that were planned for normal scenarios, like their global supply chain, how they interact with their client customers, how they go innovate with their partners on how that employees contribute to the success of an organization at all changed. And there are no data models that give them a hint of something like this for them to be prepared for this. So we are seeing organizations, um, that have adapted to this reasonably okay, and are, you know, launching to innovate faster in this. And there are organizations that have started with struggling, but are continuing to struggle. And the gap between the leaders and legs are widening. So this is creating opportunities in a different way for the leaders, um, with a lot of pivot their business, but it's also creating significant challenge for the lag guides, uh, as we defined in our future systems research that we did a year ago, uh, and those organizations are struggling further. So the gap is actually widening. >>So you just talked about the widening gap. I've talked about the tremendous uncertainty that so many companies, even the ones who have adapted reasonably well, uh, in this, in this time, talk a little bit about Accenture cloud first and why, why now? >>I think it's a great question. Um, we believe that for many of our clients COVID-19 has turned, uh, cloud from an experimentation aspiration to an origin mandate. What I mean by that is everybody has been doing something on the other end cloud. There's no company that says we don't believe in cloud are, we don't want to do cloud. It was how much they did in cloud. And they were experimenting. They were doing the new things in cloud, but they were operating a lot of their core business outside the cloud or not in the cloud. Those organizations have struggled to operate in this new normal, in a remote fashion, as well as, uh, their ability to pivot to all the changes the pandemic has brought to them. But on the other hand, the organizations that had a solid foundation in cloud were able to collect faster and not actually gone into the stage of innovating faster and driving a new behavior in the market, new behavior within their organization. >>So we are seeing that spend to make is actually fast-forwarded something that we always believed was going to happen. This, uh, uh, moving to cloud over the next decade is fast forward it to happen in the next three to five years. And it's created this moment where it's a once in an era, really replatforming of businesses in the cloud that we are going to see. And we see this moment as a cloud first moment where organizations will use cloud as the, the, the canvas and the foundation with which they're going to reimagine their business after they were born in the cloud. Uh, and this requires a whole new strategy. Uh, and as Accenture, we are getting a lot in cloud, but we thought that this is the moment where we bring all of that, gave him a piece together because we need a strategy for addressing, moving to cloud are embracing cloud in a holistic fashion. And that's what Accenture cloud first brings together a holistic strategy, a team that's 70,000 plus people that's coming together with rich cloud skills, but investing to tie in all the various capabilities of cloud to Delaware, that holistic strategy to our clients. So I want you to >>Delve into a little bit more about what this strategy actually entails. I mean, it's clearly about embracing change and being willing to experiment and having capabilities to innovate. Can you tell us a little bit more about what this strategy entails? >>Yeah. The reason why we say that as a need for strategy is like I said, cloud is not new. There's almost every customer client is doing something with the cloud, but all of them have taken different approaches to cloud and different boundaries to cloud. Some organizations say, I just need to consolidate my multiple data centers to a small data center footprint and move the nest to cloud. Certain other organizations say that well, I'm going to move certain workloads to cloud. Certain other organizations said, well, I'm going to build this Greenfield application or workload in cloud. Certain other said, um, I'm going to use the power of AI ML in the cloud to analyze my data and drive insights. But a cloud first strategy is all of this tied with the corporate strategy of the organization with an industry specific cloud journey to say, if in this current industry, if I were to be reborn in the cloud, would I do it in the exact same passion that I did in the past, which means that the products and services that they offer need to be the matching, how they interact with that customers and partners need to be revisited, how they bird and operate their IP systems need to be the, imagine how they unearthed the data from all of the systems under which they attract need to be liberated so that you could drive insights of cloud. >>First strategy hands is a corporate wide strategy, and it's a C-suite responsibility. It doesn't take the ownership away from the CIO or CIO, but the CIO is, and CDI was felt that it was just their problem and they were to solve it. And everyone as being a customer, now, the center of gravity is elevated to it becoming a C-suite agenda on everybody's agenda, where probably the CDI is the instrument to execute that that's a holistic cloud-first strategy >>And it, and it's a strategy, but the way you're describing it, it sounds like it's also a mindset and an approach, as you were saying, this idea of being reborn in the cloud. So now how do I think about things? How do I communicate? How do I collaborate? How do I get done? What I need to get done. Talk a little bit about how this has changed, the way you support your clients and how Accenture cloud first is changing your approach to cloud services. >>Wonderful. Um, you know, I did not color one very important aspect in my previous question, but that's exactly what you just asked me now, which is to do all of this. I talked about all of the variables, uh, an organization or an enterprise is going to go through, but the good part is they have one constant. And what is that? That is their employees, uh, because you do, the employees are able to embrace this change. If they are able to, uh, change them, says, pivot them says retool and train themselves to be able to operate in this new cloud. First one, the ability to reimagine every function of the business would be happening at speed. And cloud first approach is to do all of this at speed, because innovation is deadly proposed there, do the rate of probability on experimentation. You need to experiment a lot for any kind of experimentation. >>There's a probability of success. Organizations need to have an ability and a mechanism for them to be able to innovate faster for which they need to experiment a lot, the more the experiment and the lower cost at which they experiment is going to help them experiment a lot. And they experiment demic speed, fail fast, succeed more. And hence, they're going to be able to operate this at speed. So the cloud-first mindset is all about speed. I'm helping the clients fast track that innovation journey, and this is going to happen. Like I said, across the enterprise and every function across every department, I'm the agent of this change is going to be the employees or weapon, race, this change through new skills and new grueling and new mindset that they need to adapt to. >>So Karthik what you're describing it, it sounds so exciting. And yet for a pandemic wary workforce, that's been working remotely that may be dealing with uncertainty if for their kid's school and for so many other aspects of their life, it sounds hard. So how are you helping your clients, employees get onboard with this? And because the change management is, is often the hardest part. >>Yeah, I think it's, again, a great question. A bottle has only so much capacity. Something got to come off for something else to go in. That's what you're saying is absolutely right. And that is again, the power of cloud. The reason why cloud is such a fundamental breakthrough technology and capability for us to succeed in this era, because it helps in various forms. What we talked so far is the power of innovation that can create, but cloud can also simplify the life of the employees in an enterprise. There are several activities and tasks that people do in managing that complex infrastructure, complex ID landscape. They used to do certain jobs and activities in a very difficult underground about with cloud has simplified. And democratised a lot of these activities. So that things which had to be done in the past, like managing the complexity of the infrastructure, keeping them up all the time, managing the, um, the obsolescence of the capabilities and technologies and infrastructure, all of that could be offloaded to the cloud. >>So that the time that is available for all of these employees can be used to further innovate. Every organization is going to spend almost the same amount of money, but rather than spending activities, by looking at the rear view mirror on keeping the lights on, they're going to spend more money, more time, more energy, and spend their skills on things that are going to add value to their organization. Because you, every innovation that an enterprise can give to their end customer need not come from that enterprise. The word of platform economy is about democratising innovation. And the power of cloud is to get all of these capabilities from outside the four walls of the enterprise, >>It will add value to the organization, but I would imagine also add value to that employee's life because that employee, the employee will be more engaged in his or her job and therefore bring more excitement and energy into her, his or her day-to-day activities too. >>Absolutely. Absolutely. And this is, this is a normal evolution we would have seen everybody would have seen in their lives, that they keep moving up the value chain of what activities that, uh, gets performed buying by those individuals. And this is, um, you know, no more true than how the United States, uh, as an economy has operated where, um, this is the power of a powerhouse of innovation, where the work that's done inside the country keeps moving up to value chain. And, um, us leverage is the global economy for a lot of things that is required to power the United States and that global economic, uh, phenomenon is very proof for an enterprise as well. There are things that an enterprise needs to do them soon. There are things an employee needs to do themselves. Um, but there are things that they could leverage from the external innovation and the power of innovation that is coming from technologies like cloud. >>So at Accenture, you have long, long, deep Stan, sorry, you have deep and long-standing relationships with many cloud service providers, including AWS. How does the Accenture cloud first strategy, how does it affect your relationships with those providers? >>Yeah, we have great relationships with cloud providers like AWS. And in fact, in the cloud world, it was one of the first, um, capability that we started about years ago, uh, when we started developing these capabilities. But five years ago, we hit a very important milestone where the two organizations came together and said that we are forging a pharma partnership with joint investments to build this partnership. And we named that as a Accenture, AWS business group ABG, uh, where we co-invest and brought skills together and develop solutions. And we will continue to do that. And through that investment, we've also made several acquisitions that you would have seen in the recent times, like, uh, an invoice and gecko that we made acquisitions in in Europe. But now we're taking this to the next level. What we are saying is two cloud first and the $3 billion investment that we are bringing in, uh, through cloud-first. >>We are going to make specific investment to create unique joint solution and landing zones foundation, um, cloud packs with which clients can accelerate their innovation or their journey to cloud first. And one great example is what we are doing with Takeda, uh, billable, pharmaceutical giant, um, between we've signed a five-year partnership. And it was out in the media just a month ago or so, where we are, the two organizations are coming together. We have created a partnership as a power of three partnership, where the three organizations are jointly hoarding hats and taking responsibility for the innovation and the leadership position that Takeda wants to get to with this. We are going to simplify their operating model and organization by providing and flexibility. We're going to provide a lot more insights. Tequila has a 230 year old organization. Imagine the amount of trapped data and intelligence that is there. >>How about bringing all of that together with the power of AWS and Accenture and Takeda to drive more customer insights, um, come up with breakthrough R and D uh, accelerate clinical trials and improve the patient experience using AI ML and edge technologies. So all of these things that we will do through this partnership with joined investment from Accenture cloud first, as well as partner like AWS, so that Takeda can realize their gain. And, uh, their senior actually made a statement that five years from now, every ticket an employee will have an AI assistant. That's going to make that beginner employee move up the value chain on how they contribute and add value to the future of tequila with the AI assistant, making them even more equipped and smarter than what they could be otherwise. >>So, one last question to close this out here. What is your future vision for, for Accenture cloud first? What are we going to be talking about at next year's Accenture executive summit? Yeah, the future >>Is going to be, um, evolving, but the part that is exciting to me, and this is, uh, uh, a fundamental belief that we are entering a new era of industrial revolution from industry first, second, and third industry. The third happened probably 20 years ago with the advent of Silicon and computers and all of that stuff that happened here in the Silicon Valley. I think the fourth industrial revolution is going to be in the cross section of, uh, physical, digital and biological boundaries. And there's a great article, um, in one economic forum that people, uh, your audience can Google and read about it. Uh, but the reason why this is very, very important is we are seeing a disturbing phenomenon that over the last 10 years are seeing a Blackwing of the, um, labor productivity and innovation, which has dropped to about 2.1%. When you see that kind of phenomenon over that longer period of time, there has to be breakthrough innovation that needs to happen to come out of this barrier and get to the next, you know, base camp, as I would call it to further this productivity, um, lack that we are seeing, and that is going to happen in the intersection of the physical, digital and biological boundaries. >>And I think cloud is going to be the connective tissue between all of these three, to be able to provide that where it's the edge, especially is good to come closer to the human lives. It's going to come from cloud. Yeah. Pick totally in your mind, you can think about cloud as central, either in a private cloud, in a data center or in a public cloud, you know, everywhere. But when you think about edge, it's going to be far reaching and coming close to where we live and maybe work and very, um, get entertained and so on and so forth. And there's good to be, uh, intervention in a positive way in the field of medicine, in the field of entertainment, in the field of, um, manufacturing in the field of, um, you know, mobility. When I say mobility, human mobility, people, transportation, and so on and so forth with all of this stuff, cloud is going to be the connective tissue and the vision of cloud first is going to be, uh, you know, blowing through this big change that is going to happen. And the evolution that is going to happen where, you know, the human grace of mankind, um, our person kind of being very gender neutral in today's world. Um, go first needs to be that beacon of, uh, creating the next generation vision for enterprises to take advantage of that kind of an exciting future. And that's why it, Accenture, are we saying that there'll be change as our, as our purpose? >>I genuinely believe that cloud first is going to be in the forefront of that change agenda, both for Accenture as well as for the rest of the work. Excellent. Let there be change, indeed. Thank you so much for joining us Karthik. A pleasure I'm Rebecca nights stay tuned for more of Q3 60 fives coverage of the Accenture executive summit >>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS >>Welcome everyone to the Q virtual and our coverage of the Accenture executive summit, which is part of AWS reinvent 2020. I'm your host Rebecca Knight. Today, we are talking about the green cloud and joining me is Kishor Dirk. He is Accenture senior managing director cloud first global services lead. Thank you so much for coming on the show. Kishor nice to meet you. So I want to start by asking you what it is that we mean when we say green cloud, we know the sustainability is a business imperative. So many organizations around the world are committing to responsible innovation, lowering carbon emissions. But what is this? What is it? What does it mean when they talk about cloud from a sustainability perspective? I think it's about responsible innovation being cloud is a cloud first approach that has benefit the clients by helping reduce carbon emissions. Think about it this way. >>You have a large number of data centers. Each of these data centers are increasing by 14% every year. And this double digit growth. What you're seeing is these data centers and the consumption is nearly coolant to the kind of them should have a country like Spain. So the magnitude of the problem that is out there and how do we pursue a green approach. If you look at this, our Accenture analysis, in terms of the migration to public cloud, we've seen that we can reduce that by 59 million tons of CO2 per year with just the 5.9% reduction in total emissions and equates this to 22 million cars off the road. And the magnitude of reduction can go a long way in meeting climate change commitments, particularly for data sensitive. Wow, that's incredible. The numbers that you're putting forward are, are absolutely mind blowing. So how does it work? Is it a simple cloud migration? So, you know, when companies begin their cloud journey and then they confront, uh, with >>Them a lot of questions, the decision to make, uh, this particular, uh, element sustainable in the solution and benefits they drive and they have to make wise choices, and then they will gain unprecedented level of innovation leading to both a greener planet, as well as, uh, a greener balance sheet, I would say, uh, so effectively it's all about ambition, data ambition, greater the reduction in carbon emissions. So from a cloud migration perspective, we look at it as a, as a simple solution with approaches and sustainability benefits, uh, that vary based on things it's about selecting the right cloud provider, a very carbon thoughtful provider and the first step towards a sustainable cloud journey. And here we're looking at cloud operators know, obviously they have different corporate commitments towards sustainability, and that determines how they plan, how they build, uh, their, uh, uh, the data centers, how they are consumed and assumptions that operate there and how they, or they retire their data centers. >>Then, uh, the next element that you want to do is how do you build it ambition, you know, for some of the companies, uh, and average on-prem, uh, drives about 65% energy reduction and the carbon emission reduction number was 84%, which is kind of good, I would say. But then if you could go up to 98% by configuring applications to the cloud, that is significant benefit for, uh, for the board. And obviously it's a, a greener cloud that we're talking about. And then the question is, how far can you go? And, uh, you know, the, obviously the companies have to unlock greater financial societal environmental benefits, and Accenture has this cloud based circular operations and sustainable products and services that we bring into play. So it's a, it's a very thoughtful, broader approach that w bringing in, in terms of, uh, just a simple concept of cloud migration. >>So we know that in the COVID era, shifting to the cloud has really become a business imperative. How is Accenture working with its clients at a time when all of this movement has been accelerated? How do you partner and what is your approach in terms of helping them with their migrations? >>Yeah, I mean, let, let me talk a little bit about the pandemic and the crisis that is that today. And if you really look at that in terms of how we partnered with a lot of our clients in terms of the cloud first approach, I'll give you a couple of examples. We worked with rolls, Royce, MacLaren, DHL, and others, as part of the ventilator, a UK challenge consortium, again, to, uh, coordinate production of medical ventilator surgically needed for the UK health service. Many of these farms I've taken similar initiatives in, in terms of, uh, you know, from a few manufacturers hand sanitizers, and to answer it as us and again, leading passionate labels, making PPE, and again, at the UN general assembly, we launched the end-to-end integration guide that helps company is essentially to have a sustainable development goals. And that's how we are parking at a very large scale. >>Uh, and, and if you really look at how we work with our clients and what is Accenture's role there, uh, you know, from, in terms of our clients, you know, there are multiple steps that we look at. One is about planning, building, deploying, and managing an optimal green cloud solution. And Accenture has this concept of, uh, helping clients with a platform to kind of achieve that goal. And here we are having, we are having a platform or a mine app, which has a module called BGR advisor. And this is a capability that helps you provide optimal green cloud, uh, you know, a business case, and obviously a blueprint for each of our clients and right from the start in terms of how do we complete cloud migration recommendation to an improved solution, accurate accuracy to obviously bringing in the end to end perspective, uh, you know, with this green card advisor capability, we're helping our clients capture what we call as a carbon footprint for existing data centers and provide, uh, I would say the current cloud CO2 emission score that, you know, obviously helps them, uh, with carbon credits that can further that green agenda. >>So essentially this is about recommending a green index score, reducing carbon footprint for migration migrating for green cloud. And if we look at how Accenture itself is practicing what we preach, 95% of our applications are in the cloud. And this migration has helped us, uh, to lead to about $14.5 million in benefit. And in the third year and another 3 million analytics costs that are saved through right-sizing a service consumption. So it's a very broad umbrella and a footprint in terms of how we engage societaly with the UN or our clients. And what is it that we exactly bring to our clients in solving a specific problem? >>Accenture isn't is walking the walk, as you say, >>Instead of it, we practice what we preach, and that is something that we take it to heart. We want to have a responsible business and we want to practice it. And we want to advise our clients around that >>You are your own use case. And so they can, they know they can take your advice. So talk a little bit about, um, the global, the cooperation that's needed. We know that conquering this pandemic is going to take a coordinated global effort and talk a little bit about the great reset initiative. First of all, what is that? Why don't we, why don't we start there and then we can delve into it a little bit more. >>Okay. So before we get to how we are cooperating, the great reset, uh, initiative is about improving the state of the world. And it's about a group of global stakeholders cooperating to simultaneously manage the direct consequences of their COVID-19 crisis. Uh, and in spirit of this cooperation that we're seeing during COVID-19, uh, which will obviously either to post pandemic, to tackle the world's pressing issues. As I say, uh, we are increasing companies to realize a combined potential of technology and sustainable impact to use enterprise solutions, to address with urgency and scale, and, um, obviously, uh, multiple challenges that are facing our world. One of the ways that are increasing, uh, companies to reach their readiness cloud with Accenture's cloud strategy is to build a solid foundation that is resilient and will be able to faster to the current, as well as future times. Now, when you think of cloud as the foundation, uh, that drives the digital transformation, it's about scale speed, streamlining your operations, and obviously reducing costs. >>And as these businesses seize the construct of cloud first, they must remain obviously responsible and trusted. Now think about this, right, as part of our analysis, uh, that profitability can co-exist with responsible and sustainable practices. Let's say that all the data centers, uh, migrated from on-prem to cloud based, we estimate that would reduce carbon emissions globally by 60 million tons per year. Uh, and think about it this way, right? Easier metric would be taking out 22 million cars off the road. Um, the other examples that you've seen, right, in terms of the NHS work that they're doing, uh, in, in UK to build, uh, uh, you know, uh, Microsoft teams in based integration. And, uh, the platform rolled out for 1.2 million users, uh, and got 16,000 users that we were able to secure, uh, instant messages, obviously complete audio video calls and host virtual meetings across India. So, uh, this, this work that we did with NHS is, is something that we have, we are collaborating with a lot of tools and powering businesses. >>Well, you're vividly describing the business case for sustainability. What do you see as the future of cloud when thinking about it from this lens of sustainability, and also going back to what you were talking about in terms of how you are helping your, your fostering cooperation within these organizations. >>Yeah, that's a very good question. So if you look at today, right, businesses are obviously environmentally aware and they are expanding efforts to decrease power consumption, carbon emissions, and they want to run a sustainable operational efficiency across all elements of their business. And this is an increasing trend, and there is that option of energy efficient infrastructure in the global market. And this trend is the cloud first thinking. And with the right cloud migration that we've been discussing is about unlocking new opportunity, like clean energy foundations enable enabled by cloud based geographic analysis, material, waste reductions, and better data insights. And this is something that, uh, uh, will drive, uh, with obviously faster analytics platform that is out there. Now, the sustainability is actually the future of business, which is companies that are historically different, the financial security or agility benefits to cloud. Now sustainability becomes an imperative for them. And I would own experience Accenture's experience with cloud migrations. We have seen 30 to 40% total cost of ownership savings, and it's driving a greater workload, flexibility, better service, your obligation, and obviously more energy efficient, uh, public clouds that cost, uh, we'll see that, that drive a lot of these enterprise own data centers. So in our view, what we are seeing is that this, this, uh, sustainable cloud position helps, uh, helps companies to, uh, drive a lot of the goals in addition to their financial and other goods. >>So what should organizations who are, who are watching this interview and saying, Hey, I need to know more, what, what do you recommend to them? And what, where should they go to get more information on Greenplum? >>Yeah. If you wanna, if you are a business leader and you're thinking about which cloud provider is good, or how, how should applications be modernized to meet our day-to-day needs, which cloud driven innovations should be priorities. Uh, you know, that's why Accenture, uh, formed up the cloud first organization and essentially to provide the full stack of cloud services to help our clients become a cloud first business. Um, you know, it's all about excavation, uh, the digital transformation innovating faster, creating differentiated, uh, and sustainable value for our clients. And we are powering it up at 70,000 cloud professionals, $3 billion investment, and, uh, bringing together and services for our clients in terms of cloud solutions. And obviously the ecosystem partnership that we have that we are seeing today, uh, and, and the assets that help our clients realize their goals. Um, and again, to do reach out to us, uh, we can help them determine obviously, an optimal, sustainable cloud for solution that meets the business needs and being unprecedented levels of innovation. Our experience, uh, will be our advantage. And, uh, now more than ever Rebecca, >>Just closing us out here. Do you have any advice for these companies who are navigating a great deal of uncertainty? We, what, what do you think the next 12 to 24 months? What do you think that should be on the minds of CEOs as they go through? >>So, as CEO's are thinking about rapidly leveraging cloud, migrating to cloud, uh, one of the elements that we want them to be thoughtful about is can they do that, uh, with unprecedent level of innovation, but also build a greener planet and a greener balance sheet, if we can achieve this balance and kind of, uh, have a, have a world which is greener, I think the world will win. And we all along with Accenture clients will win. That's what I would say, uh, >>Optimistic outlook, and I will take it. Thank you so much. Kishor for coming on the show >>That was >>Accenture's Kishor Dirk, I'm Rebecca Knight stay tuned for more of the cube virtuals coverage of the Accenture executive summit >>Around the globe. >>It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cube virtual and our coverage of the Accenture executive summit. Part of AWS reinvent 2020. I'm your host Rebecca Knight. Today, we are talking about the power of three. And what happens when you bring together the scientific know-how of a global bias biopharmaceutical powerhouse in Takeda, a leading cloud services provider in AWS, and Accenture's ability to innovate, execute, and deliver innovation. Joining me to talk about these things. We have Aaron, sorry, Arjun, baby. He is the senior managing director and chairman of Accenture's diamond leadership council. Welcome Arjun, Karl hick. He is the chief digital and information officer at Takeda. What is your bigger, thank you, Rebecca and Brian bowhead, global director, and head of the Accenture AWS business group at Amazon web services. Thanks so much for coming up. So, as I said, we're talking today about this relationship between, uh, your three organizations. Carl, I want to talk with you. I know you're at the beginning of your cloud journey. What was the compelling reason? What w why, why move to the cloud and why now? >>Yeah, no, thank you for the question. So, you know, as a biopharmaceutical leader, we're committed to bringing better health and a brighter future to our patients. We're doing that by translating science into some really innovative and life transporting therapies, but throughout, you know, we believe that there's a responsible use of technology, of data and of innovation. And those three ingredients are really key to helping us deliver on that promise. And so, you know, while I think, uh, I'll call it, this cloud journey is already always been a part of our strategy. Um, and we've made some pretty steady progress over the last years with a number of I'll call it diverse approaches to the digital and AI. We just weren't seeing the impact at scale that we wanted to see. Um, and I think that, you know, there's a, there's a need ultimately to, you know, accelerate and, uh, broaden that shift. >>And, you know, we were commenting on this earlier, but there's, you know, it's been highlighted by a number of factors. One of those has been certainly a number of the large acquisitions we've made Shire, uh, being the most pressing example, uh, but also the global pandemic, both of those highlight the need for us to move faster, um, at the speed of cloud, ultimately. Uh, and so we started thinking outside of the box because it was taking us too long and we decided to leverage the strategic partner model. Uh, and it's giving us a chance to think about our challenges very differently. We call this the power of three, uh, and ultimately our focus is singularly on our patients. I mean, they're waiting for us. We need to get there faster. It can take years. And so I think that there is a focus on innovation, um, at a rapid speed, so we can move ultimately from treating conditions to keeping people healthy. >>So, as you are embarking on this journey, what are some of the insights you want to share about, about what you're seeing so far? >>Yeah, no, it's a great question. So, I mean, look, maybe right before I highlight some of the key insights, uh, I would say that, you know, with cloud now as the, as the launchpad for innovation, you know, our vision all along has been that in less than 10 years, we want every single to kid, uh, associate we're employed to be empowered by an AI assistant. And I think that, you know, that's going to help us make faster, better decisions. It'll help us, uh, fundamentally deliver transformative therapies and better experiences to, to that ecosystem, to our patients, to physicians, to payers, et cetera, much faster than we previously thought possible. Um, and I think that technologies like cloud and edge computing together with a very powerful I'll call it data fabric is going to help us to create this, this real-time, uh, I'll call it the digital ecosystem. >>The data has to flow ultimately seamlessly between our patients and providers or partners or researchers, et cetera. Uh, and so we've been thinking about this, uh, I'll call it, we call it sort of this pyramid, um, that helps us describe our vision. Uh, and a lot of it has to do with ultimately modernizing the foundation, modernizing and rearchitecting, the platforms that drive the company, uh, heightening our focus on data, which means that there's an accelerated shift towards, uh, enterprise data platforms and digital products. And then ultimately, uh, uh, P you know, really an engine for innovation sitting at the very top. Um, and so I think with that, you know, there's a few different, I'll call it insights that, you know, are quickly kind of come zooming into focus. I would say one is this need to collaborate very differently. Um, you know, not only internally, but you know, how do we define ultimately, and build a connected digital ecosystem with the right partners and technologies externally? >>I think the second component that maybe people don't think as much about, but, you know, I find critically important is for us to find ways of really transforming our culture. We have to unlock talent and shift the culture certainly as a large biopharmaceutical very differently. And then lastly, you've touched on it already, which is, you know, innovation at the speed of cloud. How do we re-imagine that, you know, how do ideas go from getting tested and months to kind of getting tested in days? You know, how do we collaborate very differently? Uh, and so I think those are three, uh, perhaps of the larger I'll call it, uh, insights that, you know, the three of us are spending a lot of time thinking about right now. >>So Arjun, I want to bring you into this conversation a little bit, let let's delve into those a bit. Talk first about the collaboration, uh, that Carl was referencing there. How, how have you seen that? It is enabling, uh, colleagues and teams to communicate differently and interact in new and different ways? Uh, both internally and externally, as Carl said, >>No, th thank you for that. And, um, I've got to give call a lot of credit, because as we started to think about this journey, it was clear, it was a bold ambition. It was, uh, something that, you know, we had all to do differently. And so the, the concept of the power of three that Carl has constructed has become a label for us as a way to think about what are we going to do to collectively drive this journey forward. And to me, the unique ways of collaboration means three things. The first one is that, um, what is expected is that the three parties are going to come together and it's more than just the sum of our resources. And by that, I mean that we have to bring all of ourselves, all of our collective capabilities, as an example, Amazon has amazing supply chain capabilities. >>They're one of the best at supply chain. So in addition to resources, when we have supply chain innovations, uh, that's something that they're bringing in addition to just, uh, talent and assets, similarly for Accenture, right? We do a lot, uh, in the talent space. So how do we bring our thinking as to how we apply best practices for talent to this partnership? So, um, as we think about this, so that's, that's the first one, the second one is about shared success very early on in this partnership, we started to build some foundations and actually develop seven principles that all of us would look at as the basis for this success shared success model. And we continue to hold that sort of in the forefront, as we think about this collaboration. And maybe the third thing I would say is this one team mindset. So whether it's the three of our CEOs that get together every couple of months to think about, uh, this partnership, or it is the governance model that Carl has put together, which has all three parties in the governance and every level of leadership. We always think about this as a collective group, so that we can keep that front and center. And what I think ultimately has enabled us to do is it allowed us to move at speed, be more flexible. And ultimately all we're looking at the target the same way, the North side, the same way. >>Brian, what about you? What have you observed? And are you thinking about in terms of how this is helping teams collaborate differently, >>Lillian and Arjun made some, some great points there. And I think if you really think about what he's talking about, it's that, that diversity of talent, diversity of scale and viewpoint and even culture, right? And so we see that in the power of three. And then I think if we drill down into what we see at Takeda, and frankly, Takeda was, was really, I think, pretty visionary and on their way here, right? And taking this kind of cross functional approach and applying it to how they operate day to day. So moving from a more functional view of the world to more of a product oriented view of the world, right? So when you think about we're going to be organized around a product or a service or a capability that we're going to provide to our customers or our patients or donors in this case, it implies a different structure, although altogether, and a different way of thinking, right? >>Because now you've got technical people and business experts and marketing experts, all working together in this is sort of cross collaboration. And what's great about that is it's really the only way to succeed with cloud, right? Because the old ways of thinking where you've got application people and infrastructure, people in business, people is suboptimal, right? Because we can all access this tool as these capabilities and the best way to do that. Isn't across kind of a cross-collaborative way. And so this is product oriented mindset. It's a keto was already on. I think it's allowed us to move faster in those areas. >>Carl, I want to go back to this idea of unlocking talent and culture. And this is something that both Brian and Arjun have talked about too. People are an essential part of their, at the heart of your organization. How will their experience of work change and how are you helping re-imagine and reinforce a strong organizational culture, particularly at this time when so many people are working remotely. >>Yeah. It's a great question. And it's something that, you know, I think we all have to think a lot about, I mean, I think, um, you know, driving this, this call it, this, this digital and data kind of capability building, uh, takes a lot of, a lot of thinking. So, I mean, there's a few different elements in terms of how we're tackling this one is we're recognizing, and it's not just for the technology organization or for those actors that, that we're innovating with, but it's really across all of the Cato where we're working through ways of raising what I'll call the overall digital leaders literacy of the organization, you know, what are the, you know, what are the skills that are needed almost at a baseline level, even for a global bio-pharmaceutical company and how do we deploy, I'll call it those learning resources very broadly. >>And then secondly, I think that, you know, we're, we're very clear that there's a number of areas where there are very specialized skills that are needed. Uh, my organization is one of those. And so, you know, we're fostering ways in which, you know, we're very kind of quickly kind of creating, uh, avenues excitement for, for associates in that space. So one example specifically, as we use, you know, during these very much sort of remote, uh, sort of days, we, we use what we call global it meet days, and we set a day aside every single month and this last Friday, um, you know, we, we create during that time, it's time for personal development. Um, and we provide active seminars and training on things like, you know, robotic process automation, data analytics cloud, uh, in this last month we've been doing this for months and months now, but in his last month, more than 50% of my organization participated, and there's this huge positive shift, both in terms of access and excitement about really harnessing those new skills and being able to apply them. >>Uh, and so I think that that's, you know, one, one element that, uh, can be considered. And then thirdly, um, of course, every organization to work on, how do you prioritize talent, acquisition and management and competencies that you can't rescale? I mean, there are just some new capabilities that we don't have. And so there's a large focus that I have with our executive team and our CEO and thinking through those critical roles that we need to activate in order to kind of, to, to build on this, uh, this business led cloud transformation. And lastly, probably the hardest one, but the one that I'm most jazzed about is really this focus on changing the mindsets and behaviors. Um, and I think there, you know, this is where the power of three is, is really, uh, kind of coming together nicely. I mean, we're working on things like, you know, how do we create this patient obsessed curiosity, um, and really kind of unlock innovation with a real, kind of a growth mindset. >>Uh, and the level of curiosity that's needed, not to just continue to do the same things, but to really challenge the status quo. So that's one big area of focus we're having the agility to act just faster. I mean, to worry less, I guess I would say about kind of the standard chain of command, but how do you make more speedy, more courageous decisions? And this is places where we can emulate the way that a partner like AWS works, or how do we collaborate across the number of boundaries, you know, and I think, uh, Arjun spoke eloquently to a number of partnerships that we can build. So we can break down some of these barriers and use these networks, um, whether it's within our own internal ecosystem or externally to help, to create value faster. So a lot of energy around ways of working and we'll have to check back in, but I mean, we're early in on this mindset and behavioral shift, um, but a lot of good early momentum. >>Carl you've given me a good segue to talk to Brian about innovation, because you said a lot of the things that I was the customer obsession and this idea of innovating much more quickly. Obviously now the world has its eyes on drug development, and we've all learned a lot about it, uh, in the past few months and accelerating drug development is all, uh, is of great interest to all of us. Brian, how does a transformation like this help a company's, uh, ability to become more agile and more innovative and add a quicker speed to, >>Yeah, no, absolutely. And I think some of the things that Carl talked about just now are critical to that, right? I think where sometimes folks fall short is they think, you know, we're going to roll out the technology and the technology is going to be the silver bullet where in fact it is the culture, it is, is the talent. And it's the focus on that. That's going to be, you know, the determinant of success. And I will say, you know, in this power of three arrangement and Carl talked a little bit about the pyramid, um, talent and culture and that change, and that kind of thinking about that has been a first-class citizen since the very beginning, right. That absolutely is critical for, for being there. Um, and, and so that's been, that's been key. And so we think about innovation at Amazon and AWS, and Carl mentioned some of the things that, you know, partner like AWS can bring to the table is we talk a lot about builders, right? >>So kind of obsessive about builders. Um, and, and we meet what we mean by that is we at Amazon, we hire for builders, we cultivate builders and we like to talk to our customers about it as well. And it also implies a different mindset, right? When you're a builder, you have that, that curiosity, you have that ownership, you have that stake and whatever I'm creating, I'm going to be a co-owner of this product or this service, right. Getting back to that kind of product oriented mindset. And it's not just the technical people or the it people who are builders. It is also the business people as, as Carl talked about. Right. So when we start thinking about, um, innovation again, where we see folks kind of get into a little bit of a innovation pilot paralysis, is that you can focus on the technology, but if you're not focusing on the talent and the culture and the processes and the mechanisms, you're going to be putting out technology, but you're not going to have an organization that's ready to take it and scale it and accelerate it. >>Right. And so that's, that's been absolutely critical. So just a couple of things we've been doing with, with Takeda and Decatur has really been leading the way is, think about a mechanism and a process. And it's really been working backward from the customer, right? In this case, again, the patient and the donor. And that was an easy one because the key value of Decatur is to be a patient focused bio-pharmaceutical right. So that was embedded in their DNA. So that working back from that, that patient, that donor was a key part of that process. And that's really deep in our DNA as well. And Accenture's, and so we were able to bring that together. The other one is, is, is getting used to experimenting and even perhaps failing, right. And being able to iterate and fail fast and experiment and understanding that, you know, some decisions, what we call it at Amazon are two two-way doors, meaning you can go through that door, not like what you see and turn around and go back. And cloud really helps there because the costs of experimenting and the cost of failure is so much lower than it's ever been. You can do it much faster and the implications are so much less. So just a couple of things that we've been really driving, uh, with the cadence around innovation, that's been really critical. Carl, where are you already seeing signs of success? >>Yeah, no, it's a great question. And so we chose, you know, uh, with our focus on innovation to try to unleash maybe the power of data digital in, uh, in focusing on what I call sort of a nave. And so we chose our, our, our plasma derived therapy business, um, and you know, the plasma-derived therapy business unit, it develops critical life-saving therapies for patients with rare and complex diseases. Um, but what we're doing is by bringing kind of our energy together, we're focusing on creating, I'll call it state of the art digitally connected donation centers. And we're really modernizing, you know, the, the, the donor experience right now, we're trying to, uh, improve also I'll call it the overall plasma collection process. And so we've, uh, selected a number of alcohol at a very high speed pilots that we're working through right now, specifically in this, in this area. And we're seeing >>Really great results already. Um, and so that's, that's one specific area of focus are Jen, I want you to close this out here. Any ideas, any best practices advice you would have for other pharmaceutical companies that are, that are at the early stage of their cloud journey? Sorry. Was that for me? Yes. Sorry. Origin. Yeah, no, I was breaking up a bit. No, I think they, um, the key is what's sort of been great for me to see is that when people think about cloud, you know, you always think about infrastructure technology. The reality is that the cloud is really the true enabler for innovation and innovating at scale. And, and if you think about that, right, and all the components that you need, ultimately, that's where the value is for the company, right? Because yes, you're going to get some cost synergies and that's great, but the true value is in how do we transform the organization in the case of the Qaeda and our life sciences clients, right. >>We're trying to take a 14 year process of research and development that takes billions of dollars and compress that right. Tremendous amounts of innovation opportunity. You think about the commercial aspect, lots of innovation can come there. The plasma derived therapy is a great example of how we're going to really innovate to change the trajectory of that business. So I think innovation is at the heart of what most organizations need to do. And the formula, the cocktail that the Qaeda has constructed with this footie program really has all the ingredients, um, that are required for that success. Great. Well, thank you so much. Arjun, Brian and Carl was really an enlightening conversation. Thank you. It's been a lot of, thank you. Yeah, it's been fun. Thanks Rebecca. And thank you for tuning into the cube. Virtual has coverage of the Accenture executive summit >>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cubes coverage of Accenture executive summit here at AWS reinvent. I'm your host Rebecca Knight for this segment? We have two guests. First. We have Helen Davis. She is the senior director of cloud platform services, assistant director for it and digital for the West Midlands police. Thanks so much for coming on the show, Helen, and we also have Matthew pound. He is Accenture health and public service associate director and West Midlands police account lead. Thanks so much for coming on the show. Matthew, thank you for having us. So we are going to be talking about delivering data-driven insights to the West Midlands police force. Helen, I want to start with >>You. Can you tell us a little bit about the West Midlands police force? How big is the force and also what were some of the challenges that you were grappling with prior to this initiative? >>Yeah, certainly. So Westerners police is the second largest police force in the UK, outside of the metropolitan police in London. Um, we have an excessive, um, 11,000 people work at Westman ins police serving communities, um, through, across the Midlands region. So geographically, we're quite a big area as well, as well as, um, being population, um, density, having that as a, at a high level. Um, so the reason we sort of embarked on the data-driven insights platform and it, which was a huge change for us was for a number of reasons. Um, namely we had a lot of disparate data, um, which was spread across a range of legacy systems that were many, many years old, um, with some duplication of what was being captured and no single view for offices or, um, support staff. Um, some of the access was limited. You have to be in a, in an actual police building on a desktop computer to access it. Um, other information could only reach the offices on the frontline through a telephone call back to one of our enabling services where they would do a manual checkup, um, look at the information, then call the offices back, um, and tell them what they needed to know. So it was a very long laborious, um, process and not very efficient. Um, and we certainly weren't exploiting the data that we had in a very productive way. >>So it sounds like as you're describing and an old clunky system that needed a technological, uh, reimagination, so what was the main motivation for, for doing, for making this shift? >>It was really, um, about making us more efficient and more effective in how we do how we do business. So, um, you know, certainly as a, as an it leader and sort of my operational colleagues, we recognize the benefits, um, that data and analytics could bring in, uh, in a policing environment, not something that was, um, really done in the UK at the time. You know, we have a lot of data, so we're very data rich and the information that we have, but we needed to turn it into information that was actionable. So that's where we started looking for, um, technology partners and suppliers to help us and sort of help us really with what's the art of the possible, you know, this hasn't been done before. So what could we do in this space that's appropriate for policing? >>I love that idea. What is the art of the possible, can you tell us a little bit about why you chose AWS? >>I think really, you know, as with all things and when we're procuring a partner in the public sector that, you know, there are many rules and regulations, uh, quite rightly as you would expect that to be because we're spending public money. So we have to be very, very careful and, um, it's, it's a long process and we have to be open to public scrutiny. So, um, we sort of look to everything, everything that was available as part of that process, but we recognize the benefits that Clyde would provide in this space because, you know, without moving to a cloud environment, we would literally be replacing something that was legacy with something that was a bit more modern. Um, that's not what we wanted to do. Our ambition was far greater than that. So I think, um, in terms of AWS, really, it was around the scalability, interoperability, you know, disaster things like the disaster recovery service, the fact that we can scale up and down quickly, we call it dialing up and dialing back. Um, you know, it's it's page go. So it just sort of ticked all the boxes for us. And then we went through the full procurement process, fortunately, um, it came out on top for us. So we were, we were able to move forward, but it just sort of had everything that we were looking for in that space. >>Matthew, I want to bring you into the conversation a little bit here. How are you working with a wet with the West Midlands police, sorry. And helping them implement this cloud-first journey? >>Yeah, so I guess, um, by January the West Midlands police started, um, favorite five years ago now. So, um, we set up a partnership with the force. I wanted to operate in a way that it was very different to a traditional supplier relationship. Um, secretary that the data difference insights program is, is one of many that we've been working with last nights on, um, over the last five years. Um, as having said already, um, cloud gave a number of, uh, advantages certainly from a big data perspective and the things that that enabled us today, um, I'm from an Accenture perspective that allowed us to bring in a number of the different themes that we have say, cloud teams, security teams, um, and drafted from an insurance perspective, as well as more traditional services that people would associate with the country. >>I mean, so much of this is about embracing comprehensive change to experiment and innovate and try different things. Matthew, how, how do you help, uh, an entity like West Midlands police think differently when they are, there are these ways of doing things that people are used to, how do you help them think about what is the art of the possible, as Helen said, >>There's a few things to that enable those being critical is trying to co-create solutions together. Yeah. There's no point just turning up with, um, what we think is the right answer, try and say, um, collectively work three, um, the issues that the fullest is seeing and the outcomes they're looking to achieve rather than simply focusing on a long list of requirements, I think was critical and then being really open to working together to create the right solution. Um, rather than just, you know, trying to pick something off the shelf that maybe doesn't fit the forces requirements in the way that it should too, >>Right. It's not always a one size fits all. >>Absolutely not. You know, what we believe is critical is making sure that we're creating something that met the forces needs, um, in terms of the outcomes they're looking to achieve the financial envelopes that were available, um, and how we can deliver those in a, uh, iterative agile way, um, rather than spending years and years, um, working towards an outcome, um, that is gonna update before you even get that. >>So Helen, how, how are things different? What kinds of business functions and processes have been re-imagined in, in light of this change and this shift >>It's, it's actually unrecognizable now, um, in certain areas of the business as it was before. So to give you a little bit of, of context, when we, um, started working with essentially in AWS on the data driven insights program, it was very much around providing, um, what was called locally, a wizzy tool for our intelligence analysts to interrogate data, look at data, you know, decide whether they could do anything predictive with it. And it was very much sort of a back office function to sort of tidy things up for us and make us a bit better in that, in that area or a lot better in that area. And it was rolled out to a number of offices, a small number on the front line. Um, I'm really, it was, um, in line with a mobility strategy that we, hardware officers were getting new smartphones for the first time, um, to do sort of a lot of things on, on, um, policing apps and things like that to again, to avoid them, having to keep driving back to police stations, et cetera. >>And the pilot was so successful. Every officer now has access to this data, um, on their mobile devices. So it literally went from a handful of people in an office somewhere using it to do sort of clever bang things to, um, every officer in the force, being able to access that level of data at their fingertips. Literally. So what they were touched with done before is if they needed to check and address or check details of an individual, um, just as one example, they would either have to, in many cases, go back to a police station to look it up themselves on a desktop computer. Well, they would have to make a call back to a centralized function and speak to an operator, relay the questions, either, wait for the answer or wait for a call back with the answer when those people are doing the data interrogation manually. >>So the biggest change for us is the self-service nature of the data we now have available. So officers can do it themselves on their phone, wherever they might be. So the efficiency savings from that point of view are immense. And I think just parallel to that is the quality of our, because we had a lot of data, but just because you've got a lot of data and a lot of information doesn't mean it's big data and it's valuable necessarily. Um, so again, it was having the single source of truth as we, as we call it. So you know that when you are completing those safe searches and getting the responses back, that it is the most accurate information we hold. And also you're getting it back within minutes, as opposed to, you know, half an hour, an hour or a drive back to a station. So it's making officers more efficient and it's also making them safer. The more efficient they are, the more time they have to spend out with the public doing what they, you know, we all should be doing >>That kind of return on investment because what you were just describing with all the steps that we needed to be taken in prior to this, to verify an address say, and those are precious seconds when someone's life is on the line in, in sort of in the course of everyday police work. >>Absolutely. Yeah, absolutely. It's difficult to put a price on it. It's difficult to quantify. Um, but all the, you know, the minutes here and there certainly add up to a significant amount of efficiency savings, and we've certainly been able to demonstrate the officers are spending less time up police stations as a result or more time out on the front line. Also they're safer because they can get information about what may or may not be and address what may or may not have occurred in an area before very, very quickly without having to wait. >>I do, I want to hear your observations of working so closely with this West Midlands police. Have you noticed anything about changes in its culture and its operating model in how police officers interact with one another? Have you seen any changes since this technology change? >>What's unique about the Western displaces, the buy-in from the top down, the chief and his exact team and Helen as the leader from an IOT perspective, um, the entire force is bought in. So what is a significant change program? Uh, I'm not trickles three. Um, everyone in the organization, um, change is difficult. Um, and there's a lot of time effort that's been put in to bake the technical delivery and the business change and adoption aspects around each of the projects. Um, but you can see the step change that is making in each aspect to the organization, uh, and where that's putting West Midlands police as a leader in, um, technology I'm policing in the UK. And I think globally, >>And this is a question for both of you because Matthew, as you said, change is difficult and there is always a certain intransigence in workplaces about this is just the way we've always done things and we're used to this and don't try us to get us. Don't try to get us to do anything new here. It works. How do you get the buy-in that you need to do this kind of digital transformation? >>I think it would be wrong to say it was easy. Um, um, we also have to bear in mind that this was one program in a five-year program. So there was a lot of change going on, um, both internally for some of our back office functions, as well as front tie, uh, frontline offices. So with DDI in particular, I think the stack change occurred when people could see what it could do for them. You know, we had lots of workshops and seminars where we all talk about, you know, big data and it's going to be great and it's data analytics and it's transformational, you know, and quite rightly people that are very busy doing a day job, but not necessarily technologists in the main and, you know, are particularly interested quite rightly so in what we are not dealing with the cloud, you know? And it was like, yeah, okay. >>It's one more thing. And then when they started to see on that, on their phones and what teams could do, that's when it started to sell itself. And I think that's when we started to see, you know, to see the stat change, you know, and, and if we, if we have any issues now it's literally, you know, our help desks in meltdown. Cause everyone's like, well, we call it manage without this anymore. And I think that speaks for itself. So it doesn't happen overnight. It's sort of incremental changes and then that's a step change in attitude. And when they see it working and they see the benefits, they want to use it more. And that's how it's become fundamental to all policing by itself, really, without much selling >>You, Helen just made a compelling case for how to get buy in. Have you discovered any other best practices when you are trying to get everyone on board for this kind of thing? >>We've um, we've used a lot of the traditional techniques, things around comms and engagement. We've also used things like, um, the 30 day challenge and nudge theory around how can we gradually encourage people to use things? Um, I think there's a point where all of this around, how do we just keep it simple and keep it user centric from an end user perspective? I think DDI is a great example of where the, the technology is incredibly complex. The solution itself is, um, you know, extremely large and, um, has been very difficult to, um, get delivered. But at the heart of it is a very simple front end for the user to encourage it and take that complexity away from them. Uh, I think that's been critical through the whole piece of DDR. >>One final word from Helen. I want to hear, where do you go from here? What is the longterm vision? I know that this has made productivity, um, productivity savings equivalent to 154 full-time officers. Uh, what's next, >>I think really it's around, um, exploiting what we've got. Um, I use the phrase quite a lot, dialing it up, which drives my technical architects crazy, but because it's apparently not that simple, but, um, you know, we've, we've been through significant change in the last five years and we are still continuing to batch all of those changes into everyday, um, operational policing. But what we need to see is we need to exploit and build on the investments that we've made in terms of data and claims specifically, the next step really is about expanding our pool of data and our functions. Um, so that, you know, we keep getting better and better at this. Um, the more we do, the more data we have, the more refined we can be, the more precise we are with all of our actions. Um, you know, we're always being expected to, again, look after the public purse and do more for less. And I think this is certainly an and our cloud journey and cloud first by design, which is where we are now, um, is helping us to be future-proofed. So for us, it's very much an investment. And I see now that we have good at embedded in operational policing for me, this is the start of our journey, not the end. So it's really exciting to see where we can go from here. >>Exciting times. Indeed. Thank you so much. Lily, Helen and Matthew for joining us. I really appreciate it. Thank you. And you are watching the cube stay tuned for more of the cubes coverage of the AWS reinvent Accenture executive summit. I'm Rebecca Knight from around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Hi, everyone. Welcome to the cube virtual coverage of the executive summit at AWS reinvent 2020 virtual. This is the cube virtual. We can't be there in person like we are every year we have to be remote. This executive summit is with special programming supported by Accenture where the cube virtual I'm your host John for a year, we had a great panel here called uncloud first digital transformation from some experts, Stuart driver, the director of it and infrastructure and operates at lion Australia, Douglas Regan, managing director, client account lead at lion for Accenture as a deep Islam associate director application development lead for Accenture gentlemen, thanks for coming on the cube virtual that's a mouthful, all that digital, but the bottom line it's cloud transformation. This is a journey that you guys have been on together for over 10 years to be really a digital company. Now, some things have happened in the past year that kind of brings all this together. This is about the next generation organization. So I want to ask Stuart you first, if you can talk about this transformation at lion has undertaken some of the challenges and opportunities and how this year in particular has brought it together because you know, COVID has been the accelerant of digital transformation. Well, if you're 10 years in, I'm sure you're there. You're in the, uh, on that wave right now. Take a minute to explain this transformation journey. >>Yeah, sure. So number of years back, we looked at kind of our infrastructure and our landscape trying to figure out where we >>Wanted to go next. And we were very analog based and stuck in the old it groove of, you know, Capitol reef rash, um, struggling to transform, struggling to get to a digital platform and we needed to change it up so that we could become very different business to the one that we were back then obviously cloud is an accelerant to that. And we had a number of initiatives that needed a platform to build on. And a cloud infrastructure was the way that we started to do that. So we went through a number of transformation programs that we didn't want to do that in the old world. We wanted to do it in a new world. So for us, it was partnering up with a dried organizations that can take you on the journey and, uh, you know, start to deliver bit by bit incremental progress, uh, to get to the, uh, I guess the promise land. >>Um, we're not, not all the way there, but to where we're on the way along. And then when you get to some of the challenges like we've had this year, um, it makes all of the hard work worthwhile because you can actually change pretty quickly, um, provide capacity and, uh, and increase your environments and, you know, do the things that you need to do in a much more dynamic way than we would have been able to previously where we might've been waiting for the hardware vendors, et cetera, to deliver capacity. So for us this year, it's been a pretty strong year from an it perspective and delivering for the business needs >>Before I hit the Douglas. I want to just real quick, a redirect to you and say, you know, if all the people said, Oh yeah, you got to jump on cloud, get in early, you know, a lot of naysayers like, well, wait till to mature a little bit, really, if you got in early and you, you know, paying your dues, if you will taking that medicine with the cloud, you're really kind of peaking at the right time. Is that true? Is that one of the benefits that comes out of this getting in the cloud? Yeah, >>John, this has been an unprecedented year, right. And, um, you know, Australia, we had to live through Bush fires and then we had covert and, and then we actually had to deliver a, um, a project on very large transformational project, completely remote. And then we also had had some, some cyber challenges, which is public as well. And I don't think if we weren't moved into and enabled through the cloud, we would have been able to achieve that this year. It would have been much different, would have been very difficult to do the backing. We're able to work and partner with Amazon through this year, which is unprecedented and actually come out the other end. Then we've delivered a brand new digital capability across the entire business. Um, in many, you know, wouldn't have been impossible if we could, I guess, state in the old world, the fact that we were moved into the new Naval by the new allowed us to work in this unprecedented year. >>Just quick, what's your personal view on this? Because I've been saying on the Cuban reporting necessity is the mother of all invention and the word agility has been kicked around as kind of a cliche, Oh, it'd be agile. You know, we're going to get the city, you get a minute on specifically, but from your perspective, uh, Douglas, what does that mean to you? Because there is benefits there for being agile. And >>I mean, I think as Stuart mentioned, right, in a lot of these things we try to do and, you know, typically, you know, hardware and of the last >>To be told and, and, and always on the critical path to be done, we really didn't have that in this case, what we were doing with our projects in our deployments, right. We were able to move quickly able to make decisions in line with the business and really get things going. Right. So you see a lot of times in a traditional world, you have these inhibitors, you have these critical path, it takes weeks and months to get things done as opposed to hours and days, and truly allowed us to, we had to, you know, VJ things, move things. And, you know, we were able to do that in this environment with AWS support and the fact that we can kind of turn things off and on as quickly as we need it. >>Yeah. Cloud-scale is great for speed. So DECA, Gardez get your thoughts on this cloud first mission, you know, it, you know, the dev ops world, they saw this early that jumping in there, they saw the, the, the agility. Now the theme this year is modern applications with the COVID pandemic pressure, there's real business pressure to make that happen. How did you guys learn to get there fast? And what specifically did you guys do at Accenture and how did it all come together? Can you take us inside kind of how it played out? >>Oh, right. So yeah, we started off with, as we do in most cases with a much more bigger group, and we worked with lions functional experts and, uh, the lost knowledge that allowed the infrastructure being had. Um, we then applied our journey to cloud strategy, which basically revolves around the seminars and, and, uh, you know, the deep three steps from our perspective, uh, assessing the current environment, setting up the new cloud environment. And as we go modernizing and, and migrating these applications to the cloud now, you know, one of the key things that, uh, you know, we learned along this journey was that, you know, you can have the best plans, but bottom line that we were dealing with, we often than not have to make changes. Uh, what a lot of agility and also work with a lot of collaboration with the, uh, Lyon team, as well as, uh, uh, AWS. I think the key thing for me was being able to really bring it all together. It's not just, uh, you know, essentially mobilize it's all of us working together to make this happen. >>What were some of the learnings real quick journeys? >>So I think so the perspective of the key learnings that, you know, uh, you know, when you look back at, uh, the, the infrastructure that was that we were trying to migrate over to the cloud, a lot of the documentation, et cetera, was not available. We were having to, uh, figure out a lot of things on the fly. Now that really required us to have, uh, uh, people with deep expertise who could go into those environments and, and work out, uh, you know, the best ways to, to migrate the workloads to the cloud. Uh, I think, you know, the, the biggest thing for me was making sure all the had on that real SMEs across the board globally, that we could leverage across the various technologies, uh, uh, and, and, and, you know, that would really work in our collaborative and agile environment with line. >>Let's do what I got to ask you. How did you address your approach to the cloud and what was your experience? >>Yeah, for me, it's around getting the foundations right. To start with and then building on them. Um, so, you know, you've gotta have your, your, your process and you've got to have your, your kind of your infrastructure there and your blueprints ready. Um, AWS do a great job of that, right. Getting the foundations right. And then building upon it, and then, you know, partnering with Accenture allows you to do that very successfully. Um, I think, um, you know, the one thing that was probably surprising to us when we started down this journey and kind of after we got a long way down the track and looking backwards is actually how much you can just turn off. Right? So a lot of stuff that you, uh, you get left with a legacy in your environment, and when you start to work through it with the types of people that civic just mentioned, you know, the technical expertise working with the business, um, you can really rationalize your environment and, uh, you know, cloud is a good opportunity to do that, to drive that legacy out. >>Um, so you know, a few things there, the other thing is, um, you've got to try and figure out the benefits that you're going to get out of moving here. So there's no point just taking something that is not delivering a huge amount of value in the traditional world, moving it into the cloud, and guess what is going to deliver the same limited amount of value. So you've got to transform it, and you've got to make sure that you build it for the future and understand exactly what you're trying to gain out of it. So again, you need a strong collaboration. You need a good partners to work with, and you need good engagement from the business as well, because the kind of, uh, you know, digital transformation, cloud transformation, isn't really an it project, I guess, fundamentally it is at the core, but it's a business project that you've got to get the whole business aligned on. You've got to make sure that your investment streams are appropriate and that you're able to understand the benefits and the value that, so you're going to drive back towards the business. >>Let's do it. If you don't mind me asking, what was some of the obstacles you encountered or learnings, um, that might different from the expectation we all been there, Hey, you know, we're going to change the world. Here's the sales pitch, here's the outcome. And then obviously things happen, you know, you learn legacy, okay. Let's put some containerization around that cloud native, um, all that rational. You're talking about what are, and you're going to have obstacles. That's how you learn. That's how perfection has developed. How, what obstacles did you come up with and how are they different from your expectations going in? >>Yeah, they're probably no different from other people that have gone down the same journey. If I'm totally honest, the, you know, 70 or 80% of what you do is relatively easy of the known quantity. It's relatively modern architectures and infrastructures, and you can upgrade, migrate, move them into the cloud, whatever it is, rehost, replatform, rearchitect, whatever it is you want to do, it's the other stuff, right? It's the stuff that always gets left behind. And that's the challenge. It's, it's getting that last bit over the line and making sure that you haven't invested in the future while still carrying all of your legacy costs and complexity within your environment. So, um, to be quite honest, that's probably taken longer and has been more of a challenge than we thought it would be. Um, the other piece I touched on earlier on in terms of what was surprising was actually how much of, uh, your environment is actually not needed anymore. >>When you start to put a critical eye across it and understand, um, uh, ask the tough questions and start to understand exactly what, what it is you're trying to achieve. So if you ask a part of a business, do they still need this application or this service a hundred percent of the time, they will say yes until you start to lay out to them, okay, now I'm going to cost you this to migrate it or this, to run it in the future. And, you know, here's your ongoing costs and, you know, et cetera, et cetera. And then, uh, for a significant amount of those answers, you get a different response when you start to layer on the true value of it. So you start to flush out those hidden costs within the business, and you start to make some critical decisions as a company based on, uh, based on that. So that was a little tougher than we first thought and probably broader than we thought there was more of that than we anticipated, um, which actually results in a much cleaner environment post and post migration. >>You know, the old expression, if it moves automated, you know, it's kind of a joke on government, how they want to tax everything, you know, you want to automate, that's a key thing in cloud, and you've got to discover those opportunities to create value Stuart and Sadiq. Mainly if you can weigh in on this love to know the percentage of total cloud that you have now, versus when you started, because as you start to uncover whether it's by design for purpose, or you discover opportunities to innovate, like you guys have, I'm sure it kind of, you took on some territory inside Lyon, what percentage of cloud now versus stark? >>Yeah. At the start, it was minimal, right. You know, close to zero, right. Single and single digits. Right. It was mainly SAS environments that we had, uh, sitting in clouds when we, uh, when we started, um, Doug mentioned earlier on a really significant transformation project, um, that we've undertaken and recently gone live on a multi-year one. Um, you know, that's all stood up on AWS and is a significant portion of our environment, um, in terms of what we can move to cloud. Uh, we're probably at about 80 or 90% now. And the balanced bit is, um, legacy infrastructure that is just gonna retire as we go through the cycle rather than migrate to the cloud. Um, so we are significantly cloud-based and, uh, you know, we're reaping the benefits of it. I know you like 20, 20, I'm actually glad that you did all the hard yards in the previous years when you started that business challenges thrown out as, >>So do you any common reaction to the cloud percentage penetration? >>I mean, guys don't, but I was going to say was, I think it's like the 80 20 rule, right? We, we, we worked really hard in the, you know, I think 2018, 19 to get any person off, uh, after getting a loan, the cloud and, or the last year is the 20% that we have been migrating. And Stuart said like, uh, not that is also, that's going to be a good diet. And I think our next big step is going to be obviously, you know, the icing on the tape, which is to decommission all these apps as well. Right. So, you know, to get the real benefits out of, uh, the whole conservation program from a, uh, from a >>Douglas and Stewart, can you guys talk about the decision around the cloud because you guys have had success with AWS, why AWS how's that decision made? Can you guys give some insight into some of those thoughts? >>I can stop, start off. I think back when the decision was made and it was, it was a while back, um, you know, there's some clear advantages of moving relay, Ws, a lot of alignment with some of the significant projects and, uh, the trend, that particular one big transformation project that we've alluded to as well. Um, you know, we needed some, uh, some very robust and, um, just future proof and, um, proven technology. And they Ws gave that to us. We needed a lot of those blueprints to help us move down the path. We didn't want to reinvent everything. So, um, you know, having a lot of that legwork done for us and AWS gives you that, right. And, and particularly when you partner up with, uh, with a company like Accenture as well, you get combinations of the technology and the skills and the knowledge to, to move you forward in that direction. >>So, um, you know, for us, it was a, uh, uh, it was a decision based on, you know, best of breed, um, you know, looking forward and, and trying to predict the future needs and, and, and kind of the environmental that we might need. Um, and, you know, partnering up with organizations that can then take you on the journey. Yeah. And just to build on it. So obviously, you know, lion's like an AWS, but, you know, we knew it was a very good choice given that, um, uh, the skills and the capability that we had, as well as the assets and tools we had to get the most out of, um, AWS and obviously our, our CEO globally, you know, announcement about a huge investment that we're making in cloud. Um, but you know, we've, we've worked very well DWS, we've done some joint workshops and joint investments, um, some joint POC. So yeah, w we have a very good working relationship, AWS, and I think, um, one incident to reflect upon whether it's cyber it's and again, where we actually jointly, you know, dove in with, um, with Amazon and some of their security experts and our experts. And we're able to actually work through that with mine quite successfully. So, um, you know, really good behaviors as an organization, but also really good capabilities. >>Yeah. As you guys, you're essential cloud outcomes, research shown, it's the cycle of innovation with the cloud. That's creating a lot of benefits, knowing what you guys know now, looking back certainly COVID is impacted a lot of people kind of going through the same process, knowing what you guys know now, would you advocate people to jump on this transformation journey? If so, how, and what tweaks they make, which changes, what would you advise? >>Uh, I might take that one to start with. Um, I hate to think where we would have been when, uh, COVID kicked off here in Australia and, you know, we were all sent home, literally were at work on the Friday, and then over the weekend. And then Monday, we were told not to come back into the office and all of a sudden, um, our capacity in terms of remote access and I quadrupled, or more four, five X, uh, what we had on the Friday we needed on the Monday. And we were able to stand that up during the day Monday and into Tuesday, because we were cloud-based. And, uh, you know, we just found up your instances and, uh, you know, sort of our licensing, et cetera. And we had all of our people working remotely, um, within, uh, you know, effectively one business day. >>Um, I know peers of mine in other organizations and industries that are relying on kind of a traditional wise and getting hardware, et cetera, that were weeks and months before they could get their, the right hardware to be able to deliver to their user base. So, um, you know, one example where you're able to scale and, uh, uh, get, uh, get value out of this platform beyond probably what was anticipated at the time you talk about, um, you know, less the, in all of these kinds of things. And you can also think of a few scenarios, but real world ones where you're getting your business back up and running in that period of time is, is just phenomenal. There's other stuff, right? There's these programs that we've rolled out, you do your sizing, um, and in the traditional world, you would just go out and buy more servers than you need. >>And, you know, probably never realize the full value of those, you know, the capability of those servers over the life cycle of them. Whereas you're in a cloud world, you put in what you think is right. And if it's not right, you pump it up a little bit when, when all of your metrics and so on, tell you that you need to bump it up. And conversely you scale it down at the same rate. So for us, with the types of challenges and programs and, uh, uh, and just business need, that's come at as this year, uh, we wouldn't have been able to do it without a strong cloud base, uh, to, uh, to move forward >>Know Douglas. One of the things that I talked to, a lot of people on the right side of history who have been on the right wave with cloud, with the pandemic, and they're happy, they're like, and they're humble. Like, well, we're just lucky, you know, luck is preparation meets opportunity. And this is really about you guys getting in early and being prepared and readiness. This is kind of important as people realize, then you gotta be ready. I mean, it's not just, you don't get lucky by being in the right place, the right time. And there were a lot of companies were on the wrong side of history here who might get washed away. This is a super important, I think, >>To echo and kind of build on what Stewart said. I think that the reason that we've had success and I guess the momentum is we, we didn't just do it in isolation within it and technology. It was actually linked to broader business changes, you know, creating basically a digital platform for the entire business, moving the business, where are they going to be able to come back stronger after COVID, when they're actually set up for growth, um, and actually allows, you know, lying to achievements growth objectives, and also its ambitions as far as what it wants to do, uh, with growth in whatever they make, do with acquiring other companies and moving into different markets and launching new products. So we've actually done it in a way that is, you know, real and direct business benefit, uh, that actually enables line to grow >>General. I really appreciate you coming. I have one final question. If you can wrap up here, uh, Stuart and Douglas, you don't mind weighing in what's the priorities for the future. What's next for lion in a century >>Christmas holidays, I'll start Christmas holidays been a big deal and then a, and then a reset, obviously, right? So, um, you know, it's, it's figuring out, uh, transform what we've already transformed, if that makes sense. So God, a huge proportion of our services sitting in the cloud. Um, but we know we're not done even with the stuff that is in there. We need to take those next steps. We need more and more automation and orchestration. We need to, um, our environment, there's more future growth. We need to be able to work with the business and understand what's coming at them so that we can, um, you know, build that into, into our environment. So again, it's really transformation on top of transformation is the way that I'll describe it. And it's really an open book, right? Once you get it in and you've got the capabilities and the evolving tool sets that, uh, AWS continue to bring to the market, um, you know, working with the partners to, to figure out how we unlock that value, um, you know, drive our costs down efficiency, uh, all of those kind of, you know, standard metrics. >>Um, but you know, we're looking for the next things to transform and show value back out to our customer base, um, that, uh, that we continue to, you know, sell our products to and work with and understand how we can better meet their needs. Yeah, I think just to echo that, I think it's really leveraging this and then did you capability they have and getting the most out of that investment. And then I think it's also moving to, uh, and adopting more new ways of working as far as, you know, the speed of the business, um, is getting up the speed of the market is changing. So being able to launch and do things quickly and also, um, competitive and efficient operating costs, uh, now that they're in the cloud, right? So I think it's really leveraging the most out of the platform and then, you know, being efficient in launching things. So putting them with the business, >>Any word from you on your priorities by you see this year in folding, >>There's got to say like e-learning squares, right, for me around, you know, just journey. This is a journey to the cloud, right. >>And, uh, you know, as well, the sort of Saturday, it's getting all, you know, different parts of the organization along the journey business to it, to your, uh, product lenders, et cetera. Right. And it takes time. It is tough, but, uh, uh, you know, you got to get started on it. And, you know, once we, once we finish off, uh, it's the realization of the benefits now that, you know, looking forward, I think for, from Alliance perspective, it is, uh, you know, once we migrate all the workloads to the cloud, it is leveraging, uh, all staff, right. And as I think students said earlier, uh, with, uh, you know, the latest and greatest stuff that AWS is basically working to see how we can really, uh, achieve more better operational excellence, uh, from a, uh, from a cloud perspective. >>Well, Stewart, thanks for coming on with a and sharing your environment and what's going on and your journey you're on the right wave. Did the work you're in, it's all coming together with faster, congratulations for your success, and, uh, really appreciate Douglas with Steve for coming on as well from Accenture. Thank you for coming on. Thanks, John. Okay. Just the cubes coverage of executive summit at AWS reinvent. This is where all the thought leaders share their best practices, their journeys, and of course, special programming with Accenture and the cube. I'm Sean ferry, your host, thanks for watching from around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cube virtuals coverage of the Accenture executive summit. Part of AWS reinvent 2020. I'm your host Rebecca Knight. We are talking today about reinventing the energy data platform. We have two guests joining us. First. We have Johan Krebbers. He is the GM digital emerging technologies and VP of it. Innovation at shell. Thank you so much for coming on the show, Johan you're welcome. And next we have Liz Dennett. She is the lead solution architect for O S D U on AWS. Thank you so much Liz to be here. So I want to start our conversation by talking about OSD. You like so many great innovations. It started with a problem Johan. What was the problem you were trying to solve at shell? >>Yeah, the ethical back a couple of years, we started shoving 2017 where we had a meeting with the deg, the gas exploration in shell, and the main problem they had. Of course, they got lots of lots of data, but are unable to find the right data. They need to work from all over the place. And totally >>Went to real, probably tried to solve is how that person working exploration could find their proper date, not just a day, but also the date you really needed that we did probably talked about his summer 2017. And we said, okay, they don't maybe see this moving forward is to start pulling that data into a single data platform. And that, that was at the time that we called it as the, you, the subsurface data universe in there was about the shell name was so in, in January, 2018, we started a project with Amazon to start grating a co fricking that building, that Stu environment that subserve the universe, so that single data level to put all your exploration and Wells data into that single environment that was intent. And every cent, um, already in March of that same year, we said, well, from Michelle point of view, we will be far better off if we could make this an industry solution and not just a shelf sluice, because Shelby, Shelby, if you can make an industry solution where people are developing applications for it, it also is far better than for shell to say we haven't shell special solution because we don't make money out of how we start a day that we can make money out of it. >>We have access to the data, we can explore the data. So storing the data we should do as efficiently possibly can. So we monitor, we reach out to about eight or nine other large, uh, or I guess operators like the economics, like the tutorials, like the chefs of this world and say, Hey, we inshallah doing this. Do you want to join this effort? And to our surprise, they all said, yes. And then in September, 2018, we had our kickoff meeting with your open group where we said, we said, okay, if you want to work together with lots of other companies, we also need to look at okay, how, how we organize that. Or if you started working with lots of large companies, you need to have some legal framework around some framework around it. So that's why we went to the open group and say, okay, let's, let's form the old forum as we call it at the time. So it's September, 2080, where I did a Galleria in Houston, but the kickoff meeting for the OT four with about 10 members at the time. So there's just over two years ago, we started an exercise for me called ODU, uh, kicked it off. Uh, and so that's really them will be coming from and how we've got there. Also >>The origin story. Um, what, so what digging a little deeper there? What were some of the things you were trying to achieve with the OSU? >>Well, a couple of things we've tried to achieve with you, um, first is really separating data from applications for what is, what is the biggest problem we have in the subsurface space that the data and applications are all interlinked tied together. And if, if you have them and a new company coming along and say, I have this new application and is access to the data that is not possible because the data often interlinked with the application. So the first thing we did is really breaking the link between the application, the data out as those levels, the first thing we did, secondly, put all the data to a single data platform, take the silos out what was happening in the sub-service space and know they got all the data in what we call silos in small little islands out there. So what we're trying to do is first break the link to great, great. >>They put the data single day, the bathroom, and the third part, put a standard layer on top of that, it's an API layer on top to create a platform. So we could create an ecosystem out of companies to start a valving shop application on top of dev data platform across you might have a data platform, but you're only successful. If you have a rich ecosystem of people start developing applications on top of that. And then you can export the data like small companies, last company, university, you name it, we're getting after create an ecosystem out there. So the three things were as was first break, the link between application data, just break it and put data at the center and also make sure that data, this data structure would not be managed by one company. It would only be met. It will be managed the data structures by the ODI forum. Secondly, then put a data, a single data platform certainly then has an API layer on top and then create an ecosystem. Really go for people, say, please start developing applications because now you have access to the data or the data no longer linked to somebody whose application was all freely available, but an API layer that was, that was all September, 2018, more or less >>To hear a little bit. Can you talk a little bit about some of the imperatives from the AWS standpoint in terms of what you were trying to achieve with this? Yeah, absolutely. And this whole thing is Johann said started with a challenge that was really brought out at shell. The challenges that geoscientists spend up to 70% of their time looking for data. I'm a geologist I've spent more than 70% of my time trying to find data in these silos. And from there, instead of just figuring out how we could address that one problem, we worked together to really understand the root cause of these challenges and working backwards from that use case OSU and OSU on AWS has really enabled customers to create solutions that span, not just this in particular problem, but can really scale to be inclusive of the entire energy value chain and deliver value from these use cases to the energy industry and beyond. >>Thank you, Lee, >>Uh, Johann. So talk a little bit about Accenture's cloud first approach and how it has, uh, helped shell work faster and better with it. >>Well, of course, access a cloud first approach only works together. It's been an Amazon environment, AWS environment. So we really look at, uh, at, at Accenture and others up together helping shell in this space. Now the combination of the two is where we're really looking at, uh, where access of course can be increased knowledge student to that environment operates support knowledge to do an environment. And of course, Amazon will be doing that to this environment that underpinning their services, et cetera. So, uh, we would expect a combination, a lot of goods when we started rolling out and put in production, the old you are three and four because we are anus. Then when release feed comes to the market in Q1 next year of ODU, when he started going to Audi production inside shell, but as the first release, which is ready for prime time production across an enterprise will be released just before Christmas, last year when he's still in may of this year. But really three is the first release we want to use for full scale production deployment inside shell, and also all the operators around the world. And there is one Amazon, sorry, at that one. Um, extensive can play a role in the ongoing, in the, in deployment building up, but also support environment. >>So one of the other things that we talk a lot about here on the cube is sustainability. And this is a big imperative at so many organizations around the world in particular energy companies. How does this move to OSD you, uh, help organizations become, how is this a greener solution for companies? >>Well, first he make it's a greatest solution because you start making a much more efficient use of your resources. is already an important one. The second thing we're doing is also, we started with ODU in framers, in the oil and gas space in the expert development space. We've grown, uh, OTU in our strategy, we've grown. I was, you know, also do an alternative energy sociology. We'll all start supporting next year. Things like solar farms, wind farms, uh, the, the dermatomal environment hydration. So it becomes an and, and an open energy data platform, not just what I want to get into steep that's for new industry, any type of energy industry. So our focus is to create, bring the data of all those various energy data sources to get me to a single data platform you can to use AI and other technology on top of that, to exploit the data, to beat again into a single data platform. >>Liz, I want to ask you about security because security is, is, is such a big concern when it comes to data. How secure is the data on OSD? You, um, actually, can I talk, can I do a follow up on this sustainability talking? Oh, absolutely. By all means. I mean, I want to interject though security is absolutely our top priority. I don't mean to move away from that, but with sustainability, in addition to the benefits of the OSU data platform, when a company moves from on-prem to the cloud, they're also able to leverage the benefits of scale. Now, AWS is committed to running our business in the most environmentally friendly way possible. And our scale allows us to achieve higher resource utilization and energy efficiency than a typical data center. Now, a recent study by four 51 research found that AWS is infrastructure is 3.6 times more energy efficient than the median of surveyed enterprise data centers. Two thirds of that advantage is due to higher, um, server utilization and a more energy efficient server population. But when you factor in the carbon intensity of consumed electricity and renewable energy purchases for 51 found that AWS performs the same task with an 88% lower carbon footprint. Now that's just another way that AWS and OSU are working to support our customers is they seek to better understand their workflows and make their legacy businesses less carbon intensive. >>That's that's incorrect. Those are those statistics are incredible. Do you want to talk a little bit now about security? Absolutely. Security will always be AWS is top priority. In fact, AWS has been architected to be the most flexible and secure cloud computing environment available today. Our core infrastructure is built to satisfy. There are the security requirements for the military global banks and other high sensitivity organizations. And in fact, AWS uses the same secure hardware and software to build an operate each of our regions. So that customers benefit from the only commercial cloud that's hat hits service offerings and associated supply chain vetted and deemed secure enough for top secret workloads. That's backed by a deep set of cloud security tools with more than 200 security compliance and governmental service and key features as well as an ecosystem of partners like Accenture, that can really help our customers to make sure that their environments for their data meet and or exceed their security requirements. Johann, I want you to talk a little bit about how OSD you can be used today. Does it only handle subsurface data? >>Uh, today it's Honda's subserves or Wells data. We got to add to that production around the middle of next year. That means that the whole upstate business. So we've got goes from exploration all the way to production. You've made it together into a single data platform. So production will be added around Q3 of next year. Then a principal. We have a difficult, the elder data that single environment, and we want to extend it then to other data sources or energy sources like solar farms, wind farms, uh, hydrogen, hydro, et cetera. So we're going to add a whore, a whole list of audit day energy source to them and be all the data together into a single data club. So we move from an all in guest data platform to an entity data platform. That's really what our objective is because the whole industry, if you look it over, look at our competition or moving in that same two acts of quantity of course, are very strong in oil and gas, but also increased the, got into other energy sources like, like solar, like wind, like th like highly attended, et cetera. So we would be moving exactly what it's saying, method that, that, that, that the whole OSU can't really support at home. And as a spectrum of energy sources, >>Of course, and Liz and Johan. I want you to close this out here by just giving us a look into your crystal balls and talking about the five and 10 year plan for OSD. We'll start with you, Liz, what do you, what do you see as the future holding for this platform? Um, honestly, the incredibly cool thing about working at AWS is you never know where the innovation and the journey is going to take you. I personally am looking forward to work with our customers, wherever their OSU journeys, take them, whether it's enabling new energy solutions or continuing to expand, to support use cases throughout the energy value chain and beyond, but really looking forward to continuing to partner as we innovate to slay tomorrow's challenges, Johann first, nobody can look at any more nowadays, especially 10 years, but our objective is really in the next five years, you will become the key backbone for energy companies for store your data intelligence and optimize the whole supply energy supply chain, uh, in this world Johan Krebbers Liz Dennett. Thank you so much for coming on the cube virtual. Thank you. I'm Rebecca Knight stay tuned for more of our coverage of the Accenture executive summit >>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cubes coverage of the Accenture executive summit. Part of AWS reinvent. I'm your host Rebecca Knight today we're welcoming back to Cuba alum. We have Kishor Dirk. He is the Accenture senior managing director cloud first global services lead. Welcome back to the show Kishore. Thank you very much. Nice to meet again. And, uh, Tristan moral horse set. He is the managing director, Accenture cloud first North American growth. Welcome back to you to Tristin. Great to be back in grapes here again, Rebecca. Exactly. Even in this virtual format, it is good to see your faces. Um, today we're going to be talking about my NAB and green cloud advisor capability. Kishor I want to start with you. So my NAB is a platform that is really celebrating its first year in existence. Uh, November, 2019 is when Accenture introduced it. Uh, but it's, it has new relevance in light of this global pandemic that we are all enduring and suffering through. Tell us a little bit about the lineup platform, what it is that cloud platform to help our clients navigate the complexity of cloud and cloud decisions and to make it faster. And obviously, you know, we have in the cloud, uh, you know, with >>The increased relevance and all the, especially over the last few months with the impact of COVID crisis and exhibition of digital transformation, you know, we are seeing the transformation of the exhibition to cloud much faster. This platform that you're talking about has enabled hardened 40 clients globally across different industries. You identify the right cloud solution, navigate the complexity, provide a cloud specific solution simulate for our clients to meet that strategy business needs. And the clients are loving it. >>I want to go to you now trust and tell us a little bit about how my nav works and how it helps companies make good cloud choice. >>Yeah, so Rebecca, we we've talked about cloud is, is more than just infrastructure and that's what mine app tries to solve for it. It really looks at a variety of variables, including infrastructure operating model and fundamentally what clients' business outcomes, um, uh, our clients are, are looking for and, and identifies the optimal solution for what they need. And we assign this to accelerate. And we mentioned that the pandemic, one of the big focus now is to accelerate. And so we worked through a three-step process. The first is scanning and assessing our client's infrastructure, their data landscape, their application. Second, we use our automated artificial intelligence engine to interact with. We have a wide variety and library of, uh, collective plot expertise. And we look to recommend what is the enterprise architecture and solution. And then third, before we live with our clients, we look to simulate and test this scaled up model. And the simulation gives our clients a way to see what cloud is going to look like, feel like and how it's going to transform their business before they go there. >>Tell us a little bit about that in real life. Now as a company, so many of people are working remotely having to collaborate, uh, not in real life. How is that helping them right now? >>So, um, the, the pandemic has put a tremendous strain on systems, uh, because of the demand on those systems. And so we talk about resiliency. We also now need to collaborate across data across people. Um, I think all of us are calling from a variety of different places where our last year we were all at the VA cube itself. Um, and, and cloud technologies such as teams, zoom that we're we're leveraging now has fundamentally accelerated and clients are looking to onboard this for their capabilities. They're trying to accelerate their journey. They realize that now the cloud is what is going to become important for them to differentiate. Once we come out of the pandemic and the ability to collaborate with their employees, their partners, and their clients through these systems is becoming a true business differentiator for our clients. >>Keisha, I want to talk with you now about my navs multiple capabilities, um, and helping clients design and navigate their cloud journeys. Tell us a little bit about the green cloud advisor capability and its significance, particularly as so many companies are thinking more deeply and thoughtfully about sustainability. >>Yes. So since the launch of my NAB, we continue to enhance capabilities for our clients. One of the significant, uh, capabilities that we have enabled is the being or advisor today. You know, Rebecca, a lot of the businesses are more environmentally aware and are expanding efforts to decrease power consumption, uh, and obviously carbon emissions and, uh, and run a sustainable operations across every aspect of the enterprise. Uh, as a result, you're seeing an increasing trend in adoption of energy, efficient infrastructure in the global market. And one of the things that we did, a lot of research we found out is that there's an ability to influence our client's carbon footprint through a better cloud solution. And that's what we internalize, uh, brings to us, uh, in, in terms of a lot of the client connotation that you're seeing in Europe, North America and others. Lot of our clients are accelerating to a green cloud strategy to unlock greater financial societal and environmental benefit, uh, through obviously cloud-based circular, operational, sustainable products and services. That is something that we are enhancing my now, and we are having active client discussions at this point of time. >>So Tristan, tell us a little bit about how this capability helps clients make greener decisions. >>Yeah. Um, well, let's start about the investments from the cloud providers in renewable and sustainable energy. Um, they have most of the hyperscalers today, um, have been investing significantly on data centers that are run on renewable energy, some incredibly creative constructs on the, how, how to do that. And sustainability is there for a key, um, key item of importance for the hyperscalers and also for our clients who now are looking for sustainable energy. And it turns out this marriage is now possible. I can, we marry the, the green capabilities of the cloud providers with a sustainability agenda of our clients. And so what we look into the way the mind works is it looks at industry benchmarks and evaluates our current clients, um, capabilities and carpet footprint leveraging their existing data centers. We then look to model from an end-to-end perspective, how the, their journey to the cloud leveraging sustainable and, um, and data centers with renewable energy. We look at how their solution will look like and, and quantify carbon tax credits, um, improve a green index score and provide quantifiable, um, green cloud capabilities and measurable outcomes to our clients, shareholders, stakeholders, clients, and customers. Um, and our green plot advisers sustainability solutions already been implemented at three clients. And in many cases in two cases has helped them reduce the carbon footprint by up to 400% through migration from their existing data center to green cloud. Very, very, >>That is remarkable. Now tell us a little bit about the kinds of clients. Is this, is this more interesting to clients in Europe? Would you say that it's catching on in the United States? Where, what is the breakdown that you're seeing right now? >>Sustainability is becoming such a global agenda and we're seeing our clients, um, uh, tie this and put this at board level, um, uh, agenda and requirements across the globe. Um, Europe has specific constraints around data sovereignty, right, where they need their data in country, but from a green, a sustainability agenda, we see clients across all our markets, North America, Europe in our growth markets adopt this. And we have seen case studies and all three months, >>Kesha. I want to bring you back into the conversation. Talk a little bit about how MindUP ties into Accenture's cloud first strategy, your Accenture's CEO, Julie Sweet, um, has talked about post COVID leadership, requiring every business to become a cloud first business. Tell us a little bit about how this ethos is in Accenture and how you're sort of looking outward with it too. >>So Rebecca mine is the launch pad, uh, to a cloud first transformation for our clients. Uh, Accenture, see your jewelry suite, uh, shared the Accenture cloud first and our substantial investment demonstrate our commitment and is delivering greater value for our clients when they need it the most. And with the digital transformation requiring cloud at scale, you know, we're seeing that in the post COVID leadership, it requires that every business should become a cloud business. And my nap helps them get there by evaluating the cloud landscape, navigating the complexity, modeling architecting and simulating an optimal cloud solution for our clients. And as Justin was sharing a greener cloud. >>So Tristan, talk a little bit more about some of the real life use cases in terms of what are we, what are clients seeing? What are the results that they're having? >>Yes. Thank you, Rebecca. I would say two key things right around my notes. The first is the iterative process. Clients don't want to wait, um, until they get started, they want to get started and see what their journey is going to look like. And the second is fundamental acceleration, dependent make, as we talked about, has accelerated the need to move to cloud very quickly. And my nav is there to do that. So how do we do that? First is generating the business cases. Clients need to know in many cases that they have a business case by business case, we talk about the financial benefits, as well as the business outcomes, the green, green clot impact sustainability impacts with minus. We can build initial recommendations using a basic understanding of their environment and benchmarks in weeks versus months with indicative value savings in the millions of dollars arranges. >>So for example, very recently, we worked with a global oil and gas company, and in only two weeks, we're able to provide an indicative savings where $27 million over five years, this enabled the client to get started, knowing that there is a business case benefit and then iterate on it. And this iteration is, I would say the second point that is particularly important with my nav that we've seen in bank of clients, which is, um, any journey starts with an understanding of what is the application landscape and what are we trying to do with those, these initial assessments that used to take six to eight weeks are now taking anywhere from two to four weeks. So we're seeing a 40 to 50% reduction in the initial assessment, which gets clients started in their journey. And then finally we've had discussions with all of the hyperscalers to help partner with Accenture and leverage mine after prepared their detailed business case module as they're going to clients. And as they're accelerating the client's journey, so real results, real acceleration. And is there a journey? Do I have a business case and furthermore accelerating the journey once we are by giving the ability to work in iterative approach. >>I mean, it sounds as though that the company that clients and and employees are sort of saying, this is an amazing time savings look at what I can do here in, in so much in a condensed amount of time, but in terms of getting everyone on board, one of the things we talked about last time we met, uh, Tristin was just how much, uh, how one of the obstacles is getting people to sign on and the new technologies and new platforms. Those are often the obstacles and struggles that companies face. Have you found that at all? Or what is sort of the feedback that you're getting? >>Yeah, sorry. Yes. We clearly, there are always obstacles to a cloud journey. If there were an obstacles, all our clients would be, uh, already fully in the cloud. What man I gives the ability is to navigate through those, to start quickly. And then as we identify obstacles, we can simulate what things are going to look like. We can continue with certain parts of the journey while we deal with that obstacle. And it's a fundamental accelerator. Whereas in the past one, obstacle would prevent a class from starting. We can now start to address the obstacles one at a time while continuing and accelerating the contrary. That is the fundamental difference. >>Kishor I want to give you the final word here. Tell us a little bit about what is next for Accenture might have and what we'll be discussing next year at the Accenture executive summit, >>Rebecca, we are continuously evolving with our client needs and reinventing reinventing for the future. Well, mine has been toward advisor. Our plan is to help our clients reduce carbon footprint and again, migrate to a green cloud. Uh, and additionally, we're looking at, you know, two capabilities, uh, which include sovereign cloud advisor, uh, with clients, especially in, in Europe and others are under pressure to meet, uh, stringent data norms that Kristen was talking about. And the sovereign cloud advisor helps organization to create an architecture cloud architecture that complies with the green. Uh, I would say the data sovereignty norms that is out there. The other element is around data to cloud. We are seeing massive migration, uh, for, uh, for a lot of the data to cloud. And there's a lot of migration hurdles that come within that. Uh, we have expanded mine app to support assessment capabilities, uh, for, uh, assessing applications, infrastructure, but also covering the entire state, including data and the code level to determine the right cloud solution. So we are, we are pushing the boundaries on what mine app can do with mine. Have you created the ability to take the guesswork out of cloud, navigate the complexity? We are rolling risks costs, and we are, you know, achieving client's static business objectives while building a sustainable alerts with being cloud, >>Any platform that can take some of the guesswork out of the future. I am I'm on board with thank you so much, Tristin and Kishore. This has been a great conversation. Stay tuned for more of the cubes coverage of the Accenture executive summit. I'm Rebecca Knight.
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It's the cube with digital coverage Welcome to cube three 60 fives coverage of the Accenture executive summit. Thanks for having me here. impact of the COVID-19 pandemic has been, what are you hearing from clients? you know, various facets, you know, um, first and foremost, to this reasonably okay, and are, you know, launching to So you just talked about the widening gap. all the changes the pandemic has brought to them. in the cloud that we are going to see. Can you tell us a little bit more about what this strategy entails? all of the systems under which they attract need to be liberated so that you could drive now, the center of gravity is elevated to it becoming a C-suite agenda on everybody's And it, and it's a strategy, but the way you're describing it, it sounds like it's also a mindset and an approach, That is their employees, uh, because you do, across every department, I'm the agent of this change is going to be the employees or weapon, So how are you helping your clients, And that is again, the power of cloud. And the power of cloud is to get all of these capabilities from outside that employee, the employee will be more engaged in his or her job and therefore And this is, um, you know, no more true than how So at Accenture, you have long, long, deep Stan, sorry, And in fact, in the cloud world, it was one of the first, um, And one great example is what we are doing with Takeda, uh, billable, So all of these things that we will do Yeah, the future to the next, you know, base camp, as I would call it to further this productivity, And the evolution that is going to happen where, you know, the human grace of mankind, I genuinely believe that cloud first is going to be in the forefront of that change It's the cube with digital coverage I want to start by asking you what it is that we mean when we say green cloud, magnitude of the problem that is out there and how do we pursue a green approach. Them a lot of questions, the decision to make, uh, this particular, And, uh, you know, the, obviously the companies have to unlock greater financial How do you partner and what is your approach in terms of helping them with their migrations? uh, you know, from a few manufacturers hand sanitizers, and to answer it role there, uh, you know, from, in terms of our clients, you know, there are multiple steps And in the third year and another 3 million analytics costs that are saved through right-sizing Instead of it, we practice what we preach, and that is something that we take it to heart. We know that conquering this pandemic is going to take a coordinated And it's about a group of global stakeholders cooperating to simultaneously manage the uh, in, in UK to build, uh, uh, you know, uh, Microsoft teams in What do you see as the different, the financial security or agility benefits to cloud. And obviously the ecosystem partnership that we have that We, what, what do you think the next 12 to 24 months? And we all along with Accenture clients will win. Thank you so much. It's the cube with digital coverage of AWS reinvent executive And what happens when you bring together the scientific and I think that, you know, there's a, there's a need ultimately to, you know, accelerate and, And, you know, we were commenting on this earlier, but there's, you know, it's been highlighted by a number of factors. And I think that, you know, that's going to help us make faster, better decisions. Um, and so I think with that, you know, there's a few different, How do we re-imagine that, you know, how do ideas go from getting tested So Arjun, I want to bring you into this conversation a little bit, let let's delve into those a bit. It was, uh, something that, you know, we had all to do differently. And maybe the third thing I would say is this one team And I think if you really think about what he's talking about, Because the old ways of thinking where you've got application people and infrastructure, How will their experience of work change and how are you helping re-imagine and And it's something that, you know, I think we all have to think a lot about, I mean, And then secondly, I think that, you know, we're, we're very clear that there's a number of areas where there are Uh, and so I think that that's, you know, one, one element that, uh, can be considered. or how do we collaborate across the number of boundaries, you know, and I think, uh, Arjun spoke eloquently the customer obsession and this idea of innovating much more quickly. and Carl mentioned some of the things that, you know, partner like AWS can bring to the table is we talk a lot about builders, And it's not just the technical people or the it people who are And Accenture's, and so we were able to bring that together. And so we chose, you know, uh, with our focus on innovation that when people think about cloud, you know, you always think about infrastructure technology. And thank you for tuning into the cube. It's the cube with digital coverage So we are going to be talking and also what were some of the challenges that you were grappling with prior to this initiative? Um, so the reason we sort of embarked um, you know, certainly as a, as an it leader and sort of my operational colleagues, What is the art of the possible, can you tell us a little bit about why you chose the public sector that, you know, there are many rules and regulations, uh, quite rightly as you would expect Matthew, I want to bring you into the conversation a little bit here. to bring in a number of the different themes that we have say, cloud teams, security teams, um, I mean, so much of this is about embracing comprehensive change to experiment and innovate and and the outcomes they're looking to achieve rather than simply focusing on a long list of requirements, It's not always a one size fits all. um, that is gonna update before you even get that. So to give you a little bit of, of context, when we, um, started And the pilot was so successful. And I think just parallel to that is the quality of our, because we had a lot of data, That kind of return on investment because what you were just describing with all the steps that we needed Um, but all the, you know, the minutes here and there certainly add up Have you seen any changes Um, but you can see the step change that is making in each aspect to the organization, And this is a question for both of you because Matthew, as you said, change is difficult and there is always a certain You know, we had lots of workshops and seminars where we all talk about, you know, you know, to see the stat change, you know, and, and if we, if we have any issues now it's literally, when you are trying to get everyone on board for this kind of thing? The solution itself is, um, you know, extremely large and, um, I want to hear, where do you go from here? crazy, but because it's apparently not that simple, but, um, you know, And you are watching the cube stay tuned for more of the cubes coverage of the AWS in particular has brought it together because you know, COVID has been the accelerant So number of years back, we looked at kind of our infrastructure and our landscape trying to figure uh, you know, start to deliver bit by bit incremental progress, uh, to get to the, of the challenges like we've had this year, um, it makes all of the hard work worthwhile because you can actually I want to just real quick, a redirect to you and say, you know, if all the people said, Oh yeah, And, um, you know, Australia, we had to live through Bush fires You know, we're going to get the city, you get a minute on specifically, but from your perspective, uh, Douglas, to hours and days, and truly allowed us to, we had to, you know, VJ things, And what specifically did you guys do at Accenture and how did it all come together? the seminars and, and, uh, you know, the deep three steps from uh, uh, and, and, and, you know, that would really work in our collaborative and agile environment How did you address your approach to the cloud and what was your experience? And then building upon it, and then, you know, partnering with Accenture allows because the kind of, uh, you know, digital transformation, cloud transformation, learnings, um, that might different from the expectation we all been there, Hey, you know, It's, it's getting that last bit over the line and making sure that you haven't invested in the future hundred percent of the time, they will say yes until you start to lay out to them, okay, You know, the old expression, if it moves automated, you know, it's kind of a joke on government, how they want to tax everything, Um, you know, that's all stood up on AWS and is a significant portion of And I think our next big step is going to be obviously, uh, with a company like Accenture as well, you get combinations of the technology and the skills and the So obviously, you know, lion's like an AWS, but, you know, a lot of people kind of going through the same process, knowing what you guys know now, And we had all of our people working remotely, um, within, uh, you know, effectively one business day. and in the traditional world, you would just go out and buy more servers than you need. And if it's not right, you pump it up a little bit when, when all of your metrics and so on, And this is really about you guys when they're actually set up for growth, um, and actually allows, you know, lying to achievements I really appreciate you coming. to figure out how we unlock that value, um, you know, drive our costs down efficiency, to our customer base, um, that, uh, that we continue to, you know, sell our products to and work with There's got to say like e-learning squares, right, for me around, you know, It is tough, but, uh, uh, you know, you got to get started on it. It's the cube with digital coverage of Thank you so much for coming on the show, Johan you're welcome. Yeah, the ethical back a couple of years, we started shoving 2017 where we it also is far better than for shell to say we haven't shell special solution because we don't So storing the data we should do What were some of the things you were trying to achieve with the OSU? So the first thing we did is really breaking the link between the application, And then you can export the data like small companies, last company, standpoint in terms of what you were trying to achieve with this? uh, helped shell work faster and better with it. a lot of goods when we started rolling out and put in production, the old you are three and four because we are So one of the other things that we talk a lot about here on the cube is sustainability. I was, you know, also do an alternative energy sociology. found that AWS performs the same task with an 88% lower So that customers benefit from the only commercial cloud that's hat hits service offerings and the whole industry, if you look it over, look at our competition or moving in that same two acts of quantity of course, our objective is really in the next five years, you will become the key It's the cube with digital coverage And obviously, you know, we have in the cloud, uh, you know, with and exhibition of digital transformation, you know, we are seeing the transformation of I want to go to you now trust and tell us a little bit about how my nav works and how it helps And then third, before we live with our clients, having to collaborate, uh, not in real life. They realize that now the cloud is what is going to become important for them to differentiate. Keisha, I want to talk with you now about my navs multiple capabilities, And one of the things that we did, a lot of research we found out is that there's an ability to influence So Tristan, tell us a little bit about how this capability helps clients make greener And so what we look into the way the Would you say that it's catching on in the United States? And we have seen case studies and all I want to bring you back into the conversation. And with the digital transformation requiring cloud at scale, you know, we're seeing that in And the second is fundamental acceleration, dependent make, as we talked about, has accelerated the need So for example, very recently, we worked with a global oil and gas company, Have you found that at all? What man I gives the ability is to navigate through those, to start quickly. Kishor I want to give you the final word here. and we are, you know, achieving client's static business objectives while I am I'm on board with thank you so much,
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AWS Executive Summit 2020
>>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome to cube three 60 fives coverage of the Accenture executive summit. Part of AWS reinvent. I'm your host Rebecca Knight. Today we are joined by a cube alum, Karthik, Lorraine. He is Accenture senior managing director and lead Accenture cloud. First, welcome back to the show Karthik. >>Thank you. Thanks for having me here. >>Always a pleasure. So I want to talk to you. You are an industry veteran, you've been in Silicon Valley for decades. Um, I want to hear from your perspective what the impact of the COVID-19 pandemic has been, what are you hearing from clients? What are they struggling with? What are their challenges that they're facing day to day? >>I think, um, COVID-19 is being a eye-opener from, you know, various facets, you know, um, first and foremost, it's a, it's a hell, um, situation that everybody's facing, which is not just, uh, highest economic bearings to it. It has enterprise, um, an organization with bedding to it. And most importantly, it's very personal to people, um, because they themselves and their friends, family near and dear ones are going through this challenge, uh, from various different dimension. But putting that aside, when you come to it from an organization enterprise standpoint, it has changed everything well, the behavior of organizations coming together, working in their campuses, working with each other as friends, family, and, uh, um, near and dear colleagues, all of them are operating differently. So that's what big change to get things done in a completely different way, from how they used to get things done. >>Number two, a lot of things that were planned for normal scenarios, like their global supply chain, how they interact with their client customers, how they go innovate with their partners on how that employees contribute to the success of an organization at all changed. And there are no data models that give them a hint of something like this for them to be prepared for this. So we are seeing organizations, um, that have adapted to this reasonably okay, and are, you know, launching to innovate faster in this. And there are organizations that have started with struggling, but are continuing to struggle. And the gap between the leaders and legs are widening. So this is creating opportunities in a different way for the leaders, um, with a lot of pivot their business, but it's also creating significant challenge for the lag guides, uh, as we defined in our future systems research that we did a year ago, uh, and those organizations are struggling further. So the gap is actually widening. >>So you just talked about the widening gap. I've talked about the tremendous uncertainty that so many companies, even the ones who have adapted reasonably well, uh, in this, in this time, talk a little bit about Accenture cloud first and why, why now? >>I think it's a great question. Um, we believe that for many of our clients COVID-19 has turned, uh, cloud from an experimentation aspiration to an origin mandate. What I mean by that is everybody has been doing something on the other end cloud. There's no company that says we don't believe in cloud are, we don't want to do cloud. It was how much they did in cloud. And they were experimenting. They were doing the new things in cloud, but they were operating a lot of their core business outside the cloud or not in the cloud. Those organizations have struggled to operate in this new normal, in a remote fashion, as well as, uh, their ability to pivot to all the changes the pandemic has brought to them. But on the other hand, the organizations that had a solid foundation in cloud were able to collect faster and not actually gone into the stage of innovating faster and driving a new behavior in the market, new behavior within their organization. >>So we are seeing that spend to make is actually fast-forwarded something that we always believed was going to happen. This, uh, uh, moving to cloud over the next decade is fast forward it to happen in the next three to five years. And it's created this moment where it's a once in an era, really replatforming of businesses in the cloud that we are going to see. And we see this moment as a cloud first moment where organizations will use cloud as the, the, the canvas and the foundation with which they're going to reimagine their business after they were born in the cloud. Uh, and this requires a whole new strategy. Uh, and as Accenture, we are getting a lot in cloud, but we thought that this is the moment where we bring all of that, gave him a piece together because we need a strategy for addressing, moving to cloud are embracing cloud in a holistic fashion. And that's what Accenture cloud first brings together a holistic strategy, a team that's 70,000 plus people that's coming together with rich cloud skills, but investing to tie in all the various capabilities of cloud to Delaware, that holistic strategy to our clients. So I want you to >>Delve into a little bit more about what this strategy actually entails. I mean, it's clearly about embracing change and being willing to experiment and having capabilities to innovate. Can you tell us a little bit more about what this strategy entails? >>Yeah. The reason why we say that as a need for strategy is like I said, cloud is not new. There's almost every customer client is doing something with the cloud, but all of them have taken different approaches to cloud and different boundaries to cloud. Some organizations say, I just need to consolidate my multiple data centers to a small data center footprint and move the nest to cloud. Certain other organizations say that well, I'm going to move certain workloads to cloud. Certain other organizations said, well, I'm going to build this Greenfield application or workload in cloud. Certain other said, um, I'm going to use the power of AI ML in the cloud to analyze my data and drive insights. But a cloud first strategy is all of this tied with the corporate strategy of the organization with an industry specific cloud journey to say, if in this current industry, if I were to be reborn in the cloud, would I do it in the exact same passion that I did in the past, which means that the products and services that they offer need to be the matching, how they interact with that customers and partners need to be revisited, how they bird and operate their IP systems need to be the, imagine how they unearthed the data from all of the systems under which they attract need to be liberated so that you could drive insights of cloud. >>First strategy hands is a corporate wide strategy, and it's a C-suite responsibility. It doesn't take the ownership away from the CIO or CIO, but the CIO is, and CDI was felt that it was just their problem and they were to solve it. And everyone as being a customer, now, the center of gravity is elevated to it becoming a C-suite agenda on everybody's agenda, where probably the CDI is the instrument to execute that that's a holistic cloud-first strategy >>And it, and it's a strategy, but the way you're describing it, it sounds like it's also a mindset and an approach, as you were saying, this idea of being reborn in the cloud. So now how do I think about things? How do I communicate? How do I collaborate? How do I get done? What I need to get done. Talk a little bit about how this has changed, the way you support your clients and how Accenture cloud first is changing your approach to cloud services. >>Wonderful. Um, you know, I did not color one very important aspect in my previous question, but that's exactly what you just asked me now, which is to do all of this. I talked about all of the variables, uh, an organization or an enterprise is going to go through, but the good part is they have one constant. And what is that? That is their employees, uh, because you do, the employees are able to embrace this change. If they are able to, uh, change them, says, pivot them says retool and train themselves to be able to operate in this new cloud. First one, the ability to reimagine every function of the business would be happening at speed. And cloud first approach is to do all of this at speed, because innovation is deadly proposed there, do the rate of probability on experimentation. You need to experiment a lot for any kind of experimentation. >>There's a probability of success. Organizations need to have an ability and a mechanism for them to be able to innovate faster for which they need to experiment a lot, the more the experiment and the lower cost at which they experiment is going to help them experiment a lot. And they experiment demic speed, fail fast, succeed more. And hence, they're going to be able to operate this at speed. So the cloud-first mindset is all about speed. I'm helping the clients fast track that innovation journey, and this is going to happen. Like I said, across the enterprise and every function across every department, I'm the agent of this change is going to be the employees or weapon, race, this change through new skills and new grueling and new mindset that they need to adapt to. >>So Karthik what you're describing it, it sounds so exciting. And yet for a pandemic wary workforce, that's been working remotely that may be dealing with uncertainty if for their kid's school and for so many other aspects of their life, it sounds hard. So how are you helping your clients, employees get onboard with this? And because the change management is, is often the hardest part. >>Yeah, I think it's, again, a great question. A bottle has only so much capacity. Something got to come off for something else to go in. That's what you're saying is absolutely right. And that is again, the power of cloud. The reason why cloud is such a fundamental breakthrough technology and capability for us to succeed in this era, because it helps in various forms. What we talked so far is the power of innovation that can create, but cloud can also simplify the life of the employees in an enterprise. There are several activities and tasks that people do in managing that complex infrastructure, complex ID landscape. They used to do certain jobs and activities in a very difficult underground about with cloud has simplified. And democratised a lot of these activities. So that things which had to be done in the past, like managing the complexity of the infrastructure, keeping them up all the time, managing the, um, the obsolescence of the capabilities and technologies and infrastructure, all of that could be offloaded to the cloud. >>So that the time that is available for all of these employees can be used to further innovate. Every organization is going to spend almost the same amount of money, but rather than spending activities, by looking at the rear view mirror on keeping the lights on, they're going to spend more money, more time, more energy, and spend their skills on things that are going to add value to their organization. Because you, every innovation that an enterprise can give to their end customer need not come from that enterprise. The word of platform economy is about democratising innovation. And the power of cloud is to get all of these capabilities from outside the four walls of the enterprise, >>It will add value to the organization, but I would imagine also add value to that employee's life because that employee, the employee will be more engaged in his or her job and therefore bring more excitement and energy into her, his or her day-to-day activities too. >>Absolutely. Absolutely. And this is, this is a normal evolution we would have seen everybody would have seen in their lives, that they keep moving up the value chain of what activities that, uh, gets performed buying by those individuals. And this is, um, you know, no more true than how the United States, uh, as an economy has operated where, um, this is the power of a powerhouse of innovation, where the work that's done inside the country keeps moving up to value chain. And, um, us leverage is the global economy for a lot of things that is required to power the United States and that global economic, uh, phenomenon is very proof for an enterprise as well. There are things that an enterprise needs to do them soon. There are things an employee needs to do themselves. Um, but there are things that they could leverage from the external innovation and the power of innovation that is coming from technologies like cloud. >>So at Accenture, you have long, long, deep Stan, sorry, you have deep and long-standing relationships with many cloud service providers, including AWS. How does the Accenture cloud first strategy, how does it affect your relationships with those providers? >>Yeah, we have great relationships with cloud providers like AWS. And in fact, in the cloud world, it was one of the first, um, capability that we started about years ago, uh, when we started developing these capabilities. But five years ago, we hit a very important milestone where the two organizations came together and said that we are forging a pharma partnership with joint investments to build this partnership. And we named that as a Accenture, AWS business group ABG, uh, where we co-invest and brought skills together and develop solutions. And we will continue to do that. And through that investment, we've also made several acquisitions that you would have seen in the recent times, like, uh, an invoice and gecko that we made acquisitions in in Europe. But now we're taking this to the next level. What we are saying is two cloud first and the $3 billion investment that we are bringing in, uh, through cloud-first. >>We are going to make specific investment to create unique joint solution and landing zones foundation, um, cloud packs with which clients can accelerate their innovation or their journey to cloud first. And one great example is what we are doing with Takeda, uh, billable, pharmaceutical giant, um, between we've signed a five-year partnership. And it was out in the media just a month ago or so, where we are, the two organizations are coming together. We have created a partnership as a power of three partnership, where the three organizations are jointly hoarding hats and taking responsibility for the innovation and the leadership position that Takeda wants to get to with this. We are going to simplify their operating model and organization by providing and flexibility. We're going to provide a lot more insights. Tequila has a 230 year old organization. Imagine the amount of trapped data and intelligence that is there. >>How about bringing all of that together with the power of AWS and Accenture and Takeda to drive more customer insights, um, come up with breakthrough R and D uh, accelerate clinical trials and improve the patient experience using AI ML and edge technologies. So all of these things that we will do through this partnership with joined investment from Accenture cloud first, as well as partner like AWS, so that Takeda can realize their gain. And, uh, their senior actually made a statement that five years from now, every ticket an employee will have an AI assistant. That's going to make that beginner employee move up the value chain on how they contribute and add value to the future of tequila with the AI assistant, making them even more equipped and smarter than what they could be otherwise. >>So, one last question to close this out here. What is your future vision for, for Accenture cloud first? What are we going to be talking about at next year's Accenture executive summit? Yeah, the future >>Is going to be, um, evolving, but the part that is exciting to me, and this is, uh, uh, a fundamental belief that we are entering a new era of industrial revolution from industry first, second, and third industry. The third happened probably 20 years ago with the advent of Silicon and computers and all of that stuff that happened here in the Silicon Valley. I think the fourth industrial revolution is going to be in the cross section of, uh, physical, digital and biological boundaries. And there's a great article, um, in one economic forum that people, uh, your audience can Google and read about it. Uh, but the reason why this is very, very important is we are seeing a disturbing phenomenon that over the last 10 years are seeing a Blackwing of the, um, labor productivity and innovation, which has dropped to about 2.1%. When you see that kind of phenomenon over that longer period of time, there has to be breakthrough innovation that needs to happen to come out of this barrier and get to the next, you know, base camp, as I would call it to further this productivity, um, lack that we are seeing, and that is going to happen in the intersection of the physical, digital and biological boundaries. >>And I think cloud is going to be the connective tissue between all of these three, to be able to provide that where it's the edge, especially is good to come closer to the human lives. It's going to come from cloud. Yeah. Pick totally in your mind, you can think about cloud as central, either in a private cloud, in a data center or in a public cloud, you know, everywhere. But when you think about edge, it's going to be far reaching and coming close to where we live and maybe work and very, um, get entertained and so on and so forth. And there's good to be, uh, intervention in a positive way in the field of medicine, in the field of entertainment, in the field of, um, manufacturing in the field of, um, you know, mobility. When I say mobility, human mobility, people, transportation, and so on and so forth with all of this stuff, cloud is going to be the connective tissue and the vision of cloud first is going to be, uh, you know, blowing through this big change that is going to happen. And the evolution that is going to happen where, you know, the human grace of mankind, um, our person kind of being very gender neutral in today's world. Um, go first needs to be that beacon of, uh, creating the next generation vision for enterprises to take advantage of that kind of an exciting future. And that's why it, Accenture, are we saying that there'll be change as our, as our purpose? >>I genuinely believe that cloud first is going to be the forefront of that change agenda, both for Accenture as well as for the rest of the work. >>Excellent. Let there be changed. Indeed. Thank you so much for joining us Karthik. A pleasure I'm Rebecca Knight stay tuned for more of Q3 60 fives coverage of the Accenture executive summit >>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cube virtual and our coverage of the Accenture executive summit. Part of AWS reinvent 2020. I'm your host Rebecca Knight. Today, we are talking about the power of three. And what happens when you bring together the scientific, how of a global bias biopharmaceutical powerhouse in Takeda, a leading cloud services provider in AWS, and Accenture's ability to innovate, execute, and deliver innovation. Joining me to talk about these things. We have Aaron, sorry. Arjan Beatty. He is the senior managing director and chairman of Accenture's diamonds leadership council. Welcome Arjun. Thank you, Karl hick. He is the chief digital and information officer at Takeda. >>What is your bigger, thank you, Rebecca >>And Brian Beau Han global director and head of the Accenture AWS business group at Amazon web services. Thanks so much for coming on. Thank you. So, as I said, we're talking today about this relationship between, uh, your three organizations. Carl, I want to talk with you. I know you're at the beginning of your cloud journey. What was the compelling reason? Why w why, why move to the cloud and why now? >>Yeah, no, thank you for the question. So, you know, as a biopharmaceutical leader, we're committed to bringing better health and a brighter future to our patients. We're doing that by translating science into some really innovative and life transporting therapies, but throughout, you know, we believe that there's a responsible use of technology, of data and of innovation. And those three ingredients are really key to helping us deliver on that promise. And so, you know, while I think a I'll call it, this cloud journey is already always been a part of our strategy. Um, and we've made some pretty steady progress over the last years with a number of I'll call it diverse approaches to the digital and AI. We just weren't seeing the impact at scale that we wanted to see. Um, and I think that, you know, there's a, there's a need ultimately to, you know, accelerate and broaden that shift. >>And, you know, we were commenting on this earlier, but there's, you know, it's been highlighted by a number of factors. One of those has been certainly a number of the acquisitions we've made Shire, uh, being the most pressing example, uh, but also the global pandemic, both of those highlight the need for us to move faster, um, at the speed of cloud, ultimately. Uh, and so we started thinking outside of the box because it was taking us too long and we decided to leverage the strategic partner model. Uh, and it's giving us a chance to think about our challenges very differently. We call this the power of three, uh, and ultimately our focus is singularly on our patients. I mean, they're waiting for us. We need to get there faster. It can take years. And so I think that there is a focus on innovation at a rapid speed, so we can move ultimately from treating conditions to keeping people healthy. >>So as you are embarking on this journey, what are some of the insights you want to share about, about what you're seeing so far? >>Yeah, no, it's a great question. So, I mean, look, maybe right before I highlight some of the key insights, uh, I would say that, you know, with cloud now as the, as a launchpad for innovation, you know, our vision all along has been that in less than 10 years, we want every single to kid, uh, the associate or employee to be empowered by an AI assistant. And I think that, you know, that's going to help us make faster, better decisions. That'll help us, uh, fundamentally deliver transformative therapies and better experiences to, to that ecosystem, to our patients, to physicians, to payers, et cetera, much faster than we previously thought possible. Um, and I think that technologies like cloud and edge computing together with a very powerful I'll call it data fabric is going to help us to create this, this real-time, uh, I'll call it the digital ecosystem. >>The data has to flow ultimately seamlessly between our patients and providers or partners or researchers, et cetera. Uh, and so we've been thinking about this, uh, I'll call it weekly, call up sort of this pyramid, um, that helps us describe our vision. Uh, and a lot of it has to do with ultimately modernizing the foundation, modernizing and rearchitecting, the platforms that drive the company, uh, heightening our focus on data, which means that there's an accelerated shift towards, uh, enterprise data platforms and digital products. And then ultimately, uh, uh, uh, you know, really an engine for innovation sitting at the very top. Um, and so I think with that, you know, there's a few different, I'll call it insights that, you know, are quickly kind of come zooming into focus. I would say one is this need to collaborate very differently. Um, you know, not only internally, but you know, how do we define ultimately, and build a connected digital ecosystem with the right partners and technologies externally? >>I think the second component that maybe people don't think as much about, but, you know, I find critically important is for us to find ways of really transforming our culture. We have to unlock talent and shift the culture certainly as a large biopharmaceutical very differently. And then lastly, you've touched on it already, which is, you know, innovation at the speed of cloud. How do we re-imagine that? You know, how do ideas go from getting tested in months to kind of getting tested in days? You know, how do we collaborate very differently? Uh, and so I think those are three, uh, perhaps of the larger I'll call it, uh, insights that, you know, the three of us are spending a lot of time thinking about right now. >>So Arjun, I want to bring you into this conversation a little bit. Let's, let's delve into those a bit. Talk first about the collaboration, uh, that Carl was referencing there. How, how have you seen that? It is enabling, uh, colleagues and teams to communicate differently and interact in new and different ways? Uh, both internally and externally, as Carl said, >>No, thank you for that. And, um, I've got to give call a lot of credit because as we started to think about this journey, it was clear. It was a bold ambition was, uh, something that, you know, we had all to do differently. And so the concept of the power of three that Carl has constructed has become a label for us as a way to think about what are we going to do to collectively drive this journey forward. And to me, the unique ways of collaboration means three things. The first one is that, um, what is expected is that the three parties are going to come together and it's more than just the sum of our resources. And by that, I mean that we have to bring all of ourselves, all of our collective capabilities, as an example, Amazon has amazing supply chain capabilities. They're one of the best at supply chain. >>So in addition to resources, when we have supply chain innovations, uh, that's something that they're bringing in addition to just, uh, talent and assets, similarly for Accenture, right? We do a lot, uh, in the talent space. So how do we bring our thinking as to how we apply best practices for talent to this partnership? So, um, as we think about this, so that's, that's the first one, the second one is about shared success very early on in this partnership, we started to build some foundations and actually develop seven principles that all of us would look at as the basis for this success shared success model. And we continue to hold that sort of in the forefront, as we think about this collaboration. And maybe the third thing I would say is this one team mindset. So whether it's the three of our CEOs that get together every couple of months to think about, uh, this partnership, or it is the governance model that Carl has put together, which has all three parties in the governance and every level of leadership, we always think about this as a collective group so that we can keep that front and center. >>And what I think ultimately has enabled us to do is it's allowed us to move at speed, be more flexible. And ultimately all we're looking at the target the same way, the North side, the same way, >>Brian, about you, what have you observed and what are you thinking about in terms of how this is helping teams collaborate differently? Yeah, >>Absolutely. And RJ made some, some great points there. And I think if you really think about what he's talking about, it's that, that diversity of talent, diversity of skill and viewpoint and even culture, right? And so we see that in the power of three. And then I think if we drill down into what we see at Takeda and frankly Takeda was, was really, I think, pretty visionary and on their way here, right. And taking this kind of cross-functional approach and applying it to how they operate day to day. So moving from a more functional view of the world to more of a product oriented view of the world, right? So when you think about we're going to be organized around a product or a service or a capability that we're going to provide to our customers or our patients or donors in this case, it implies a different structure all to altogether and a different way of thinking, right? >>Because now you've got technical people and business experts and marketing experts all working together in this is sort of cross collaboration. And what's great about that is it's really the only way to succeed with cloud, right? Because the old ways of thinking where you've got application people and infrastructure, people in business, people is suboptimal, right? Because we can all access this tool as these capabilities and the best way to do that. Isn't across kind of a cross collaborative way. And so this is product oriented mindset. It's a keto was already on. I think it's allowed us to move faster. >>Carl, I want to go back to this idea of unlocking talent and culture. And this is something that both Brian and Arjun have talked about too. People are an essential part of their, at the heart of your organization. How will their experience of work change and how are you helping re-imagine and reinforce a strong organizational culture, particularly at this time when so many people are working remotely. >>Yeah. It's a great question. And it's something that, you know, I think we all have to think a lot about, I mean, I think, um, you know, driving this, this color, this, this digital and data kind of capability building, uh, it takes a lot of, a lot of thinking. So, I mean, there's a few different elements in terms of how we're tackling this one is we're recognizing, and it's not just for the technology organization or for those actors that, that we're innovating with, but it's really across all of the Qaeda where we're working through ways of raising what I'll call the overall digital leaders literacy of the organization, you know, what are the, you know, what are the skills that are needed almost at a baseline level, even for a global bio-pharmaceutical company and how do we deploy, I'll call it those learning resources very broadly. >>And then secondly, I think that, you know, we're, we're very clear that there's a number of areas where there are very specialized skills that are needed. Uh, my organization is one of those. And so, you know, we're fostering ways in which, you know, we're very kind of quickly kind of creating, uh, avenues excitement for, for associates in that space. So one example specifically, as we use, you know, during these, uh, very much sort of remote, uh, sort of days, we, we use what we call global it meet days, and we set a day aside every single month and this last Friday, um, you know, we, we create during that time, it's time for personal development. Um, and we provide active seminars and training on things like, you know, robotic process automation, data analytics cloud, uh, in this last month we've been doing this for months and months now, but in his last month, more than 50% of my organization participated, and there's this huge positive shift, both in terms of access and excitement about really harnessing those new skills and being able to apply them. >>Uh, and so I think that that's, you know, one, one element that can be considered. And then thirdly, um, of course every organization has to work on how do you prioritize talent, acquisition and management and competencies that you can't rescale? I mean, there are just some new capabilities that we don't have. And so there's a large focus that I have with our executive team and our CEO and thinking through those critical roles that we need to activate in order to kind of, to, to build on this, uh, this business led cloud transformation. And lastly, probably the hardest one, but the one that I'm most jazzed about is really this focus on changing the mindsets and behaviors. Um, and I think there, you know, this is where the power of three is, is really, uh, kind of coming together nicely. I mean, we're working on things like, you know, how do we create this patient obsessed curiosity, um, and really kind of unlock innovation with a real, kind of a growth mindset. >>Uh, and the level of curiosity that's needed, not to just continue to do the same things, but to really challenge the status quo. So that's one big area of focus we're having the agility to act just faster. I mean, to worry less, I guess I would say about kind of the standard chain of command, but how do you make more speedy, more courageous decisions? And this is places where we can emulate the way that a partner like AWS works, or how do we collaborate across the number of boundaries, you know, and I think, uh, Arjun spoke eloquently to a number of partnerships that we can build. So we can break down some of these barriers and use these networks, um, whether it's within our own internal ecosystem or externally to help, to create value faster. So a lot of energy around ways of working and we'll have to check back in, but I mean, we're early in on this mindset and behavioral shift, um, but a lot of good early momentum. >>Carl you've given me a good segue to talk to Brian about innovation, because you said a lot of the things that I was the customer obsession and this idea of innovating much more quickly. Obviously now the world has its eyes on drug development, and we've all learned a lot about it, uh, in the past few months and accelerating drug development is all, uh, is of great interest to all of us. Brian, how does a transformation like this help a company's ability to become more agile and more innovative and at a quicker speed to, >>Yeah, no, absolutely. And I think some of the things that Carl talked about just now are critical to that, right? I think where sometimes folks fall short is they think, you know, we're going to roll out the technology and the is going to be the silver bullet where in fact it is the culture, it is, is the talent. And it's the focus on that. That's going to be, you know, the determinant of success. And I will say, you know, in this power of three arrangement and Carl talked a little bit about the pyramid, um, talent and culture and that change, and that kind of thinking about that has been a first-class citizen since the very beginning, right. That absolutely is critical for, for being there. Um, and so that's been, that's been key. And so we think about innovation at Amazon and AWS and Chrome mentioned some of the things that, you know, a partner like AWS brings to the table is we talk a lot about builders, right? >>So we're kind of obsessive about builders. Um, and, and we meet what we mean by that is we, we, at Amazon, we hire for builders, we cultivate builders and we like to talk to our customers about it as well. And it also implies a different mindset, right? When you're a builder, you have that, that curiosity, you have that ownership, you have that stake and whatever I'm creating, I'm going to be a co-owner of this product or this service, right. Getting back to that kind of product oriented mindset. And it's not just the technical people or the it people who are builders. It is also the business people as, as Carl talked about. Right. So when we start thinking about, um, innovation again, where we see folks kind of get into a little bit of, uh, innovation, pilot paralysis, is that you can focus on the technology, but if you're not focusing on the talent and the culture and the processes and the mechanisms, you're going to be putting out technology, but you're not going to have an organization that's ready to take it and scale it and accelerate it. >>Right. And so that's, that's been absolutely critical. So just a couple of things we've been doing with, with the Qaeda and Decatur has really been leading the way is, think about a mechanism and a process. And it's really been working backward from the customer, right? In this case, again, the patient and the donor. And that was an easy one because the key value of Decatur is to be a patient focused bio-pharmaceutical right. So that was embedded in their DNA. So that working back from that, that patient, that donor was a key part of that process. And that's really deep in our DNA as well and Accentures. And so we were able to bring that together. The other one is, is, is getting used to experimenting and even perhaps failing, right. And being able to iterate and fail fast and experiment and understanding that, you know, some decisions, what we call it at Amazon are two two-way doors, meaning you can go through that door, not like what you see and turn around and go back. And cloud really helps there because the costs of experimenting and the cost of failure is so much lower than it's ever been. You can do it much faster and the implications are so much less. So just a couple of things that we've been really driving, uh, with Decatur around innovation, that's been really critical. >>Carl, where are you already seeing signs of success? Yeah, no, it's a great question. And so we chose, you know, uh, with our focus on, on innovation to try to unleash maybe the power of data digital in, uh, in focusing on what I call sort of a nave. And so we chose our, our, our plasma derived therapy business, um, and you know, the plasma-derived therapy business unit, it develops critical life-saving therapies for patients with rare and complex diseases. Um, but what we're doing is by bringing kind of our energy together, we're focusing on creating, I'll call it state of the art digitally connected donation centers. And we're really modernizing, you know, the, the, the donor experience right now, we're trying to, uh, improve also I'll call it the overall plasma collection process. And so we've, uh, selected a number of alcohol at a very high-speed pilots that we're working through right now, specifically in this, in this area. And we're seeing really great results already. Um, and so that's, that's one specific area of focus >>Arjun. I want you to close this out here. Any ideas, any best practices advice you would have for other pharmaceutical companies that are, that are at the early stage of their cloud journey for me? Yes. >>Yeah, no, I was breaking up a bit. No, I think they, um, the key is what's sort of been great for me to see is that when people think about cloud, you know, you always think about infrastructure technology. The reality is that the cloud is really the true enabler for innovation and innovating at scale. And, and if you think about that, right, in all the components that you need, that ultimately that's where the value is for the company, right? Because yes, you're going to get some cost synergies and that's great, but the true value is in how do we transform the organization in the case of the Qaeda and the life sciences clients, right. We're trying to take a 14 year process of research and development that takes billions of dollars and compress that, right. Tremendous amounts of innovation opportunity. You think about the commercial aspect, lots of innovation can come there. The plasma derived therapy is a great example of how we're going to really innovate to change the trajectory of that business. So I think innovation is at the heart of what most organizations need to do. And the formula, the cocktail that the Qaeda has constructed with this Fuji program really has all the ingredients, um, that are required for that success. >>Great. Well, thank you so much. Arjun, Brian and Carl was really an enlightening conversation. >>Yeah, it's been fun. Thanks Rebecca. >>Thank you for tuning into the cube virtuals coverage of the Accenture executive summit from around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. Welcome everyone to the cubes of Accenture >>Executive summit here at AWS reinvent. I'm your host Rebecca Knight for this segment? We have two guests. First. We have Helen Davis. She is the senior director of cloud platform services, assistant director for it and digital for the West Midlands police. Thanks so much for coming on the show, Helen, And we also have Matthew lb. He is Accenture health and public service associate director and West Midlands police account lead. Thanks so much for coming on the show. Matthew, thank you for having us. So we are going to be talking about delivering data-driven insights to the West Midlands police force. Helen, I want to start with you. Can you tell us a little bit about the West Midlands police force? How big is the force and also what were some of the challenges that you were grappling with prior to this initiative? >>Yes, certainly. So Westerners police is the second largest police force in the UK, outside of the metropolitan police in London. Um, we have an excessive, um, 11,000 people work at Westminster police serving communities, um, through, across the Midlands region. So geographically, we're quite a big area as well, as well as, um, being population, um, density, having that as a, at a high level. Um, so the reason we sort of embarked on the data-driven insights platform and it, which was a huge change for us was for a number of reasons. Um, namely we had a lot of disparate data, um, which was spread across a range of legacy systems that were many, many years old, um, with some duplication of, um, what was being captured and no single view for offices or, um, support staff. Um, some of the access was limited. You have to be in a, in an actual police building on a desktop computer to access it. Um, other information could only reach officers on the frontline through a telephone call back to one of our enabling services where they would do a manual checkup, um, look at the information, then call the offices back, um, and tell them what they needed to know. So it was a very long laborious process and not very efficient. Um, and we certainly weren't exploiting the data that we had in a very productive way. >>So it sounds like as you're describing and an old clunky system that needed a technological, uh, reimagination, so what was the main motivation for, for doing, for making this shift? >>It was really, um, about making us more efficient and more effective in how we do how we do business. So, um, you know, certainly as a, as an it leader and sort of my operational colleagues, we recognize the benefits, um, that data analytics could bring in, uh, in a policing environment, not something that was, um, really done in the UK at time. You know, we have a lot of data, so we're very data rich and the information that we have, but we needed to turn it into information that was actionable. So that's where we started looking for, um, technology partners and, um, suppliers to help us and sort of help us really with what's the art of the possible, you know, this hasn't been done before. So what could we do in this space that's appropriate for policing >>Helen? I love that idea. What is the art of the possible, can you tell us a little bit about why you chose AWS? >>I think really, you know, as with all things and when we're procuring a partner in the public sector that, you know, there are many rules and regulations quite rightly as you would expect that to be because we're spending public money. So we have to be very, very careful and, um, it's, it's a long process and we have to be open to public scrutiny. So, um, we sort of look to everything, everything that was available as part of that process, but we recognize the benefits that tide would provide in this space because, you know, without moving to a cloud environment, we would literally be replacing something that was legacy with something that was a bit more modern. Um, that's not what we wanted to do. Our ambition was far greater than that. So I think, um, in terms of AWS, really, it was around scalability, interoperability, you know, disaster things like the disaster recovery service, the fact that we can scale up and down quickly, we call it dialing up and dialing back. Um, you know, it's it's page go. So it just sort of ticked all the boxes for us. And then we went through the full procurement process, fortunately, um, it came out on top for us. So we were, we were able to move forward, but it just sort of had everything that we were looking for in that space. >>Matthew, I want to bring you into the conversation a little bit here. How are you working with the wet with the West Midlands police, sorry, and helping them implement this cloud first journey? >>Yeah, so I guess, um, by January the West Midlands police started, um, pay for five years ago now. So, um, we set up a partnership with the force I, and you to operate operation the way that was very different to a traditional supplier relationship. Um, secretary that the data difference insights program is, is one of many that we've been working with less neutral on, um, over the last five years. Um, as having said already, um, cloud gave a number of, uh, advantages certainly from a big data perspective and the things that that enabled us today, um, I'm from an Accenture perspective that allowed us to bring in a number of the different themes that we have say cloud themes, security teams, um, interacted from a design perspective, as well as more traditional services that people would associate with the country. >>So much of this is about embracing comprehensive change to experiment, innovate, and try different things. Matthew, how, how do you help an entity like West Midlands police think differently when they are, there are these ways of doing things that people are used to, how do you help them think about what is the art of the possible, as Helen said, >>There's a few things for that, you know, what's being critical is trying to co-create solutions together. Yeah. There's no point just turning up with, um, what we think is the right answer, try and say, um, collectively work through, um, the issues that the forest are seeing the outcomes they're looking to achieve rather than simply focusing on the long list of requirements I think was critical and then being really open to working together to create the right solution. Um, rather than just, you know, trying to pick something off the shelf that maybe doesn't fit the forces requirements in the way that it should to, right. It's not always a one size fits all. Obviously, you know, today what we thought was critical is making sure that we're creating something that met the forces needs, um, in terms of the outcomes they're looking to achieve the financial envelopes that were available, um, and how we can deliver those in a, uh, iterative agile way, um, rather than spending years and years, um, working towards an outcome, um, that is going to outdate before you even get that. >>How, how are things different? What kinds of business functions and processes have been re-imagined in, in light of this change and this shift >>It's, it's actually unrecognizable now, um, in certain areas of the business as it was before. So to give you a little bit of context, when we, um, started working with essentially century AWS on the data driven insights program, it was very much around providing, um, what was called locally, a wizzy tool for our intelligence analysts to interrogate data, look at data, you know, decide whether they could do anything predictive with it. And it was very much sort of a back office function to sort of tidy things up for us and make us a bit better in that, in that area or a lot better in that area. And it was rolled out to a number of offices, a small number on the front line. Um, I'm really, it was, um, in line with a mobility strategy that we, hardware officers were getting new smartphones for the first time, um, to do sort of a lot of things on, on, um, policing apps and things like that to again, to avoid them, having to keep driving back to police stations, et cetera. >>And the pilot was so successful. Every officer now has access to this data, um, on their mobile devices. So it literally went from a handful of people in an office somewhere using it to do sort of clever whizzbang things to, um, every officer in the force, being able to access that level of data at their fingertips literally. So what they would touch we've done before is if they needed to check and address or check, uh, details of an individual, um, just as one example, they would either have to, in many cases, go back to a police station to look it up themselves on a desktop computer. Well, they would have to make a call back to, um, a centralized function and speak to an operator, relay the questions either, wait for the answer or wait for a call back with the answer when those people are doing the data interrogation manually. >>So the biggest change for us is the self-service nature of the data we now have available. So officers can do it themselves on their phone, wherever they might be. So the efficiency savings, um, from that point of view are immense. And I think just parallel to that is the quality of our data because we had a lot of data, but just because you've got a lot of data and a lot of information doesn't mean it's big data and it's valuable necessarily. Um, so again, it was having the single source of truth as we, as we call it. So you know, that when you are completing those safe searches and getting the responses back, that it is the most accurate information we hold. And also you're getting it back within minutes as opposed to, you know, half an hour, an hour or a drive back to the station. So it's making officers more efficient and it's also making them safer. The more efficient they are, the more time they have to spend, um, out with the public doing what they, you know, we all should be doing. >>And have you seen that kind of return on investment because what you were just describing with all the steps that we'd needed to be taken in prior to this to verify and address say, and those are precious seconds when someone's life is on the line in, in sort of in the course of everyday police work. >>Absolutely. Yeah, absolutely. It's difficult to put a price on it. It's difficult to quantify. Um, but all the, you know, the minutes here and that certainly add up to a significant amount of efficiency savings, and we've certainly been able to demonstrate the officers are spending less time up police stations as a result and more time out on the front line. Also they're safer because they can get information about what may or may not be and address what may or may not have occurred in an area before very, very quickly without having to wait. >>Matthew, I want to hear your observations of working so closely with this West Midlands police. Have you noticed anything about changes in its culture and its operating model in how police officers interact with one another? Have you seen any changes since this technology change, >>Um, unique about the West new misplaces, the buy-in from the top, it depend on the chief and his exact team. And Helen is the leader from an IOT perspective. Um, the entire force is bought in. So what is a significant change program? Uh, uh, not trickles three. Um, everyone in the organization, um, change is difficult. Um, and there's a lot of time effort. That's been put into bake, the technical delivery and the business change and adoption aspects around each of the projects. Um, but you can see the step change that it's making in each aspect to the organization, uh, and where that's putting West Midlands police as a leader in, um, technology I'm policing in the UK. And I think globally, >>And this is a question for both of you because Matthew, as you said, change is difficult and there is always a certain intransigence in workplaces about this is just the way we've always done things and we're used to this and don't try to get us, don't try to get us to do anything new here. It works. How do you get the buy-in that you need to, to do this kind of digital transformation? >>I think it, it would be wrong to say it was easy. Um, um, we also have to bear in mind that this was one program in a five year program. So there was a lot of change going on, um, both internally for some of our back office functions, as well as front tie, uh, frontline offices. So with DDI in particular, I think the stat change occurred when people could see what it could do for them. You know, we had lots of workshops and seminars where we all talk about, you know, big data and it's going to be great and it's data analytics and it's transformational, you know, and quite rightly people that are very busy doing a day job that not necessarily technologists in the main and, you know, are particularly interested quite rightly so in what we are not dealing with the cloud, you know? >>And it was like, yeah, okay. It's one more thing. And then when they started to see on that, on their phones and what teams could do, that's when it started to sell itself. And I think that's when we started to see, you know, to see the stack change, you know, and, and if we, if we have any issues now it's literally, you know, our help desks in meltdown. Cause everyone's like, well, we call it manage without this anymore. And I think that speaks for itself. So it doesn't happen overnight. It's sort of incremental changes and then that's a step change in attitude. And when they see it working and they see the benefits, they want to use it more. And that's how it's become fundamental to our policing by itself, really without much selling >>Matthew, Helen just made a compelling case for how to get buy in. Have you discovered any other best practices when you are trying to get everyone on board for this kind of thing? >>So we've, um, we've used a lot of the traditional techniques, things around comms and engagement. We've also used things like, um, the 30 day challenge and nudge theory around how can we gradually encourage people to use things? Um, I think there's a point where all of this around, how do we just keep it simple and keep it user centric from an end user perspective? I think DDI is a great example of where the, the technology is incredibly complex. The solution itself is, um, you know, extremely large and, um, has been very difficult to, um, get delivered. But at the heart of it is a very simple front end for the user to encourage it and take that complexity away from them. Uh, I think that's been critical through the whole piece of video. >>One final word from Helen. I want to hear, where do you go from here? What is the longterm vision? I know that this made productivity, >>Um, productivity savings equivalent to 154 full-time officers. Uh, what's next, I think really it's around, um, exploiting what we've got. Um, I use the phrase quite a lot, dialing it up, which drives my technical architects crazy, but because it's apparently not that simple, but, um, you know, we've, we've been through significant change in the last five years and we are still continuing to batch all of those changes into everyday, um, operational policing. But what we need to see now is we need to exploit and build on the investments that we've made, um, in terms of data and claims specifically, the next step really is about expanding our pool of data and our functions. Um, so that, you know, we keep getting better and better, um, at this, um, the more we do, the more data we have, the more refined we can be, the more precise we are with all of our actions. >>Um, you know, we're always being expected to, again, look after the public purse and do more for less. And I think this is certainly an and our cloud journey and cloud first by design, which is where we are now, um, is helping us to be future-proofed. So for us, it's very much an investment. And I see now that we have good at embedded in operational policing for me, this is the start of our journey, not the end. So it's really exciting to see where we can go from here. Exciting times. Indeed. Thank you so much. And Matthew for joining us, I really appreciate it. And you are watching the cube stay tuned for more of the cubes coverage of the AWS reinvent Accenture executive summit. I'm Rebecca Knight from around the globe with digital coverage, >>AWS reinvent executive summit, 2020, sponsored by Accenture and AWS. Everyone. Welcome to the cube virtual coverage of the executive summit at AWS reinvent 2020 virtual. This is the cube virtual. We can't be there in person like we are every year we have to be remote. This executive summit is with special programming supported by Accenture where the cube virtual I'm your host John for a year, we had a great panel here called uncloud first digital transformation from some experts, Stuart driver, the director of it and infrastructure and operates at lion Australia, Douglas Regan, managing director, client account lead at lion for Accenture as a deep Islam associate director application development lead for Accenture gentlemen, thanks for coming on the cube virtual that's a mouthful, all that digital, but the bottom line it's cloud transformation. This is a journey that you guys have been on together for over 10 years to be really a digital company. Now, some things have happened in the past year that kind of brings all this together. This is about the next generation organization. So I want to ask Stuart you first, if you can talk about this transformation at lion has undertaken some of the challenges and opportunities and how this year in particular has brought it together because you, you know, COVID has been the accelerant of digital transformation. Well, if you're 10 years in, I'm sure you're there. You're in the, uh, uh, on that wave right now. Take a minute to explain this transformation journey. >>Yeah, sure. So number of years back, we, we looked at kind of our infrastructure and our landscape. I'm trying to figure out where we wanted to go next. And we were very analog based, um, and stuck in the old it groove of, you know, capital refresh, um, struggling to transform, struggling to get to a digital platform and we needed to change it up so that we could, uh, become very different business to the one that we were back then. Um, obviously cloud is an accelerant to that and we had a number of initiatives that needed a platform to build on. And a cloud infrastructure was the way that we started to do that. So we went through a number of transformation programs that we didn't want to do that in the old world. We wanted to do it in a new world. So for us, it was partnering up with a, you know, great organizations that can take you on the journey and, uh, you know, start to deliver a bit by bit incremental progress, uh, to get to the, uh, I guess the promise land. >>Um, we're not, uh, not all the way there, but to where we're a long way along. And then when you get to some of the challenges like we've had this year, um, it makes all of the hard work worthwhile because you can actually change pretty quickly, um, provide capacity and, uh, and increase your environments and, you know, do the things that you need to do in a much more dynamic way than we would have been able to previously where we might've been waiting for the hardware vendors, et cetera, to deliver capacity for us this year, it's been a pretty strong year from an it perspective and delivering for the business needs, >>Forget the Douglas. I want to just real quick and redirect to you and say, you know, for all the people who said, Oh yeah, you got to jump on cloud, get in early, you know, a lot of naysayers like, well, wait till to mature a little bit. Really, if you got in early and you paying your dues, if you will taking that medicine with the cloud, you're really kind of peaking at the right time. Is that true? Is that one of the benefits that comes out of this getting in the cloud, >>John, this has been an unprecedented year, right. And, um, you know, Australia, we had to live through Bush fires and then we had covert and, and then we actually had to deliver a, um, a project I'm very know transformational product project, completely remote. And then we also had had some, some cyber challenges, which is public as well. And I don't think if we weren't moved into and enabled through the cloud would have been able to achieve that this year. It would have been much different. It would have been very difficult to do the fact that we were able to work and partner with Amazon through this year, which is unprecedented and actually come out the other end and we've delivered a brand new digital capability across the entire business. Um, it wouldn't >>Have been impossible if we could, I guess, stayed in the old world. The fact that we moved into the new Naval by the Navy allowed us to work in this unprecedented gear >>Just quick. What's your personal view on this? Because I've been saying on the Cuban reporting, necessity's the mother of all invention and the word agility has been kicked around as kind of a cliche, Oh, it'd be agile. You know, we're gonna get to Sydney. You get a minute on specifically, but from your perspective, uh, Douglas, what does that mean to you? Because there is benefits there for being agile. And >>I mean, I think as Stuart mentioned writing, and a lot of these things we try to do and, you know, typically, you know, hardware capabilities of the last to be told and, and always the only critical path to be done. You know, we really didn't have that in this case, what we were doing with our projects in our deployments, right. We were able to move quickly able to make decisions in line with the business and really get things going, right. So you, a lot of times in a traditional world, you have these inhibitors, you have these critical path, it takes weeks and months to get things done as opposed to hours and days. And it truly allowed us to, we had to VJ things, move things. And, you know, we were able to do that in this environment with AWS to support and the fact that we can kind of turn things off and on as quickly as we need it. Yeah. >>Cloud-scale is great for speed. So DECA got, Gardez get your thoughts on this cloud first mission, you know, it, you know, the dev ops worlds, they saw this early, that jumping in there, they saw the, the, the agility. Now the theme this year is modern applications with the COVID pandemic pressure, there's real business pressure to make that happen. How did you guys learn to get there fast? And what specifically did you guys do at Accenture and how did it all come together? Can you take us inside kind of how it played out? >>All right. So we started off with us and we work with lions experts and, uh, the lost knowledge that allowed reconstructive being had. Um, we then applied our journey group cloud strategy basically revolves around the seven Oz and, and, uh, you know, the deep peaking steps from our perspective, uh, assessing the current bottom, setting up the new cloud in modern. And as we go modernizing and, and migrating these applications to the cloud now, you know, one of the things that, uh, no we did not along this journey was that, you know, you can have the best plans, but bottom of that, we were dealing with, we often than not have to make changes. Uh, what a lot of agility and also work with a lot of collaboration with the, uh, Lyon team, as well as, uh, uh, AWS. I think the key thing for me was being able to really bring it all together. It's not just, uh, you know, essentially mobilize all of us. >>What were some of the learnings real quick, your journey there? >>So I think perspective the key learnings around that, you know, uh, you know, what, when we look back at, uh, the, the infrastructure that was that we were trying to migrate over to the cloud, a lot of the documentation, et cetera, was not, uh, available. We were having to, uh, figure out a lot of things on the fly. Now that really required us to have, uh, uh, people with deep expertise who could go into those environments and, and work out, uh, you know, the best ways to, to migrate the workloads to the cloud. Uh, I think, you know, the, the biggest thing for me was making Jovi had on that real SMEs across the board globally, that we could leverage across various technologies, uh, uh, and, and, and, you know, that would really work in our collaborative and agile environment would line >>Just do what I got to ask you. How did you address your approach to the cloud and what was your experience? >>Yeah, for me, it's around getting the foundations right. To start with and then building on them. Um, so, you know, you've got to have your, your process and you're going to have your, your kind of your infrastructure there and your blueprints ready. Um, AWS do a great job of that, right. Getting the foundations right. And then building upon it, and then, you know, partnering with Accenture allows you to do that very successfully. Um, I think, um, you know, the one thing that was probably surprising to us when we started down this journey and kind of, after we got a long way down, the track of looking backwards is actually how much you can just turn off. Right? So a lot of stuff that you, uh, you get left with a legacy in your environment, and when you start to work through it with the types of people that civic just mentioned, you know, the technical expertise working with the business, um, you can really rationalize your environment and, uh, um, you know, cloud is a good opportunity to do that, to drive that legacy out. >>Um, so you know, a few things there, the other thing is, um, you've got to try and figure out the benefits that you're going to get out of moving here. So there's no point just taking something that is not delivering a huge amount of value in the traditional world, moving it into the cloud, and guess what it's going to deliver the same limited amount of value. So you've got to transform it, and you've got to make sure that you build it for the future and understand exactly what you're trying to gain out of it. So again, you need a strong collaboration. You need a good partners to work with, and you need good engagement from the business as well, because the kind of, uh, you know, digital transformation, cloud transformation, isn't really an it project, I guess, fundamentally it is at the core, but it's a business project that you've got to get the whole business aligned on. You've got to make sure that your investment streams are appropriate and that you're able to understand the benefits and the value that you're going to drive back towards the business. >>Let's do it. If you don't mind me asking what was some of the obstacles encountered or learnings, um, that might've differed from the expectation we all been there, Hey, you know, we're going to change the world. Here's the sales pitch, here's the outcome. And then obviously things happen, you know, you learn legacy, okay. Let's put some containerization around that cloud native, um, all that rational. You're talking about what are, and you're going to have obstacles. That's how you learn. That's how perfection has developed. How, what obstacles did you come up with and how are they different from your expectations going in? >>Yeah, they're probably no different from other people that have gone down the same journey. If I'm totally honest, the, you know, 70 or 80% of what you do is relative music, because they're a known quantity, it's relatively modern architectures and infrastructures, and you can, you know, upgrade, migrate, move them into the cloud, whatever it is, rehost, replatform, rearchitect, whatever it is you want to do, it's the other stuff, right? It's the stuff that always gets left behind. And that's the challenge. It's, it's getting that last bit over the line and making sure that you haven't invested in the future while still carrying all of your legacy costs and complexity within your environment. So, um, to be quite honest, that's probably taken longer and, and has been more of a challenge than we thought it would be. Um, the other piece I touched on earlier on in terms of what was surprising was actually how much of your environment is actually not needed anymore. >>When you start to put a critical eye across it and understand, um, uh, ask the tough questions and start to understand exactly what, what it is you're trying to achieve. So if you ask a part of a business, do they still need this application or this service a hundred percent of the time, they'll say yes, until you start to lay out to them, okay, now I'm going to cost you this to migrate it or this, to run it in the future. And, you know, here's your ongoing costs and, you know, et cetera, et cetera. And then, uh, for a significant amount of those answers, you get a different response when you start to layer on the true value of it. So you start to flush out those hidden costs within the business, and you start to make some critical decisions as a company based on, uh, based on that. So that was a little tougher than we first thought and probably broader than we thought there was more of that than we anticipated, which actually resulted in a much cleaner environment post and post migration. Yeah. >>Well, expression, if it moves automated, you know, it's kind of a joke on government, how they want to tax everything, you know, you want to automate, that's a key thing in cloud, and you've got to discover those opportunities to create value, uh, Stuart and Siddique. Mainly if you can weigh in on this love to know the percentage of total cloud that you have now, versus when you started, because as you start to uncover whether it's by design for purpose, or you discover opportunities to innovate, like you guys have, I'm sure it kind of, you took on some territory inside Lyon, what percentage of cloud now versus >>Yeah. At the start, it was minimal, right. You know, close to zero, right. Single and single digits. Right. It was mainly SAS environments that we had, uh, sitting in cloud when we, uh, when we started, um, Doug mentioned earlier a really significant transformation project that we've undertaken recently gone live on a multi-year one. Um, you know, that's all stood up on AWS and is a significant portion of our environment, um, in terms of what we can move to cloud. Uh, we're probably at about 80 or 90% now. And the balanced bit is, um, legacy infrastructure that is just gonna retire as we go through the cycle rather than migrate to the cloud. Um, so we are significantly cloud-based and, uh, you know, we're reaping the benefits of it in a year, like 2020, and makes you glad that you did all of the hard yards in the previous years when you start business challenges, trying out as, >>So do you get any common reaction to the cloud percentage penetration? >>Sorry, I didn't, I didn't catch that, but I, all I was going to say was, I think it's like the typical 80 20 rule, right? We, we, we worked really hard in the, you know, I think 2018, 19 to get 80% off the, uh, application onto the cloud. And over the last year is the 20% that we have been migrating. And Stuart said, right. A lot of it is also, that's going to be your diet. And I think our next big step is going to be obviously, you know, the icing on the cake, which is to decommission all of these apps as well. Right. So, you know, to get the real benefits out of, uh, out of the whole conservation program from a, uh, from a reduction of CapEx, OPEX perspective, >>Douglas and Stuart, can you guys talk about the decision around the clouds because you guys have had success with AWS? Why AWS how's that decision made? Can you guys give some insight into some of those things? >>I can, I can start, start off. I think back when the decision was made and it was, it was a while back, um, you know, there was some clear advantages of moving relay, Ws, a lot of alignment with some of the significant projects and, uh, the trend, that particular one big transformation project that we've alluded to as well. Um, you know, we needed some, um, some very robust and, um, just future proof and, and proven technology. And AWS gave that to us. We needed a lot of those blueprints to help us move down the path. We didn't want to reinvent everything. So, um, you know, having a lot of that legwork done for us and AWS gives you that, right. And particularly when you partner up with, uh, with a company like Accenture as well, you get combinations of technology and the, the skills and the knowledge to, to move you forward in that direction side. Um, you know, for us, it was a, uh, uh, it was a decision based on, you know, best of breed, um, you know, looking forward and, and trying to predict the future needs and, and, and kind of the environmental that we might need. Um, and, you know, partnering up with organizations that can then take you on the journey >>Just to build on that. So obviously, you know, lines like an antivirus, but, you know, we knew it was a very good choice given the, um, >>Uh, skills and the capability that we had, as well as the assets and tools we had to get the most out of an AWS. And obviously our CEO globally just made an announcement about a huge investment that we're making in cloud. Um, but you know, we've, we've worked very well with AWS. We've done some joint workshops and joint investments, um, some joint POC. So yeah, w we have a very good working relationship, AWS, and I think, um, one incident to reflect upon whether it's cyber it's and again, where we actually jointly, you know, dove in with, um, with Amazon and some of their security experts and our experts. And we're able to actually work through that with mine quite successful. So, um, you know, really good behaviors as an organization, but also really good capabilities. >>Yeah. As you guys, your essential cloud outcomes, research shown, it's the cycle of innovation with the cloud, that's creating a lot of benefits, knowing what you guys know now, looking back certainly COVID has impacted a lot of people kind of going through the same process, knowing what you guys know now, would you advocate people to jump on this transformation journey? If so, how, and what tweaks they make, which changes, what would you advise? >>I might take that one to start with. Um, I hate to think where we would have been when, uh, COVID kicked off here in Australia and, you know, we were all sent home, literally were at work on the Friday, and then over the weekend. And then Monday, we were told not to come back into the office and all of a sudden, um, our capacity in terms of remote access and I quadrupled, or more four, five X, what we had on the Friday we needed on the Monday. And we were able to stand that up during the day Monday into Tuesday, because we were cloud-based and, uh, you know, we just spun up your instances and, uh, you know, sort of our licensing, et cetera. And, and we had all of our people working remotely, um, within, uh, you know, effectively one business day. Um, I know peers of mine in other organizations and industries that are relying on kind of a traditional wise and getting hardware, et cetera, that were weeks and months before they could get the right hardware to be able to deliver to their user base. >>So, um, you know, one example where you're able to scale and, uh, uh, get, uh, get value out of this platform beyond probably what was anticipated at the time you talk about, um, you know, less this, the, and all of these kinds of things. And you can also think of a few scenarios, but real world ones where you're getting your business back up and running in that period of time is, is just phenomenal. There's other stuff, right? There's these programs that we've rolled out, you do your sizing, um, and in the traditional world, you would just go out and buy more servers than you need. And, you know, probably never realize the full value of those, you know, the capability of those servers over the life cycle of them. Whereas, you know, in a cloud world, you put in what you think is right. And if it's not right, you pump it up a little bit when, when all of your metrics and so on telling you that you need to bump it up and conversely Scarlett down at the same rate. So for us with the types of challenges and programs and, uh, uh, and just business need, that's come at as this year, uh, we wouldn't have been able to do it without a strong cloud base, uh, to, uh, to move forward with >>Yeah, Douglas, one of the things that I talked to, a lot of people on the right side of history who have been on the right wave with cloud, with the pandemic, and they're happy, they're like, and they're humble. Like, well, we're just lucky, you know, luck is preparation meets opportunity. And this is really about you guys getting in early and being prepared and readiness. This is kind of important as people realize, then you gotta be ready. I mean, it's not just, you don't get lucky by being in the right place, the right time. And there were a lot of companies were on the wrong side of history here who might get washed away. This is a second >>I think, to echo and kind of build on what Stewart said. I think that the reason that we've had success and I guess the momentum is we, we didn't just do it in isolation within it and technology. It was actually linked to broader business changes, you know, creating basically a digital platform for the entire business, moving the business, where are they going to be able to come back stronger after COVID, when they're actually set up for growth, um, and actually allows, you know, a line new achievements, growth objectives, and also its ambitions as far as what he wants to do, uh, with growth in whatever they may do as acquiring other companies and moving into different markets and launching new product. So we've actually done it in a way that there's, you know, real and direct business benefit, uh, that actually enables line to grow >>General. I really appreciate you coming. I have one final question. If you can wrap up here, uh, Stuart and Douglas, you don't mind waiting, and what's the priorities for the future. What's next for lion and a century >>Christmas holidays, I'll start Christmas holidays. And I spent a third year and then a, and then a reset, obviously, right? So, um, you know, it's, it's figuring out, uh, transform what we've already transformed, if that makes sense. So God, a huge proportion of our services sitting in the cloud. Um, but we know we're not done even with the stuff that is in there. We need to take those next steps. We need more and more automation and orchestration. We need to, um, our environment, there's more future growth. We need to be able to work with the business and understand what's coming at them so that we can, um, you know, build that into, into our environment. So again, it's really transformation on top of transformation is the way that I'll describe it. And it's really an open book, right? Once you get it in and you've got the capabilities and the evolving tool sets that AWS continue to bring to the market base, um, you know, working with the partners to, to figure out how we unlock that value, um, you know, drive our costs down our efficiency, uh, all of those kind of, you know, standard metrics. >>Um, but you know, we're looking for the next things to transform and show value back out to our customer base, um, that, uh, that we continue to, you know, sell our products to and work with and understand how we can better meet their needs. Yeah, I think just to echo that, I think it's really leveraging this and then digital capability they have and getting the most out of that investment. And then I think it's also moving to, >>Uh, and adopting more new ways of working as far as, you know, the state of the business. Um, it's getting up the speed of the market is changing. So being able to launch and do things quickly and also, um, competitive and efficient operating costs, uh, now that they're in the cloud, right. So I think it's really leveraging the most out of a platform and then, you know, being efficient in launching things. So putting the, with the business, >>Cedric, any word from you on your priorities by UC this year and folding. >>Yeah. So, uh, just going to say like e-learning squares, right for me were around, you know, just journey. This is a journey to the cloud, right. And, uh, you know, as well dug into sort of Saturday, it's getting all, you know, different parts of the organization along the journey business to ID to your, uh, product windows, et cetera. Right. And it takes time with this stuff, but, uh, uh, you know, you gotta get started on it and, you know, once we, once we finish off, uh, it's the realization of the benefits now that, you know, I'm looking forward? I think for, from Alliance perspective, it's, it is, uh, you know, once we migrate all the workloads to the cloud, it is leveraging, uh, all stack drive. And as I think Stewart said earlier, uh, with, uh, you know, the latest and greatest stuff that AWS it's basically working to see how we can really, uh, achieve more better operational excellence, uh, from a, uh, from a cloud perspective. >>Well, Stewart, thanks for coming on with a century and sharing your environment and what's going on and your journey you're on the right wave. Did the work you were in that it's all coming together with faster, congratulations for your success, and really appreciate Douglas with Steve for coming on as well from Accenture. Thank you for coming on. Thanks, John. Okay. Just the cubes coverage of executive summit at AWS reinvent. This is where all the thought leaders share their best practices, their journeys, and of course, special programming with the center and the cube. I'm Sean ferry, your host, thanks for watching From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cube virtuals coverage of the Accenture executive summit. Part of AWS reinvent 2020. I'm your host Rebecca Knight. We are talking today about reinventing the energy data platform. We have two guests joining us. First. We have Johan Krebbers. He is the GM digital emerging technologies and VP of it. Innovation at shell. Thank you so much for coming on the show. Johan you're welcome. And next we have Liz Dennett. She is the lead solution architect for O S D U on AWS. Thank you so much, Liz. You'll be. So I want to start our conversation by talking about OSD. You like so many great innovations. It started with a problem Johan. What was the problem you were trying to solve at shell? >>Yeah, the ethical back a couple of years, we started summer 2017, where we had a meeting with the deg, the gas exploration in shell, and the main problem they had. Of course, they got lots of lots of data, but are unable to find the right data. They need to work from once the day, this was scattered in is scattered my boss kind of Emirates all over the place and turned them into real, probably tried to solve is how that person working exploration could find their proper date, not just a day of loss of date. You really needed that we did probably talked about is summer 2017. We said, okay. The only way ABC is moving forward is to start pulling that data into a single data platform. And that, that was at the time that we called it as the, you, the subsurface data universe in there was about the shell name was so in, in January, 2018, we started a project with Amazon to start grating a freaking that building, that Stu environment that the, that universe, so that single data level to put all your exploration and Wells data into that single environment that was intent and every cent, um, already in March of that same year, we said, well, from Michele point of view, we will be far better off if we could make this an industry solution and not just a shelf solution, because Shelby, Shelby, if you can make this industry solution, but people are developing applications for it. >>It also is far better than for shell to say we haven't shell special solution because we don't make money out of how we start a day that we can make money out of, if you have access to the data, we can explore the data. So storing the data we should do as efficiently possibly can. So in March, we reached out to about eight or nine other large, uh, I gas operators, like the economics, like the totals, like the chefs of this world and say, Hey, we inshallah doing this. Do you want to join this effort? And to our surprise, they all said, yes. And then in September, 2018, we had our kickoff meeting with your open group where we said, we said, okay, if you want to work together, lots of other companies, we also need to look at, okay, how, how we organize that, or is that if you started working with lots of large companies, you need to have some legal framework around some framework around it. So that's why we went to the open group and said, okay, let's, let's form the ODU forum as we call it the time. So it's September, 2080, where I did a Galleria in Houston, but the kick off meeting for the OT four with about 10 members at the time. So there's just over two years ago, we started an exercise for me called ODU, kicked it off. Uh, and so that's really then we'll be coming from and how we got there. Also >>The origin story. Um, well, so what digging a little deeper there? What were some of the things you were trying to achieve with the OSD? >>Well, a couple of things we've tried to achieve with OSU, um, first is really separating data from applications. And what is the, what is the biggest problem we have in the subsurface space that the data and applications are all interlinked or tied together. And if you have them and a new company coming along and say, I have this new application and has access to the data that is not possible because the data often interlinked with the application. So the first thing we did is really breaking the link between the application, the data as those levels, the first thing we did, secondly, put all the data to a single data platform, take the silos out what was happening in the subsurface space. And they got all the data in what we call silos in small little islands out there. So we're trying to do is first break the link to great, great. >>They put the data in a single data bathroom, and a third part who does standard layer. On top of that, it's an API layer on top of the, a platform. So we could create an ecosystem out of companies to start developing soft applications on top of dev data platform across you might have a data platform, but you're only successful. If you have a rich ecosystem of people start developing applications on top of that. And then you can explore today, like small companies, last company, university, you name it, we're getting after create an ecosystem out here. So the three things, whereas was first break the link between application data, just break it and put data at the center and also make sure that data, this data structure would not be managed by one company. It would only be met. It will be managed the data structures by the OT forum. Secondly, then the data of single data platform certainly has an API layer on top and then create an ecosystem. Really go for people, say, please start developing applications because now you have access to the data. I've got the data no longer linked to somebody whose application was all freely available for an API layer. That was, that was all September, 2018, more or less. >>And to bring you in here a little bit, can you talk a little bit about some of the imperatives from the AWS standpoint in terms of what you were trying to achieve with this? Yeah, absolutely. And this whole thing is Johan said started with a challenge that was really brought out at shell. The challenges that geo-scientists spend up to 70% of their time looking for data, I'm a geologist I've spent more than 70% of my time trying to find data in these silos. And from there, instead of just figuring out how we could address that one problem, we worked together to really understand the root cause of these challenges and working backwards from that use case OSU and OSU on AWS has really enabled customers to create solutions that span, not just this in particular problem, but can really scale to be inclusive of the entire energy chain and deliver value from these use cases to the energy industry and beyond. Thank you, Lee, uh, Johann. So talk a little bit about Accenture's cloud first approach and how it has, uh, helped shell work faster and better with speed. >>Well, of course, access a cloud first approach only works together in an Amazon environment, AWS environment. So we really look at, at, at, at Accenture and others altogether helping shell in this space. Now the combination of the two is what we're really looking at, uh, where access of course can be, this is not a student who that environment operates, support knowledge to an environment. And of course, Amazon would be doing that to today's environment that underpinning, uh, services, et cetera. So, uh, we would expect a combination, a lot of goods when we started rolling out and put in production, the old you are three and bubble because we are anus. Then when the release feed comes to the market in Q1 next year of ODU, when he started going to Audi production inside shell, but as the first release, which is ready for prime time production across an enterprise will be released one just before Christmas, last year when he's still in may of this year. But release three is the first release we want to use for full scale production deployment inside shell, and also all the operators around the world. And there is what Amazon, sorry. Um, extensive can play a role in the ongoing, in the, in deployment building up, but also support environment. >>So one of the other things that we talk a lot about here on the cube is sustainability. And this is a big imperative at so many organizations around the world in particular energy companies. How does this move to OSD you, uh, help organizations become, how is this a greener solution for companies? >>Well, firstly make it, it's a great solution because you start making a much more efficient use of your resources, which is, which is already an important one. The second thing they're doing is also, we started with ODU in the oil and gas space with the expert development space. We've grown, uh OTU but in our strategy of growth, OSU now also do an alternative energy sociology. We'll all start supporting next year. Things like solar farms, wind farms, uh, the, the dermatomal environment hydration. So it becomes an and, and an open energy data platform, not just for the, for the, I want to get into steam that's for new industry, any type of energy industry. So our focus is to create, bring that data of all those various energy data sources together into a single data platform. You're going to use AI and other technology on top of that to exploit the data, to meet again in a single data platform. >>Liz, I want to ask you about security because security is, is, is such a big concern when it comes to how secure is the data on OSD you, um, actually, can I talk, can I do a follow up on the sustainability talking? Oh, absolutely. By all means. I mean, I want to interject though security is absolutely our top priority. I don't mean to move away from that, but with sustainability, in addition to the benefits of the OSU data platform, when a company moves from on-prem to the cloud, they're also able to leverage the benefits of scale. Now, AWS is committed to running our business in the most environmentally friendly way possible. And our scale allows us to achieve higher resource utilization and energy efficiency than a typical on-prem data center. Now, a recent study by four 51 research found that AWS is infrastructure is 3.6 times more energy efficient than the median of surveyed enterprise data centers. Two thirds of that advantage is due to higher server utilization and a more energy efficient server population. But when you factor in the carbon intensity of consumed electricity and renewable energy purchases, four 51 found that AWS performs the same task with an 88% lower carbon footprint. Now that's just another way that AWS and OSU are working to support our customers is they seek to better understand their workflows and make their legacy businesses less carbon intensive. >>That's that's those are those statistics are incredible. Do you want to talk a little bit now about security? Absolutely. And security will always be AWS is top priority. In fact, AWS has been architected to be the most flexible and secure cloud computing environment available today. Our core infrastructure is built to satisfy. There are the security requirements for the military global banks and other high sensitivity organizations. And in fact, AWS uses the same secure hardware and software to build and operate each of our regions. So that customers benefit from the only commercial cloud that's had hits service offerings and associated supply chain vetted and deemed secure enough for top secret workloads. That's backed by a deep set of cloud security tools with more than 200 security compliance and governmental service and key features as well as an ecosystem of partners like Accenture, that can really help our customers to make sure that their environments for their data meet and or exceed their security requirements. Johann, I want you to talk a little bit about how OSD you can be used today. Does it only handle subsurface data >>And today it's hundreds of servers or Wells data. We got to add to that production around the middle of next year. That means that the whole upstate business. So we've got, if you look at MC, obviously this goes from exploration all the way to production. You've been at the into to a single data platform. So production will be added the round Q3 of next year. Then it principal, we have a difficult, the elder data that single environment, and we want to extended them to other data sources or energy sources like solar farms, wheat farms, uh, hydrogen hydro at San Francisco. We want to add a whore or a list of other day. >>And he saw a student and B all the data together into a single data club. So we move from an fallen guest, a data platform to an energy data platform. That's really what our objective is because the whole industry we've looked at, I've looked at our company companies all moving in that same direction of quantity, of course are very strong at all, I guess, but also increase the, got into all the other energy sources like, like solar, like wind, like, like the hydrogen, et cetera. So we, we move exactly the same method that, that, that the whole OSU can really support at home. And as a spectrum of energy sources, of course, >>And Liz and Johan. I want you to close us out here by just giving us a look into your crystal balls and talking about the five and 10 year plan for OSD. You we'll start with you, Liz. What do you, what do you see as the future holding for this platform? Um, honestly, the incredibly cool thing about working at AWS is you never know where the innovation and the journey is going to take you. I personally am looking forward to work with our customers, wherever their OSU journeys, take them, whether it's enabling new energy solutions or continuing to expand, to support use cases throughout the energy value chain and beyond, but really looking forward to continuing to partner as we innovate to slay tomorrow's challenges. >>Yeah. First, nobody can look that far ahead, any more nowadays, especially 10 years mean now, who knows what happens in 10 years, but if you look what our whole objective is that really in the next five years owes you will become the key backbone for energy companies for storing your data. You are efficient intelligence and optimize the whole supply energy supply chain in this world out there. >>Rubbers Liz Dennett. Thank you so much for coming on the cube virtual, >>Thank you, >>Rebecca nights, stay tuned for more of our coverage of the Accenture executive summit >>Around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cubes coverage of the Accenture executive summit. Part of AWS reinvent. I'm your host Rebecca Knight today we're welcoming back to Kubila. We have Kishor Dirk. He is the Accenture senior managing director cloud first global services lead. Welcome back to the show >>Kishore. Thank you very much. >>Nice to meet again. And, uh, Tristin moral horse set. He is the managing director, Accenture cloud first North American growth. Welcome back to YouTube. >>Great to be back in. Great to see you again, Rebecca. >>Exactly. Even in this virtual format, it is good to see your faces. Um, today we're going to be talking about my nav and green cloud advisor >>Capability. Kishor I want to start with you. So my NAB is a platform that is really celebrating its first year in existence. Uh, November, 2019 is when Accenture introduced it. Uh, but it's, it has new relevance in light of this global pandemic that we are all enduring and suffering through. Tell us a little bit about the miner platform, what it is. >>Sure, Rebecca, you know, we lost it and now 2019 and, uh, you know, it is a cloud platform to help our clients navigate the complexity of cloud and cloud decisions and to make it faster and obviously innovate in the cloud, uh, you know, with the increased relevance and all the, especially over the last few months with the impact of COVID crisis and exhibition of digital transformation, you know, we are seeing the transformation of the acceleration to cloud much faster. This platform that you're talking about has enabled hundred and 40 clients globally across different industries. You identify the right cloud solution, navigate the complexity, provide a cloud specific solution simulate for our clients to meet the strategy business needs and the clients are loving it. >>I want to go to you now trust and tell us a little bit about how my nav works and how it helps companies make good cloud choices. >>Yeah. So Rebecca we've talked about cloud is, is more than just infrastructure and that's what mine app tries to solve for. It really looks at a variety of variables, including infrastructure operating model and fundamentally what clients business outcomes, um, uh, our clients are, are looking for and, and identify as the optimal solution for what they need. And we design this to accelerate and we mentioned the pandemic. One of the big focus now is to accelerate. And so we worked through a three-step process. The first is scanning and assessing our client's infrastructure, their data landscape, their application. Second, we use our automated artificial intelligence engine to interact with. We have a wide variety and library of, uh, collective plot expertise. And we look to recommend what is the enterprise architecture and solution. And then third, before we aligned with our clients, we look to simulate and test this scaled up model. And the simulation gives our clients a wait to see what cloud is going to look like, feel like and how it's going to transform their business before they go there. >>Tell us a little bit about that in real life. Now as a company, so many of people are working remotely having to collaborate, uh, not in real life. How is that helping them right now? >>So, um, the, the pandemic has put a tremendous strain on systems, uh, because of the demand on those systems. And so we talk about resiliency. We also now need to collaborate across data across people. Um, I think all of us are calling from a variety of different places where our last year we were all at the cube itself. Um, and, and cloud technologies such as teams, zoom that we're we're leveraging now has fundamentally accelerated and clients are looking to onboard this for their capabilities. They're trying to accelerate their journey. They realize that now the cloud is what is going to become important for them to differentiate. Once we come out of the pandemic and the ability to collaborate with their employees, their partners, and their clients through these systems is becoming a true business differentiator for our clients. >>Sure. I want to talk with you now about my NABS multiple capabilities, um, and helping clients design and navigate their cloud journeys. Tell us a little bit about the green cloud advisor capability and its significance, particularly as so many companies are thinking more deeply and thoughtfully about sustainability. >>Yes. So since the launch of my NAB, we continue to enhance capabilities for our clients. One of the significant, uh, capabilities that we have enabled is the brain trust advisor today. You know, Rebecca, a lot of the businesses are more environmentally aware and are expanding efforts to decrease power consumption, uh, and obviously carbon emissions and, uh, and run a sustainable operations across every aspect of the enterprise. Uh, as a result, you're seeing an increasing trend in adoption of energy, efficient infrastructure in the global market. And one of the things that we did, a lot of research we found out is that there's an ability to influence our client's carbon footprint through a better cloud solution. And that's what we entered by brings to us, uh, in, in terms of a lot of the client connotation that you're seeing in Europe, North America and others, lot of our clients are accelerating to a green cloud strategy to unlock beta financial, societal and environmental benefit, uh, through obviously cloud-based circular, operational and sustainable products and services. That is something that, uh, we are enhancing my now and we are having active client discussions at this point of time. >>So Tristan, tell us a little bit about how this capability helps clients make greener. >>Yeah. Um, well, let's start about the investments from the cloud providers in renewable and sustainable energy. Um, they have most of the hyperscalers today, um, have been investing significantly on data centers that are run or renewable energy, some incredibly creative constructs on the how to do that. And sustainability is therefore a key, um, key item of importance for the hyperscalers and also for our clients who now are looking for sustainable energy. And it turns out this marriage is now possible. I can, we marry the, the green capabilities of the cloud providers with a sustainability agenda of our clients. And so what we look into way the mine EF works is it looks at industry benchmarks and evaluates our current clients, um, capabilities and carpet footprint leveraging their existing data centers. We then look to model from an end-to-end perspective, how the, their journey to the cloud leveraging sustainable and, um, and data centers with renewable energy. We look at how their solution will look like and, and quantify carbon tax credits, um, improve a green index score and provide quantifiable, um, green cloud capabilities and measurable outcomes to our clients, shareholders, stakeholders, clients, and customers, um, and our green plot advisors, sustainability solutions already been implemented at three clients. And in many cases in two cases has helped them reduce the carbon footprint by up to 400% through migration from their existing data center to green club. Very, very important. Yeah, >>That is remarkable. Now tell us a little bit about the kinds of clients. Is this, is this more interesting to clients in Europe? Would you say that it's catching on in the United States where we're at? What is the breakdown that you're seeing right now? >>Sustainability is becoming such a global agenda and we're seeing our clients, um, uh, tie this and put this at board level, um, uh, agenda and requirements across the globe. Um, Europe has specific constraints around data sovereignty, right, where they need their data in country, but from a green, a sustainability agenda, we see clients across all our markets, North America, Europe, and our growth markets adopt this. And we have seen case studies in all three markets >>Kisha. I want to bring you back into the conversation. Talk a little bit about how mine up ties into Accenture's cloud first strategy, your Accenture's CEO, Julie Sweet has talked about post COVID leadership requiring every business to become a cloud first business. Tell us a little bit about how this ethos is in Accenture and how you're sort of looking outward with it too. >>So Rebecca mine is the launch pad, uh, to a cloud first transformation for our clients. Uh, Accenture, see you, uh, Julie Sweet, uh, shared the Accenture cloud first and our substantial investment demonstrate our commitment and is delivering data value for our clients when they need it the most. And with the district transformation requiring cloud at scale, you know, we're seeing that in the post COVID leadership, it requires that every business should become a cloud business. And my nap helps them get there by evaluating the cloud landscape, navigating the complexity, modeling architecting and simulating an optimal cloud solution for our clients. And as Justin was sharing a greener cloud, Tristan, talk a little >>Bit more about some of the real life use cases in terms of what are we, what are clients seeing? What are the results? >>Yes, thank you, Rebecca. I would say two key things right around my now the first is the iterative process. Clients don't want to wait, um, until they get started, they want to get started and see what their journey is going to look like. And the second is fundamental acceleration, dependent make, as we talked about, has accelerated the need to move to cloud very quickly. And my nav is there to do that. So how do we do that? First is generating the business cases. Clients need to know in many cases that they have a business case by business case, we talk about the financial benefits, as well as the business outcomes, the green green cloud impact sustainability impacts with minus we can build initial recommendations using a basic understanding of their environment and benchmarks in weeks versus months with indicative value savings in the millions of dollars arranges. >>So for example, very recently, we worked with a global oil and gas company, and in only two weeks, we're able to provide an indicative savings for $27 million over five years. This enabled the client to get started, knowing that there is a business case benefit and then iterate on it. And this iteration is, I would say the second point that is particularly important with my nav that we've seen in bank, the clients, which is, um, any journey starts with an understanding of what is the application landscape and what are we trying to do with those, these initial assessments that used to take six to eight weeks are now taking anywhere from two to four weeks. So we're seeing a 40 to 50% reduction in the initial assessment, which gets clients started in their journey. And then finally we've had discussions with all of the hyperscalers to help partner with Accenture and leverage mine after prepared their detailed business case module as they're going to clients. And as they're accelerating the client's journey, so real results, real acceleration. And is there a journey? Do I have a business case and furthermore accelerating the journey once we are by giving the ability to work in an iterative approach, >>It sounds as though that the company that clients and and employees are sort of saying, this is an amazing time savings look at what I can do here in, in so much in a condensed amount of time, but in terms of getting everyone on board, one of the things we talked about last time we met, uh, Tristin was just how much, uh, how one of the obstacles is getting people to sign on and the new technologies and new platforms. Those are often the obstacles and struggles that companies face. Have you found that at all? Or what is sort of the feedback that you're getting from? >>Yeah. Sorry. Yes. We clearly, there are always obstacles to a con journey. If there weren't obstacles, all our clients would be already fully in the cloud. What man I gives the ability is to navigate through those, to start quickly. And then as we identify obstacles, we can simulate what things are going to look like. We can continue with certain parts of the journey while we deal with that obstacle. And it's a fundamental accelerator. Whereas in the past one, obstacle would prevent a class from starting. We can now start to address the obstacles one at a time while continuing and accelerating the contrary. That is the fundamental difference. Kishor I want to give you the final word here. Tell us a little bit about what is next for Accenture might have and what we'll be discussing next year at the Accenture executive summit >>Sort of echo, we are continuously evolving with our client needs and reinventing, reinventing for the future. For my advisor, our plan is to help our clients reduce carbon footprint and again, migrate to a green cloud. Uh, and additionally, we're looking at, you know, two capabilities, uh, which include sovereign cloud advisor, uh, with clients, especially in, in Europe and others are under pressure to meet stringent data norms that Kristen was talking about. And the sovereign cloud advisor health organization to create an architecture cloud architecture that complies with the green. Uh, I would say the data sound-bitey norms that is out there. The other element is around data to cloud. We are seeing massive migration, uh, for, uh, for a lot of the data to cloud. And there's a lot of migration hurdles that come within that. Uh, we have expanded mine app to support assessment capabilities, uh, for, uh, assessing applications, infrastructure, but also covering the entire state, including data and the code level to determine the right cloud solution. So we are, we are pushing the boundaries on what might have can do with mine. And we have created the ability to take the guesswork out of cloud, navigate the complexity. We are rolling risks costs, and we are achieving clients strategy, business objectives, while building a sustainable lots with being cloud, >>Any platform that can take some of the guesswork out of the future. I'm I'm on board with. Thank you so much, Kristin and Kishore. This has been a great conversation. Thank you, Rebecca. Thank you, Rebecca. Stay tuned for more of the cubes coverage of the Accenture executive summit. I'm Rebecca Knight. >>Yeah, Yeah.
SUMMARY :
It's the cube with digital coverage Welcome to cube three 60 fives coverage of the Accenture executive summit. Thanks for having me here. impact of the COVID-19 pandemic has been, what are you hearing from clients? you know, various facets, you know, um, first and foremost, to this reasonably okay, and are, you know, launching to So you just talked about the widening gap. all the changes the pandemic has brought to them. in the cloud that we are going to see. Can you tell us a little bit more about what this strategy entails? all of the systems under which they attract need to be liberated so that you could drive now, the center of gravity is elevated to it becoming a C-suite agenda on everybody's And it, and it's a strategy, but the way you're describing it, it sounds like it's also a mindset and an approach, the employees are able to embrace this change. across every department, I'm the agent of this change is going to be the employees or weapon, And because the change management is, is often the hardest And that is again, the power of cloud. And the power of cloud is to get all of these capabilities from outside that employee, the employee will be more engaged in his or her job and therefore And this is, um, you know, no more true than how So at Accenture, you have long, long, deep Stan, sorry, And in fact, in the cloud world, it was one of the first, um, And one great example is what we are doing with Takeda, uh, billable, to drive more customer insights, um, come up with breakthrough Yeah, the future to the next, you know, base camp, as I would call it to further this productivity, And the evolution that is going to happen where, you know, the human grace of mankind, I genuinely believe that cloud first is going to be the forefront of that change Thank you so much for joining us Karthik. It's the cube with digital coverage And what happens when you bring together the scientific, And Brian Beau Han global director and head of the Accenture AWS business group at Amazon Um, and I think that, you know, there's a, there's a need ultimately to, And, you know, we were commenting on this earlier, but there's, you know, it's been highlighted by a number of factors. And I think that, you know, that's going to help us make faster, better decisions. Um, and so I think with that, you know, there's a few different, it, uh, insights that, you know, the three of us are spending a lot of time thinking about right now. So Arjun, I want to bring you into this conversation a little bit. uh, something that, you know, we had all to do differently. in the governance and every level of leadership, we always think about this as a collective the same way, the North side, the same way, And I think if you really think about what he's talking about, Because the old ways of thinking where you've got application people and infrastructure, How will their experience of work change and how are you helping re-imagine and And it's something that, you know, I think we all have to think a lot about, I mean, And then secondly, I think that, you know, we're, we're very clear that there's a number of areas where there are Uh, and so I think that that's, you know, one, one element that can be considered. or how do we collaborate across the number of boundaries, you know, and I think, uh, Arjun spoke eloquently the customer obsession and this idea of innovating much more quickly. of the things that, you know, a partner like AWS brings to the table is we talk a lot about builders, And it's not just the technical people or the it people who are you know, some decisions, what we call it at Amazon are two two-way doors, meaning you can go through that door, And so we chose, you know, uh, with our focus on, I want you to close this out here. sort of been great for me to see is that when people think about cloud, you know, Well, thank you so much. Yeah, it's been fun. It's the cube with digital coverage of How big is the force and also what were some of the challenges that you were grappling with Um, so the reason we sort of embarked um, you know, certainly as a, as an it leader and sort of my operational colleagues, What is the art of the possible, can you tell us a little bit about why you the public sector that, you know, there are many rules and regulations quite rightly as you would expect Matthew, I want to bring you into the conversation a little bit here. to bring in a number of the different themes that we have say cloud themes, security teams, um, So much of this is about embracing comprehensive change to experiment, the outcomes they're looking to achieve rather than simply focusing on the long list of requirements I think was critical So to give you a little bit of context, when we, um, started And the pilot was so successful. And I think just parallel to that is the quality of our data because we had a lot of data, And have you seen that kind of return on investment because what you were just describing with all the steps Um, but all the, you know, the minutes here and that certainly add up Have you seen any changes And Helen is the leader from an IOT perspective. And this is a question for both of you because Matthew, as you said, change is difficult and there is always a certain You know, we had lots of workshops and seminars where we all talk about, you know, see, you know, to see the stack change, you know, and, and if we, if we have any issues now it's literally, when you are trying to get everyone on board for this kind of thing? the 30 day challenge and nudge theory around how can we gradually encourage people to use things? I want to hear, where do you go from here? not that simple, but, um, you know, we've, we've been through significant change in the last And I see now that we have good at embedded in operational So I want to ask Stuart you first, if you can talk about this transformation and stuck in the old it groove of, you know, capital refresh, um, of the challenges like we've had this year, um, it makes all of the hard work worthwhile because you can actually I want to just real quick and redirect to you and say, you know, for all the people who said, Oh yeah, And, um, you know, Australia, we had to live through Bush fires by the Navy allowed us to work in this unprecedented gear Because I've been saying on the Cuban reporting, necessity's the mother of all and always the only critical path to be done. And what specifically did you guys do at Accenture and how did it all come applications to the cloud now, you know, one of the things that, uh, no we did not along uh, uh, and, and, and, you know, that would really work in our collaborative and agile environment How did you address your approach to the cloud and what was your experience? And then building upon it, and then, you know, partnering with Accenture allows because the kind of, uh, you know, digital transformation, cloud transformation, learnings, um, that might've differed from the expectation we all been there, Hey, you know, It's, it's getting that last bit over the line and making sure that you haven't invested in the future hundred percent of the time, they'll say yes, until you start to lay out to them, okay, you know, you want to automate, that's a key thing in cloud, and you've got to discover those opportunities to create value, Um, you know, that's all stood up on AWS and is a significant portion of And I think our next big step is going to be obviously, So, um, you know, having a lot of that legwork done for us and AWS gives you that, So obviously, you know, lines like an antivirus, but, you know, we knew it was a very good So, um, you know, really good behaviors as an a lot of people kind of going through the same process, knowing what you guys know now, And, and we had all of our people working remotely, um, within, uh, you know, effectively one business day. the time you talk about, um, you know, less this, the, and all of these kinds of things. And this is really about you guys getting It was actually linked to broader business changes, you know, creating basically a digital platform Stuart and Douglas, you don't mind waiting, and what's the priorities for the future. to figure out how we unlock that value, um, you know, drive our costs down our efficiency, our customer base, um, that, uh, that we continue to, you know, sell our products to and work with Uh, and adopting more new ways of working as far as, you know, the state of the business. And it takes time with this stuff, but, uh, uh, you know, Did the work you were in that it's all coming together with faster, What was the problem you were trying to solve at shell? And that, that was at the time that we called it as the, make money out of how we start a day that we can make money out of, if you have access to the data, we can explore the data. What were some of the things you were trying to achieve with the OSD? So the first thing we did is really breaking the link between the application, I've got the data no longer linked to somebody whose application was all freely available for an API layer. And to bring you in here a little bit, can you talk a little bit about some of the imperatives from the a lot of goods when we started rolling out and put in production, the old you are three and bubble because we are So one of the other things that we talk a lot about here on the cube is sustainability. of that to exploit the data, to meet again in a single data platform. purchases, four 51 found that AWS performs the same task with an So that customers benefit from the only commercial cloud that's had hits service offerings and You've been at the into to a single data platform. And he saw a student and B all the data together into a single data club. Um, honestly, the incredibly cool thing about working at AWS is you who knows what happens in 10 years, but if you look what our whole objective is that really in the next five Thank you so much for coming on the cube virtual, It's the cube with digital coverage of He is the Accenture senior managing director cloud first global services Thank you very much. He is the managing director, Great to see you again, Rebecca. Even in this virtual format, it is good to see your faces. So my NAB is a platform that is really celebrating to make it faster and obviously innovate in the cloud, uh, you know, with the increased relevance I want to go to you now trust and tell us a little bit about how my nav works and how it helps One of the big focus now is to accelerate. having to collaborate, uh, not in real life. They realize that now the cloud is what is going to become important for them to differentiate. about the green cloud advisor capability and its significance, particularly as so many companies And one of the things that we did, a lot of research we found out is that there's an ability to influence or renewable energy, some incredibly creative constructs on the how to do that. What is the breakdown that you're seeing right now? And we have seen case studies in all I want to bring you back into the conversation. And with the district transformation requiring cloud at scale, you know, we're seeing that in And the second is fundamental acceleration, dependent make, as we talked about, has accelerated the need This enabled the client to get started, knowing that there is a business is getting people to sign on and the new technologies and new platforms. What man I gives the ability is to navigate through those, to start quickly. And the sovereign cloud advisor health organization to create an Any platform that can take some of the guesswork out of the future.
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Eric Herzog, IBM & Sam Werner, IBM | CUBE Conversation, October 2020
(upbeat music) >> Announcer: From theCUBE Studios in Palo Alto and Boston, connecting with thought leaders all around the world. This is a CUBE conversation. >> Hey, welcome back everybody. Jeff Frick here with the CUBE, coming to you from our Palo Alto studios today for a CUBE conversation. we've got a couple of a CUBE alumni veterans who've been on a lot of times. They've got some exciting announcements to tell us today, so we're excited to jump into it, So let's go. First we're joined by Eric Herzog. He's the CMO and VP worldwide storage channels for IBM Storage, made his time on theCUBE Eric, great to see you. >> Great, thanks very much for having us today. >> Jeff: Absolutely. And joining him, I think all the way from North Carolina, Sam Werner, the VP of, and offering manager business line executive storage for IBM. Sam, great to see you as well. >> Great to be here, thank you. >> Absolutely. So let's jump into it. So Sam you're in North Carolina, I think that's where the Red Hat people are. You guys have Red Hat, a lot of conversations about containers, containers are going nuts. We know containers are going nuts and it was Docker and then Kubernetes. And really a lot of traction. Wonder if you can reflect on, on what you see from your point of view and how that impacts what you guys are working on. >> Yeah, you know, it's interesting. We talk, everybody hears about containers constantly. Obviously it's a hot part of digital transformation. What's interesting about it though is most of those initiatives are being driven out of business lines. I spend a lot of time with the people who do infrastructure management, particularly the storage teams, the teams that have to support all of that data in the data center. And they're struggling to be honest with you. These initiatives are coming at them, from application developers and they're being asked to figure out how to deliver the same level of SLAs the same level of performance, governance, security recovery times, availability. And it's a scramble for them to be quite honest they're trying to figure out how to automate their storage. They're trying to figure out how to leverage the investments they've made as they go through a digital transformation and keep in mind, a lot of these initiatives are accelerating right now because of this global pandemic we're living through. I don't know that the strategy's necessarily changed, but there's been an acceleration. So all of a sudden these storage people kind of trying to get up to speed or being thrown right into the mix. So we're working directly with them. You'll see, in some of our announcements, we're helping them, you know, get on that journey and provide the infrastructure their teams need. >> And a lot of this is driven by multicloud and hybrid cloud, which we're seeing, you know, a really aggressive move to before it was kind of this rush to public cloud. And that everybody figured out, "Well maybe public cloud isn't necessarily right for everything." And it's kind of this horses for courses, if you will, with multicloud and hybrid cloud, another kind of complexity thrown into the storage mix that you guys have to deal with. >> Yeah, and that's another big challenge. Now in the early days of cloud, people were lifting and shifting applications trying to get lower capex. And they were also starting to deploy DevOps, in the public cloud in order to improve agility. And what they found is there were a lot of challenges with that, where they thought lifting and shifting an application will lower their capital costs the TCO actually went up significantly. Where they started building new applications in the cloud. They found they were becoming trapped there and they couldn't get the connectivity they needed back into their core applications. So now we're at this point where they're trying to really, transform the rest of it and they're using containers, to modernize the rest of the infrastructure and complete the digital transformation. They want to get into a hybrid cloud environment. What we found is, enterprises get two and a half X more value out of the IT when they use a hybrid multicloud infrastructure model versus an all public cloud model. So what they're trying to figure out is how to piece those different components together. So you need a software-driven storage infrastructure that gives you the flexibility, to deploy in a common way and automate in a common way, both in a public cloud but on premises and give you that flexibility. And that's what we're working on at IBM and with our colleagues at Red Hat. >> So Eric, you've been in the business a long time and you know, it's amazing as it just continues to evolve, continues to evolve this kind of unsexy thing under the covers called storage, which is so foundational. And now as data has become, you know, maybe a liability 'cause I have to buy a bunch of storage. Now it is the core asset of the company. And in fact a lot of valuations on a lot of companies is based on its value, that's data and what they can do. So clearly you've got a couple of aces in the hole you always do. So tell us what you guys are up to at IBM to take advantage of the opportunity. >> Well, what we're doing is we are launching, a number of solutions for various workloads and applications built with a strong container element. For example, a number of solutions about modern data protection cyber resiliency. In fact, we announced last year almost a year ago actually it's only a year ago last week, Sam and I were on stage, and one of our developers did a demo of us protecting data in a container environment. So now we're extending that beyond what we showed a year ago. We have other solutions that involve what we do with AI big data and analytic applications, that are in a container environment. What if I told you, instead of having to replicate and duplicate and have another set of storage right with the OpenShift Container configuration, that you could connect to an existing external exabyte class data lake. So that not only could your container apps get to it, but the existing apps, whether they'll be bare-metal or virtualized, all of them could get to the same data lake. Wow, that's a concept saving time, saving money. One pool of storage that'll work for all those environments. And now that containers are being deployed in production, that's something we're announcing as well. So we've got a lot of announcements today across the board. Most of which are container and some of which are not, for example, LTO-9, the latest high performance and high capacity tape. We're announcing some solutions around there. But the bulk of what we're announcing today, is really on what IBM is doing to continue to be the leader in container storage support. >> And it's great, 'cause you talked about a couple of very specific applications that we hear about all the time. One obviously on the big data and analytics side, you know, as that continues to do, to kind of chase history of honor of ultimately getting the right information to the right people at the right time so they can make the right decision. And the other piece you talked about was business continuity and data replication, and to bring people back. And one of the hot topics we've talked to a lot of people about now is kind of this shift in a security threat around ransomware. And the fact that these guys are a little bit more sophisticated and will actually go after your backup before they let you know that they're into your primary storage. So these are two, really important market areas that we could see continue activity, as all the people that we talk to every day. You must be seeing the same thing. >> Absolutely we are indeed. You know, containers are the wave. I'm a native California and I'm coming to you from Silicon Valley and you don't fight the wave, you ride it. So at IBM we're doing that. We've been the leader in container storage. We, as you know, way back when we invented the hard drive, which is the foundation of almost this entire storage industry and we were responsible for that. So we're making sure that as container is the coming wave that we are riding that in and doing the right things for our customers, for our channel partners that support those customers, whether they be existing customers, and obviously, with this move to containers, is going to be some people searching for probably a new vendor. And that's something that's going to go right into our wheelhouse because of the things we're doing. And some of our capabilities, for example, with our FlashSystems, with our Spectrum Virtualize, we're actually going to be able to support CSI snapshots not only for IBM Storage, but our Spectrum Virtualize products supports over 500 different arrays, most of which aren't ours. So if you got that old EMC VNX2 or that HPE, 3PAR or aNimble or all kinds of other storage, if you need CSI snapshot support, you can get it from IBM, with our Spectrum Virtualize software that runs on our FlashSystems, which of course cuts capex and opex, in a heterogeneous environment, but gives them that advanced container support that they don't get, because they're on older product from, you know, another vendor. We're making sure that we can pull our storage and even our competitor storage into the world of containers and do it in the right way for the end user. >> That's great. Sam, I want to go back to you and talk about the relationship with the Red Hat. I think it was about a year ago, I don't have my notes in front of me, when IBM purchased Red Hat. Clearly you guys have been working very closely together. What does that mean for you? You've been in the business for a long time. You've been at IBM for a long time, to have a partner you know, kind of embed with you, with Red Hat and bringing some of their capabilities into your portfolio. >> It's been an incredible experience, and I always say my friends at Red Hat because we spend so much time together. We're looking at now, leveraging a community that's really on the front edge of this movement to containers. They bring that, along with their experience around storage and containers, along with the years and years of enterprise class storage delivery that we have in the IBM Storage portfolio. And we're bringing those pieces together. And this is a case of truly one plus one equals three. And you know, an example you'll see in this announcement is the integration of our data protection portfolio with their container native storage. We allow you to in any environment, take a snapshot of that data. You know, this move towards modern data protection is all about a movement to doing data protection in a different way which is about leveraging snapshots, taking instant copies of data that are application aware, allowing you to reuse and mount that data for different purposes, be able to protect yourself from ransomware. Our data protection portfolio has industry leading ransomware protection and detection in it. So we'll actually detect it before it becomes a problem. We're taking that, industry leading data protection software and we are integrating it into Red Hat, Container Native Storage, giving you the ability to solve one of the biggest challenges in this digital transformation which is backing up your data. Now that you're moving towards, stateful containers and persistent storage. So that's one area we're collaborating. We're working on ensuring that our storage arrays, that Eric was talking about, that they integrate tightly with OpenShift and that they also work again with, OpenShift Container Storage, the Cloud Native Storage portfolio from, Red Hat. So we're bringing these pieces together. And on top of that, we're doing some really, interesting things with licensing. We allow you to consume the Red Hat Storage portfolio along with the IBM software-defined Storage portfolio under a single license. And you can deploy the different pieces you need, under one single license. So you get this ultimate investment protection and ability to deploy anywhere. So we're, I think we're adding a lot of value for our customers and helping them on this journey. >> Yeah Eric, I wonder if you could share your perspective on multicloud management. I know that's a big piece of what you guys are behind and it's a big piece of kind of the real world as we've kind of gotten through the hype and now we're into production, and it is a multicloud world and it is, you got to manage this stuff it's all over the place. I wonder if you could speak to kind of how that challenge you know, factors into your design decisions and how you guys are about, you know, kind of the future. >> Well we've done this in a couple of ways in things that are coming out in this launch. First of all, IBM has produced with a container-centric model, what they call the Multicloud Manager. It's the IBM Cloud Pak for multicloud management. That product is designed to manage multiple clouds not just the IBM Cloud, but Amazon, Azure, et cetera. What we've done is taken our Spectrum Protect Plus and we've integrated it into the multicloud manager. So what that means, to save time, to save money and make it easier to use, when the customer is in the multicloud manager, they can actually select Spectrum Protect Plus, launch it and then start to protect data. So that's one thing we've done in this launch. The other thing we've done is integrate the capability of IBM Spectrum Virtualize, running in a FlashSystem to also take the capability of supporting OCP, the OpenShift Container Platform in a Clustered environment. So what we can do there, is on-premise, if there really was an earthquake in Silicon Valley right now, that OpenShift is sitting on a server. The servers just got crushed by the roof when it caved in. So you want to make sure you've got disaster recovery. So what we can do is take that OpenShift Container Platform Cluster, we can support it with our Spectrum Virtualize software running on our FlashSystem, just like we can do heterogeneous storage that's not ours, in this case, we're doing it with Red Hat. And then what we can do is to provide disaster recovery and business continuity to different cloud vendors not just to IBM Cloud, but to several cloud vendors. We can give them the capability of replicating and protecting that Cluster to a cloud configuration. So if there really was an earthquake, they could then go to the cloud, they could recover that Red Hat Cluster, to a different data center and run it on-prem. So we're not only doing the integration with a multicloud manager, which is multicloud-centric allowing ease of use with our Spectrum Protect Plus, but incase of a really tough situation of fire in a data center, earthquake, hurricane, whatever, the Red Hat OpenShift Cluster can be replicated out to a cloud, with our Spectrum Virtualize Software. So in most, in both cases, multicloud examples because in the first one of course the multicloud manager is designed and does support multiple clouds. In the second example, we support multiple clouds where our Spectrum Virtualize for public clouds software so you can take that OpenShift Cluster replicate it and not just deal with one cloud vendor but with several. So showing that multicloud management is important and then leverage that in this launch with a very strong element of container centricity. >> Right >> Yeah, I just want to add, you know, and I'm glad you brought that up Eric, this whole multicloud capability with, the Spectrum Virtualize. And I could see the same for our Spectrum Scale Family, which is our storage infrastructure for AI and big data. We actually, in this announcement have containerized the client making it very simple to deploy in Kubernetes Cluster. But one of the really special things about Spectrum Scale is it's active file management. This allows you to build out a file system not only on-premises for your, Kubernetes Cluster but you can actually extend that to a public cloud and it automatically will extend the file system. If you were to go into a public cloud marketplace which it's available in more than one, you can go in there click deploy, for example, in AWS Marketplace, click deploy it will deploy your Spectrum Scale Cluster. You've now extended your file system from on-prem into the cloud. If you need to access any of that data, you can access it and it will automatically cash you on locally and we'll manage all the file access for you. >> Yeah, it's an interesting kind of paradox between, you know, kind of the complexity of what's going on in the back end, but really trying to deliver simplicity on the front end. Again, this ultimate goal of getting the right data to the right person at the right time. You just had a blog post Eric recently, that you talked about every piece of data isn't equal. And I think it's really highlighted in this conversation we just had about recovery and how you prioritize and how you, you know, think about, your data because you know, the relative value of any particular piece might be highly variable, which should drive the way that you treated in your system. So I wonder if you can speak a little bit, you know, to helping people think about data in the right way. As you know, they both have all their operational data which they've always had, but now they've got all this unstructured data that's coming in like crazy and all data isn't created equal, as you said. And if there is an earthquake or there is a ransomware attack, you need to be smart about what you have available to bring back quickly. And maybe what's not quite so important. >> Well, I think the key thing, let me go to, you know a modern data protection term. These are two very technical terms was, one is the recovery time. How long does it take you to get that data back? And the second one is the recovery point, at what point in time, are you recovering the data from? And the reason those are critical, is when you look at your datasets, whether you replicate, you snap, you do a backup. The key thing you've got to figure out is what is my recovery time? How long is it going to take me? What's my recovery point. Obviously in certain industries you want to recover as rapidly as possible. And you also want to have the absolute most recent data. So then once you know what it takes you to do that, okay from an RPO and an RTO perspective, recovery point objective, recovery time objective. Once you know that, then you need to look at your datasets and look at what does it take to run the company if there really was a fire and your data center was destroyed. So you take a look at those datasets, you see what are the ones that I need to recover first, to keep the company up and rolling. So let's take an example, the sales database or the support database. I would say those are pretty critical to almost any company, whether you'd be a high-tech company, whether you'd be a furniture company, whether you'd be a delivery company. However, there also is probably a database of assets. For example, IBM is a big company. We have buildings all over, well, guess what? We don't lease a chair or a table or a whiteboard. We buy them. Those are physical assets that the company has to pay, you know, do write downs on and all this other stuff, they need to track it. If we close a building, we need to move the desk to another building. Like even if we leasing a building now, the furniture is ours, right? So does an asset database need to be recovered instantaneously? Probably not. So we should focus on another thing. So let's say on a bank. Banks are both online and brick and mortar. I happened to be a Wells Fargo person. So guess what? There's Wells Fargo banks, two of them in the city I'm in, okay? So, the assets of the money, in this case now, I don't think the brick and mortar of the building of Wells Fargo or their desks in there but now you're talking financial assets or their high velocity trading apps. Those things need to be recovered almost instantaneously. And that's what you need to do when you're looking at datasets, is figure out what's critical to the business to keep it up and rolling, what's the next most critical. And you do it in basically the way you would tear anything. What's the most important thing, what's the next most important thing. It doesn't matter how you approach your job, how you used to approach school, what are the classes I have to get an A and what classes can I not get an A and depending on what your major was, all that sort of stuff, you're setting priorities, right? And the dataset, since data is the most critical asset of any company, whether it's a Global Fortune 500 or whether it's Herzog Cigar Store, all of those assets, that data is the most valuable. So you've got to make sure, recover what you need as rapidly as you need it. But you can't recover all of it. You just, there's just no way to do that. So that's why you really ranked the importance of the data to use sameware, with malware and ransomware. If you have a malware or ransomware attack, certain data you need to recover as soon as you can. So if there, for example, as a, in fact there was one Jeff, here in Silicon Valley as well. You've probably read about the University of California San Francisco, ended up having to pay over a million dollars of ransom because some of the data related to COVID research University of California, San Francisco, it was the health care center for the University of California in Northern California. They are working on COVID and guess what? The stuff was held for ransom. They had no choice, but to pay them. And they really did pay, this is around end of June, of this year. So, okay, you don't really want to do that. >> Jeff: Right >> So you need to look at everything from malware and ransomware, the importance of the data. And that's how you figure this stuff out, whether be in a container environment, a traditional environment or virtualized environment. And that's why data protection is so important. And with this launch, not only are we doing the data protection we've been doing for years, but now taking it to the heart of the new wave, which is the wave of containers. >> Yeah, let me add just quickly on that Eric. So think about those different cases you talked about. You're probably going to want for your mission critically. You're going to want snapshots of that data that can be recovered near instantaneously. And then, for some of your data, you might decide you want to store it out in cloud. And with Spectrum Protect, we just announced our ability to now store data out in Google cloud. In addition to, we already supported AWS Azure IBM Cloud, in various on-prem object stores. So we already provided that capability. And then we're in this announcement talking about LTL-9. And you got to also be smart about which data do you need to keep, according to regulation for long periods of time, or is it just important to archive? You're not going to beat the economics nor the safety of storing data out on tape. But like Eric said, if all of your data is out on tape and you have an event, you're not going to be able to restore it quickly enough at least the mission critical things. And so those are the things that need to be in snapshot. And that's one of the main things we're announcing here for Kubernetes environments is the ability to quickly snapshot application aware backups, of your mission critical data in your Kubernetes environments. It can very quickly to be recovered. >> That's good. So I'll give you the last word then we're going to sign off, we are out of time, but I do want to get this in it's 2020, if I didn't ask the COVID question, I would be in big trouble. So, you know, you've all seen the memes and the jokes about really COVID being an accelerant to digital transformation, not necessarily change, but certainly a huge accelerant. I mean, you guys have a, I'm sure a product roadmap that's baked pretty far and advanced, but I wonder if you can speak to, you know, from your perspective, as COVID has accelerated digital transformation you guys are so foundational to executing that, you know, kind of what is it done in terms of what you're seeing with your customers, you know, kind of the demand and how you're seeing this kind of validation as to an accelerant to move to these better types of architectures? Let's start with you Sam. >> Yeah, you know I, and I think i said this, but I mean the strategy really hasn't changed for the enterprises, but of course it is accelerating it. And I see storage teams more quickly getting into trouble, trying to solve some of these challenges. So we're working closely with them. They're looking for more automation. They have less people in the data center on-premises. They're looking to do more automation simplify the management of the environment. We're doing a lot around Ansible to help them with that. We're accelerating our roadmaps around that sort of integration and automation. They're looking for better visibility into their environments. So we've made a lot of investments around our storage insights SaaS platform, that allows them to get complete visibility into their data center and not just in their data center. We also give them visibility to the stores they're deploying in the cloud. So we're making it easier for them to monitor and manage and automate their storage infrastructure. And then of course, if you look at everything we're doing in this announcement, it's about enabling our software and our storage infrastructure to integrate directly into these new Kubernetes, initiatives. That way as this digital transformation accelerates and application developers are demanding more and more Kubernetes capabilities. They're able to deliver the same SLAs and the same level of security and the same level of governance, that their customers expect from them, but in this new world. So that's what we're doing. If you look at our announcement, you'll see that across, across the sets of capabilities that we're delivering here. >> Eric, we'll give you the last word, and then we're going to go to Eric Cigar Shop, as soon as this is over. (laughs) >> So it's clearly all about storage made simple, in a Kubernetes environment, in a container environment, whether it's block storage, file storage, whether it be object storage and IBM's goal is to offer ever increasing sophisticated services for the enterprise at the same time, make it easier and easier to use and to consume. If you go back to the old days, the storage admins manage X amount of gigabytes, maybe terabytes. Now the same admin is managing 10 petabytes of data. So the data explosion is real across all environments, container environments, even old bare-metal. And of course the not quite so new anymore virtualized environments. The admins need to manage that more and more easily and automated point and click. Use AI based automated tiering. For example, we have with our Easy Tier technology, that automatically moves data when it's hot to the fastest tier. And when it's not as hot, it's cool, it pushes down to a slower tier, but it's all automated. You point and you click. Let's take our migration capabilities. We built it into our software. I buy a new array, I need to migrate the data. You point, you click, and we automatic transparent migration in the background on the fly without taking the servers or the storage down. And we always favor the application workload. So if the application workload is heavy at certain times a day, we slow the migration. At night for sake of argument, If it's a company that is not truly 24 by seven, you know, heavily 24 by seven, and at night, it slows down, we accelerate the migration. All about automation. We've done it with Ansible, here in this launch, we've done it with additional integration with other platforms. So our Spectrum Scale for example, can use the OpenShift management framework to configure and to grow our Spectrum Scale or elastic storage system clusters. We've done it, in this case with our Spectrum Protect Plus, as you saw integration into the multicloud manager. So for us, it's storage made simple, incredibly new features all the time, but at the same time we do that, make sure that it's easier and easier to use. And in some cases like with Ansible, not even the real storage people, but God forbid, that DevOps guy messes with a storage and loses that data, wow. So by, if you're using something like Ansible and that Ansible framework, we make sure that essentially the DevOps guy, the test guy, the analytics guy, basically doesn't lose the data and screw up the storage. And that's a big, big issue. So all about storage made simple, in the right way with incredible enterprise features that essentially we make easy and easy to use. We're trying to make everything essentially like your iPhone, that easy to use. That's the goal. And with a lot less storage admins in the world then there has been an incredible storage growth every single year. You'd better make it easy for the same person to manage all that storage. 'Cause it's not shrinking. It is, someone who's sitting at 50 petabytes today, is 150 petabytes the next year and five years from now, they'll be sitting on an exabyte of production data, and they're not going to hire tons of admins. It's going to be the same two or four people that were doing the work. Now they got to manage an exabyte, which is why this storage made simplest is such a strong effort for us with integration, with the Open, with the Kubernetes frameworks or done with OpenShift, heck, even what we used to do in the old days with vCenter Ops from VMware, VASA, VAAI, all those old VMware tools, we made sure tight integration, easy to use, easy to manage, but sophisticated features to go with that. Simplicity is really about how you manage storage. It's not about making your storage dumb. People want smarter and smarter storage. Do you make it smarter, but you make it just easy to use at the same time. >> Right. >> Well, great summary. And I don't think I could do a better job. So I think we'll just leave it right there. So congratulations to both of you and the teams for these announcement after a whole lot of hard work and sweat went in, over the last little while and continued success. And thanks for the, check in, always great to see you. >> Thank you. We love being on theCUBE as always. >> All right, thanks again. All right, he's Eric, he was Sam, I'm I'm Jeff, you're watching theCUBE. We'll see you next time, thanks for watching. (upbeat music)
SUMMARY :
leaders all around the world. coming to you from our Great, thanks very Sam, great to see you as well. on what you see from your point of view the teams that have to that you guys have to deal with. and complete the digital transformation. So tell us what you guys are up to at IBM that you could connect to an existing And the other piece you talked and I'm coming to you to have a partner you know, and ability to deploy anywhere. of what you guys are behind and make it easier to use, And I could see the same for and how you prioritize that the company has to pay, So you need to look at and you have an event, to executing that, you know, of security and the same Eric, we'll give you the last word, And of course the not quite so new anymore So congratulations to both of you We love being on theCUBE as always. We'll see you next time,
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ThoughtSpot Keynote
>>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 Volante. 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 cohosts from ThoughtSpot first chief data strategy officer, the ThoughtSpot is Cindy Hausen. Cindy 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. Cindy 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. Cindy. Great to see you welcome to the show. Thank you, Dave. Nice to join you virtually. Now our second cohost and friend of the cube is ThoughtSpot CEO, sedition air. Hello. Sudheesh how are you doing today? I am validating. It's good to talk to you again. That's great to see you. Thanks so much for being here now Sateesh 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. >>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. Um, look, since we have all been, you know, cooped up in our homes, I know that the vendors like us, we have amped up know sort of effort to reach out to you with invites for events like this. So we are getting very 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. Then this is going to be used. Number two, we want to put you in touch with industry leaders and thought leaders, generally good people that you want to hang around with long after this event is over. >>And number three, has we planned through this? You know, we are living through these difficult times. You want an event to be this event, to be more of an uplifting and inspiring event. Now, the challenge is how do you do that with the team being change agents? Because teens can, as much as we romanticize it, it is not one of those uplifting things that everyone wants to do, or like through the VA. I think of it changes sort of like if you've ever done bungee jumping and it's like standing on the edges waiting to make that one more step, uh, 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, most businesses, it is somewhat scary. >>Change becomes all the more difficult, ultimately change requires courage, courage. 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 they feel like I don't have the skills. Sometimes they've may feel that I'm, 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, that are people in the company who are going to have 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 the silo of people with the answers, and there is a silo of people with the questions. And there is gap. This sort of silos are standing in the way of making that necessary change that we all 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 the domino of the positive changes that are necessarily the group of people that we are brought in. The four people, including Cindy, 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. >>So we're going to take a hard pivot now and go from football to Ternopil 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, the additional thousands, getting cancer and 20,000 years before the ground around there and 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. Isn't 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, Cindy, 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 parameterized reports on premises, data, warehouses, or not even that operational reports at best one enterprise, nice 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 cost 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 a leader, a data and analytics leader, what is 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 being a 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. None of this. Oh, well, I didn't invent that. I'm not going to look at that. There's still proud of that ownership, but it's collaborating to get to a better place faster. And people feel empowered to present new ideas, 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 double monetized, not just for people, how are users or analysts, but really at the of impact what we like to call the new decision makers or really the front line 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 lockstep 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's hard coding of 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 Pinboard 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 use 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 thoughts about 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, or Azure synapse or Google big query, they do not. >>They re 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. It's 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 years ago. So let's talk about the real world impact of culture. And if you read any of my books or used any of the maturity models out there, whether the Gardner it score that I worked on, or the data warehousing Institute also has the 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, basing 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 us federal government said, well, you can't turn them off. >>He said, we'll extend that even beyond the mandated guidelines and facing a slow down in the business because of the tough economy, he 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 with them 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 Sisyphus. 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 with them, what is 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 seventies or eighties for the teachers, teachers, you ask them about data. They'll say we don't, we don't need that. I care about the student. So if you can use data to help a student perform better, that is with them. 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 in bed, 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 and 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 Masa, Pharaoh, 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. >>Very happy to be here and, uh, looking forward to, uh, to talking to all of you today. So as we look to move organizations to a data-driven, uh, capability into the future, there is a lot that needs to be done on the data side, but also how did it connect and enable different business teams and technology teams into the future. As we look across, uh, 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, 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 on to google.com or you go on to being, you gone to Yahoo and you search for what you want search to find an answer ThoughtSpot for us, it's 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 action needed 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 the journey to modernize our larger ecosystem as a whole. That includes modernizing our underlying data warehouses, our technology or our Elequil environments. And as we move that we've actually picked to our cloud providers going to AWS and GCP. We've also adopted snowflake to really drive into organize our information and our data then drive these new solutions and capabilities forward. So the portion of us though, is culture. So how do we engage with the business teams and bring the, the, the it teams together to really hit the drive, these holistic end to end solution, the 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 does this is maybe 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's really then enables the business to act quickly and take advantage of opportunities as they come in based upon industries, based upon markets, as upon products, solutions or partnerships into the future. These are really some of the keys that, uh, that become crucial as you move forward, right, uh, into this, uh, 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. And these, 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, those capabilities. And those solutions forward as we go through this journey, uh, boasted both of 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 has only a celebrating. 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 our customers want, what our customers need and how do we then surface them with our information, with our data, with our platform, 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 the current business lines, but how do you actually use your information, your data, to actually better support your customers and to support your business there's important, your employees, your operations teams, and so forth, and really creating that full integration in that ecosystem is really when he talked to get large dividends from his investments into the future. But that being said, uh, I hope you enjoyed the segment on how to become and how to drive a data driven organization. And I'm looking forward to talking to you again soon. Thank you, >>Tom. That was great. Thanks so much. Now I'm going to have to brag on you for a second as a change agent. You've come in this rusted. And how long have you been at Western union? >>Uh, well in nine months. So just, uh, just started this year, but, uh, there'd be some great opportunities and great changes and we were 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, Schneider electric, but even going back to Sam's clubs. Gustavo. Welcome. >>So hi everyone. My name is Gustavo Canton and thank you so much, Cindy, for the intro, as you mentioned, doing transformations is a high effort, high reward situation. I have empowerment transformations and I have less 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 do 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 nontraditional 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 into what is happening, 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 is great to be, you know, stay in tune and have the skillset and the Koresh. But for me personally, to be honest, to have this courage is not about Nadina afraid. You're always afraid when you're making big changes in your 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. What I do it thinking about the mission of how do I make change for the bigger, eh, you know, workforce? So the bigger, good, despite the fact that this might have a perhaps implication. So my own self interest in my career, right? Because you have to have that courage sometimes to make choices that are not well seeing politically speaking, what 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 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 add cultural issues, politics, and lack of alignment, those are the top four. But the interesting thing is that as Cindy has mentioned, these topic about culture is sexually gaining, gaining more and more traction. And in 2018, there was a story from HBR and he wants 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 in set us state, eh, deadline to say, Hey, in two years, we're going to make this happen. Why do we need to do, to empower and enable this change engines 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 think the transformations most recently, as Cindy 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 having successful while working 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 their 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 to in a, in a way that is super fast, the second area, and this is specifically to implementation of AI is 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 function. So the leaders look at technology, they look at it from the prison of the prior auth success criteria for the traditional BIS. And that's not going to work again, your opportunity here is that you need to really find what success look like. In my case, I want the user experience of our workforce to be the same as this experience you have at home is a very simple concept. And so we need to think about how do we gain that user experience with this augmented analytics tools and then work backwards to have the right talent processes and technology to enable that. And finally, and obviously with, with COVID a lot of pressuring 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 some growth areas, but do it by business question. Don't do it by function. If you actually invest. And these kind of solutions, if you actually invest on developing your talent, 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 in working very hard, but it's not efficiency, and it's not working in the way that you might want to work. So there is a lot of opportunity there. And you just to put into some 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 your organization. >>Maturity is 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 attack 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 have imperfect 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 a hundred 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 a hundred dollars. >>But now let's say you have 80% perfect data and 20% flow data by using this assumption that Florida is 10 times as costly as perfect data. Your total costs now becomes $280 as opposed to a hundred dollars. This just for you to really think about as a CIO CTO, CSRO CEO, are we really paying attention and really close in the gaps that we have on our data infrastructure. If we don't do that, it's hard sometimes to see this 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 various, right. I think the key is I am in analytics. I know statistics obviously, and, and, 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 coffee 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 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 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 where 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, I pulled up, 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 manufacturers. 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 Tablo to other tools like, you know, you need to really explain them. >>What is the difference in how these two 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 Cindy's point. I 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 the station. Like I said, it's been years for us to kind of lay the foundation, get the leadership in shape the culture so people can understand why you truly need to invest, but I meant analytics. >>And so what I'm showing here is an example of how do we use basically to capture in 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, our safe user experience and adoption. So for our safe or a mission was to have 10 hours per week per employee save on average user experience or 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. I used to 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 teams and the users in HR safety and other areas that might be, eh, basically stakeholders in this whole process. >>So just to summarize this kind of effort takes a lot of energy. You hire a change agent, you need to have the 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 very souls for this organization. And that gave me the confidence to know that the work has been done and we are now in a different stage for the organization. And so for me, it says to say, thank you for everybody who has believed, obviously in our vision, everybody wants to believe in, you know, the word that we were trying to do and to make the life for, you know, workforce or customers that in 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. We, the accomplishments of this transformation, and I just, 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, what would mentors, where we, people in this industry that can help you out and guide you on this kind of a transformation is not easy to do is high effort bodies, well worth it. And with that said, I hope you are well. And it's been a pleasure talking to you. Take care. Thank you, Gustavo. That was amazing. All right, let's go to the panel. >>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. And 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, 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. We'll COVID is broken everything. And it's great to hear from our experts, you know, how to move forward. So let's get right into, so Gustavo, let's start with you. If, if I'm an aspiring change agent and let's say I'm a, 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 say, in tune to what is happening, not only in your specific field, like I have a passion for analytics, I can do this for 50 years plus, but I think you need to understand wellbeing other areas across not only a specific business, as you know, I come from, you know, Sam's club, Walmart, retail, I mean 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 use lean 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, different certain transformations that make me, you know, stretch and develop as a leader. That's what I'm looking to do. So I can help to inform the functions organizations and do the change management decision of mindset as required for these kinds of efforts. A thank you for that, that is inspiring. And, and Sydney, you love data. And the data's pretty clear that diversity is a good business, but I wonder if you can add your perspective 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 in 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. I mean, I feel like everybody in our businesses 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 a digital business over the last 12 months, really, uh, even in celebration, right? Once, once COBIT hit, uh, we really saw that, uh, that, uh, in the 200 countries and territories that we operate in today and service our customers. And today that, uh, been a huge need, right? To send money, to support family, to support, uh, friends and loved ones across the world. And as part of that, uh, we, you know, we we're, we are, uh, very, uh, honored to get to support those customers that we across all the centers today. But as part of that acceleration, we need to make sure that we had 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, uh, we, we did do some, uh, some the pivots and we did, uh, a solo rate, some of our plans on digital to help support that overall growth coming in there to support our customers going forward, because there were these times during this pandemic, right? This is the most important time. And we need to support those, those that we love and those that we care about and doing that it's one of those ways is actually by sending money to them, support them financially. And that's where, uh, really our part that our services come into play that, you know, we really support those families. So it was really a, a, a, a, 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, you were pushing the envelope too much in, in doing things with, with data or the technology that was just maybe too bold, maybe you felt like at some point it was, it was, 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, the varying points or making repetitive business cases onto 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 cannot just stay with the status quo. We need to find a way to accelerate it's information. That's the way, how, how about Utah? We were talking earlier was sedation Cindy, about that bungee jumping moment. What can you share? Yeah. You know, I think you hit upon, uh, 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, that's what I tell my team. This is that you need to be, need to feel comfortable being uncomfortable. I mean, that we have to be able to basically, uh, scale, right, expand and support that 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 what, uh, how you're operating today and your current business model, right. Things are only going to get faster. So you have to plan into align and to drive the actual transformation so that you can scale even faster in the future. So as part of that is what we're putting in place here, right. Is 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, Cindy, 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 is pre COVID, maybe sometimes clients didn't always act on it. You know, they're not on my watch 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, um, Dave, to answer your question, I would say the one bit of advice, maybe I was a little more, um, very aware of the power and 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, as Tom and Gustavo said, get used to being uncomfortable, the power and politics are gonna happen. Break the rules, get used to that and be bold. Do not, 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's the dish gonna go on to junk >>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 the cube 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 is 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, tremendous results. 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 you 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. So these please bring us home. Thank you. Thank you, Dave. Thank you. The cube team, and thanks. 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 had from all four of our distinguished speakers. First, Michelle, I was simply put it. She said it really well. That is be brave and drive. >>Don't go for a drive along. That is such an important point. Often times, you know that I think that you have to make the positive change that you want to see happen when 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, Cindy 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 voices are heard, and if it requires some force and apply that force, make sure your ideas are we start with talking about the importance of building consensus, not going at things all alone, sometimes building the importance of building the Koran. 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 take away. >>What I was inspired by is the fact that a company that is 170 years old, 170 years sold 200 companies, 200 countries they're operating in and they were able to make the change that is necessary through this difficult time. So 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 topspot.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 stock. And the last thing is these go to topspot.com/beyond our global user conferences 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, we have a lot of amazing things in store for you, our customers, our partners, our collaborators, they will be coming and sharing. You'll be sharing things that you have been working to release something that will come out next year. And also some of the crazy ideas or engineers. All of those things will be available for you at hotspot beyond. Thank you. Thank you so much.
SUMMARY :
It's time to lead the way it's of speakers and our goal is to provide you with some best practices that you can bring back It's good to talk to you again. And our first one that when you finish this and walk away, we want to make sure that you don't feel like it Now, the challenge is how do you do that with the team being change agents? are afraid to challenge the status quo because they are thinking that, you know, maybe I don't have the power or how small the company is, you may need to bring some external stimuli to start And this is why I want you to focus on having fostering a CDO said to me, you know, Cindy, I actually think this And the data is not in one place, but really at the of impact what we like to call the So the first generation BI and analytics platforms were deployed but you have to look at the BI and analytics tier in lockstep with your So you have these different components, And if you read any of my books or used And let's take an example of where you can have great data, And even though the us federal government said, well, you can't turn them off. agent, identify the relevance, or I like to call it with them and organize or eighties for the teachers, teachers, you ask them about data. forward to seeing how you foster that culture. Very happy to be here and, uh, looking forward to, uh, to talking to all of you today. You go on to google.com or you go on to being, you gone to Yahoo and you search for what you want the capabilities to really support the actual business into the future. If you can really start to provide answers part of that, you need to make sure you have the right underlying foundation ecosystems and solutions And I'm looking forward to talking to you again soon. Now I'm going to have to brag on you for a second as to support those customers going forward. And now I'm excited to it's really hard to predict the future, but if you have a North star and you know where you're going, So I think the answer to that is you have to what are the right thing to do and you have to push through it. And what they show is that if you look at the four main barriers that are basically keeping the second area, and this is specifically to implementation of AI is very And the solution that most leaders I see are taking is to just minimize costs is going to offset all those hidden costs and inefficiencies that you have on your system, it's going to cost you a dollar. But as you can tell, the price tag goes up very, very quickly. how to bring in the right leaders, because you need to focus on the leaders that you're going to make I think if you can actually have And I will show you some of the findings that we had in the pilot in the last two months. legal communications, obviously the operations teams and the users in HR And that gave me the confidence to know that the work has And with that said, I hope you are well. And of course the data, as you rightly pointed out, Tom, the pandemic I can do this for 50 years plus, but I think you need to understand wellbeing other areas don't care what type of minority you are finding your voice, And as part of that, uh, we, you know, we we're, we are, uh, very, that experience and how you got through it? Hey, the CEO is making a one two year, you know, right now, the pace of change will be the slowest pace that you see for the rest of your career. and to drive the actual transformation so that you can scale even faster in the future. I do think you have to do that with empathy, as Michelle said, and Gustavo, right, the right culture is going to deliver tournament, tremendous results. And that means making it accessible to the people in your organization that are empowered to make decisions, that you have to make the positive change that you want to see happen when you wait for someone else to do it, And the last thing is these go to topspot.com/beyond our
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Cindi Howson, ThoughtSpot | Thought.Leaders Digital 2020
>>So we're going to take a hard pivot now and go from football to Ternopil 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, the additional thousands, getting cancer and 20,000 years before the ground around there and 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. Isn't 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, Cindy, 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 is the technology look like? Is it based on 1990s BI and reporting largely parameterized 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 least cost to serve. So ticks and distrust there it's between business and it or individual stakeholders is the norm. So data is hoarded. Let's contrast that with a leader, a data and analytics leader, what is 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. >>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? >>They'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 lockstep 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's hard coding of 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 Pinboard 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, 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 thoughts about 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, or Azure synapse or Google big query, they do not. >>They re 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. It's acceleration Gartner recently predicted that by 2020 to 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 years ago. So let's talk about the real world impact of culture. And if you read any of my books or used any of the maturity models out there, whether the Gardner it score that I worked on, or the data warehousing Institute also has the 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, 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. >>The opened fake accounts, basing 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 effects, samples, 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 us federal government said, well, you can't turn them off. >>He said, we'll extend that even beyond the mandated guidelines and facing a slow down in the business because of the tough economy, he 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 with them 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 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 Sisyphus. 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 with them, what is 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 seventies or eighties for the teachers, teachers, you ask them about data. They'll say we don't, we don't need that. I care about the student. So if you can use data to help a student perform better, that is with them. And sometimes we spend so much time talking the technology, we forget what is the value we're trying to deliver with it? 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 in bed, 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 said to the months ahead to the year ahead and 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 thoughtless.
SUMMARY :
and this is why I want you to focus on having fostering a CDO said to me, you know, Cindy, I actually think this And the data is not in one place, analysts, but really at the point of impact what Why is it not at the front lines? So it's easy enough for that new decision maker, the business user, So you have these different, the So let's talk about the real world impact of And let's take an example of where you can have great, in fines, change in leadership that even the CEO agent, identify the relevance, or I like to call it with them and organize Management is the biggest barrier to of technology, leveraging the cloud, all your data.
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Thought.Leaders Digital 2020
>> Voice Over: 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. (soft upbeat music) >> 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 of the ThoughtSpot is Cindi Howson, Cindi is an analytics and BI expert with 20 plus years experience, and the author of Successful Business Intelligence: Unlock the Value of BI & Big Data. Cindi was previously the lead analyst at Gartner for the data and analytics Magic Quadrant. In early last year, she joined ThoughtSpot to help CEOs 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'm well, good to talk to you again. >> That'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. (upbeat 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 you know, cooped up in our homes, I know that the vendors like us, we have amped up our sort of effort to reach out to you with, invites for events like this. So we are getting very 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, then this is going to be used. Number two, we want to put you in touch with industry leaders and thought leaders, 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 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 teens 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, changes sort of like, if you've ever done bungee jumping, and 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 today. 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 most businesses, it is somewhat scary, change becomes all the more difficult. Ultimately change requires courage, courage 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 they 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, that are people in the company who are going to have 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 the silo of people with the answers, and there is a silo of people with the questions, and there is gap, this sort of silos are standing in the way of making that necessary change that we all 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 the domino of the positive changes that are necessary. The group of people that we are 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 dress 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 owner is to introduce Michelle. And she's our first speaker, Michelle I am very happy after watching our presentation and reading your bio that there are no country vital worldwide competition for cool parents, because she will beat all of us. Because when her children were small, 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 this slides, a bunch of amazing pictures, I'm looking to see the context behind it, I'm very thrilled to make that client so far, Michelle, I'm looking forward to her talk next. Welcome Michelle, it's over to you. (soft upbeat 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, and I thought 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 is like a religion and you pick sides. I chose Auburn University working in the Athletic Department, so I'm testament to you can start the 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 the 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 kinds 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 the 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 magic band, just these 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 Studios 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 wine 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 contract 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 dress 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 Oh, so 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 this 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 as our 100 and first year and athletes 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 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 a next level, it's powered by Amazon Web Services, and we gathered 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, matchups, et cetera, so much faster than ever before. We're continuing to roll out sensors too, that we'll gather more and more information about 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 or 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 and 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 coexist. I mean the NFL is a great example of what we call coopertition, which is cooperation and competition. When 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 old wine person. (Michelle laughing) >> Well, then I can do my job without you. >> Great, and I'm getting the feeling now you know, Sudheesh is talking about bungee jumping. My boat is when we're past this pandemic, we both take them to the Delaware Water Gap and we do the cliff jumping. >> That sounds good, I'll watch. >> 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 to the broadcasters your, your partners here and football mamas like myself. How do you prioritize when there's 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 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 I thank you for your metership here. So Michelle, I look forward to discussing this more with our other customers and disruptors joining us in a little bit. (soft upbeat 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 the additional thousands getting cancer, and 20,000 years before the ground around there and 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, isn't 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 is the technology look like? Is it based on 1990s BI and reporting largely parameterized 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 cost 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 a leader, a data and analytics leader, what is 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 being a 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? They'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 lockstep 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's hard coding a report, it's typing in search keywords and very robust keywords contains rank, top, bottom getting to a visualization that then can be pinned to an existing Pinboard 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, it's 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 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, that 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 that 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 US 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, he 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 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 Sisyphus, 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 is 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 asked 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 it. 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 in bed, 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 Thomas 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. (soft upbeat 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 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 over the shift 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 integrated 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 on to google.com or you go on to Bing, or go to Yahoo and you search for what you want, search to find an answer. ThoughtSpot for us as the same thing, but in the business world. So using ThoughtSpot and other AI capability is 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 action needed, 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 the journey to modernize our larger ecosystem as a whole. That includes modernizing our underlying data warehouses, our technology or our (indistinct) environments, and as we move that we've actually picked to our cloud providers going to AWS and GCP. We've also adopted Snowflake to really drive into organize our information and our data, then drive these new solutions and capabilities forward. So big portion of us though is culture, so how do we engage with the business teams and bring the IT teams together to really 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 does is 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's 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 of 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 a celebrating. 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 our customers want, what do our customers need, and how do we then surface them with our information, with our data, with our platform, 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 the current business lines. But how do you actually use your information 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. Now I'm going to have to brag 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, I just started this year, but there'd be some great opportunities and big 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 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 Club, Gustavo welcome. (soft upbeat music) >> So hi everyone my name is Gustavo Canton and thank you so much Cindi for the intro. As you mentioned, doing transformations is a you know, high effort, high reward situation. I have empowerment in transformation 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 do 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 nontraditional 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 into 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 your 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, what I do it thinking about the mission of how do I make change for the bigger, you know workforce so the bigger good, despite the fact that this might have a perhaps implication, so my own self interest in my career, right? Because you have to have that courage sometimes to make choices, that are not well seeing politically speaking what 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 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 add, cultural issues, politics, and lack of alignment, those are the top four. But the interesting thing is that as Cindi has mentioned, this topic about culture is actually gaining more and more traction, and in 2018, there was a story from HBR and it was for 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 us 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 search engines 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 samples of some of the roadblocks that I went through, as I think the intro information 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. We're working 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 their 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 to in a way that is super fast. The second area and this is specifically to implementation of AI is very interesting to me, because just example that I have with ThoughtSpot, right? We went to an implementation and a lot of the way the IT team functions, so 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, your opportunity here is that you need to really find what success look like, in my case, I want the user experience of our workforce to be the same as your 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 this 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 cost sometimes and cut budget. We have to do the opposite, we have to actually invest some 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, your leadership, to see more digitally, if you actually invest on fixing your data platform is 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 in working very hard but it's not efficiency, and it's not working in the way that you might want to work. So there is a lot of opportunity there, and you just to put it into some 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 think 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 attack price to what is a 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 have imperfect 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 a $100. But now let's say you have any percent perfect data and 20% flow data, by using this assumption that flow 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 CSRO, CEO, are we really paying attention and really closing the gaps that we have on our 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 can do 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 coffee 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, I pulled up, 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 manufacturers, 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 Tableau to other tools like you know, ThoughtSpot, you need to really explain them, what is the difference, and how these two can truly replace some of the spreadsheets or some of the views that you might have on these other kind 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 seeing these 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 these stations. Like I said it's been years for us to kind of lay the foundation, get the leadership and chasing culture, so people can understand why you truly need to invest what I meant 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 per employee save on average, user experience or 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. I used to 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 a courage to make these 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 very souls for this organization, and that gave me the confidence to know that the work has been done, and we are now in a different stage for the organization. And so for me it safe to say, thank you for everybody who has believed obviously in our vision, everybody who has believed in, you know, the word that we were trying to do and to make the life for, you know workforce or customers that are in 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, what would mentors what people in this industry that can help you out and guide you on this kind of a transformation is not easy to do is high effort but is 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. (soft upbeat music) >> 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, and 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. That was 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's 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 say, in tune to what is happening not only in your specific field, like I have a passion for analytics, I can do this for 50 years plus, but I think you need to understand wellbeing other areas across not only a specific business as you know, I come from, you know, Sam's Club Walmart retail, I mean 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 use lean continuous improvement that's just going to take you so far. What you have to do is and that's what I tried 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 these change management and decisions mindset as required for these kinds of efforts. >> Thank you for 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 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. I mean, I feel like everybody in our businesses 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 you know, in a digital business over the last 12 months really, even in celebration, right? Once COVID hit, we really saw that in the 200 countries and territories that we operate in today and service our customers and today, that there's been a huge need, right? To send money, to support family, to support friends and loved ones across the world. And as part of that, you know, we are very honored to support those customers that we across all the centers today. But as part of that celebration, we need to make sure that we had 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 celebrate some of our plans on digital to help support that overall growth coming in, and to support our customers going forward. Because there were 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 in doing that, it's one of those ways is actually by sending money to them, support them financially. And that's where really are part of that our services come into play that, you know, I really support those families. So it was really a great opportunity for us to really support and really bring some of our products to this 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 and doing things with data or the technology that was just maybe too bold, maybe you felt like at some point it was failing, or you 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 onto 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 cannot just stay with the status quo, we need to find a way to accelerate transformation... >> How about you Tom, we were talking earlier was Sudheesh had said 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? That's what I tell my team is that you need to feel comfortable being uncomfortable. I mean, that we have to be able to basically scale, right? Expand and support that the ever changing needs 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 the marketplace, it's only going to accelerate. So as part of that, you know, as we look at what how you're operating today in your current business model, right? Things are only going to get faster. So you have to plan into align, to drive the actual transformation, so that you can scale even faster into the future. So as part of that, so we're putting in place here, right? Is how do we create that underlying framework and foundation that allows the organization to basically continue to scale and evolve into the future? >> 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 is pre COVID, maybe sometimes clients didn't always act on it. You know, they're not on my watch 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's Sudheesh going to go on bungee jumping? (all chuckling) >> That's 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. And 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 tremendous results. Yeah, 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 that can drive you 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 had from all four of our distinguished speakers. First, Michelle, I was simply put it, she said it really well, that is be brave and drive. Don't go for a drive along, that is such an important point. Often times, you know that I think 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, 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 voices are heard and if it requires some force then apply that force, make sure your ideas are good. Gustavo talked about the importance of building consensus, not going at things all alone sometimes building the importance of building the courtroom. 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 take away, 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. So 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 conferences 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 would have been up to since the 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, you'll be sharing things that you have been working to release something that will come out next year. And also some of the crazy ideas for engineers I've been cooking up. All of those things will be available for you at ThoughtSpot Beyond, thank you, thank you so much.
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and the change every to you by ThoughtSpot, to join you virtually. and of course to our audience, and insights that you talked about. and talk to you about being So you and I share a love of Great, and I'm getting the feeling now and you can find the common So I thank you for your metership here. and the time to maturity or go to Yahoo and you and how long have you and we have a lot more to go, a change agent that I've had the pleasure in the past about you know, All right, let's go to the panel. and of course the data. that's just going to take you so far. and the data is pretty and the models, and how they're applied, in our businesses in some way, and the right platforms and how you got through it? and the vision that we want to that you see for the rest of your career. to believe that you know, and how to bring people along in a way the right culture is going to the changes to last, you want to make sure
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Thought.Leaders Digital 2020 | Japan
(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.
SUMMARY :
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ThoughtSpot Keynote v6
>> 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 at the ThoughtSpot is Cindi Howson. Cindi is an analytics and BI expert with 20 plus years experience and the author of "Successful Business Intelligence "Unlock the Value of BI & 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 the cube is ThoughtSpot CEO Sudheesh Nair Hello, Sudheesh how are you doing today? >> I'm 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. (upbeat music) >> Thanks, Dave. I wish you were there to introduce me into every room and that I walk into because you have such an amazing way of doing it. Makes me feel all so good. Look, since we have all been cooped up in our homes, I know that the vendors like us, we have amped up our sort of effort to reach out to you with invites for events like this. So we are getting very 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, generally good people that you want to hang around with long after this event is over. And number three, as we plan through this, 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 like to do. The way I think of it sort of like a, if you've ever done bungee jumping and it's like standing on the edges waiting to make that one more step, 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 first of all challenge the status quo. People sometimes are afraid to challenge the status quo because they are thinking that maybe I don't have the power to make the change that the company needs. Sometimes they feel like I don't have the skills. Sometimes they may feel that I'm probably not the right person 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. 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 the silo of people with the answers, and there is a silo of people with the questions. And there is gap. This sort of silos are standing in the way of making that necessary change that we all 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 the domino of the positive changes that are necessary. The group of people that we are 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 dress 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 our bio, that there are no country vital worldwide competition for cool patterns, because she will beat all of us because when her children were small, they were probably into Harry Potter and Disney. 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, tons of amazing pictures. I'm looking to see the context behind it. I'm very thrilled to make the acquaintance of Michelle and looking forward to her talk next. Welcome Michelle, it's over to you. (upbeat 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. And I thought 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 to you can start the 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 SCC 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 the 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 kinds of world casts 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 the 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 magic band, 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 two thousands, I was at universal studios 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 wan selects you at a wan 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 contract tracing devices joined with testing data, talk about data, actually enabling your business without it w 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 do you 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 what 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 GM's 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 all so 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 it's 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 in stats, and you immediately know that impact those with the best stats usually when the games. The NFL has always recorded stats since the beginning of time here at the NFL a little this year is our 101 year and athletes 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 and how fast 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 a next level. It's powered by Amazon web services. And we gathered 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, 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've 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 and 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-op petition, 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, tank 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 old line person. (Michelle and Cindi laughing) >> Well, then I can do my job without you. >> Great. And I'm getting the feeling now, Sudheesh is talking about bungee jumping. My vote is when we're past this pandemic, we both take them to the Delaware water gap and we do the cliff jumping. >> That sounds good, I'll 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's 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. (upbeat 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, the 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 and innovate your culture. Now, oftentimes I would talk about culture and I talk about technology. And recently a CDO said to me, "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 cost 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 a leader, a data and analytics leader, what is 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 being a 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. Everyone said that if our 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 in 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 datasets, 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 lockstep 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 use 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 big query, 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 years ago. So let's talk about the real world impact of culture. And if you 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 the money surety model. We talk about these five pillars to really become data-driven. As Michelle, I 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 and 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 up skilling 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 WIFM 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 Sisyphus. 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 WIFM. What is 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, we don't need that. I care about the student. So if you can use data to help a student perform better, that is WIFM. And sometimes we spend so much time talking the technology, we forget what is the value we're trying to deliver with it. 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 in bed, 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 JPMorgan Chase spearheading digital innovation in technology, operations, risk compliance, and retail banking. Tom, thank you so much for joining us today. (upbeat 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 technology teams into the future. As you 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 and over the shift 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 on to Bing we go onto Yahoo and you search for what you want search to find and answer. ThoughtSpot for us as the same thing, but in the business world. So using ThoughtSpot and other AI capability 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 action 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 the journey to modernize our larger ecosystem as a whole. That includes modernizing our underlying data warehouses, our technology, or our Eloqua environments. And as we move that, we've actually picked two of our cloud providers going to AWS and 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 they portion of us though is culture. So how do we engage with the business teams and bring the IT teams together to really 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 does this is maybe 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's 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 accelerating 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 of 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 organization such as how do you use your data to support the current business lines, but how do you actually use your information, your data to actually put a 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 this investments into the future. But that being said, hope you enjoy the segment on how to become and how to drive it data driven organization. And, looking forward to talking to you again soon. Thank you. >> Tom that was great thanks so much. Now I'm going to have to brag 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, doing some great opportunities and great 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. (upbeat music) >> So, hey everyone, my name is Gustavo Canton and thank you so much, Cindi, for the intro, as you mentioned, doing transformations is high effort, high reward situation. I have empowered 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 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 do 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 varying into what is happening in society, socioeconomically speaking wellbeing. The common example is a great example. And for me personally, it's an opportunity because the one core value that I have is well-being, 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 is great to be, 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 when 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. What I do it thinking about the mission of how do I make change for the bigger, workforce? for the bigger good. Despite this fact that this might have a perhaps implication on my own self-interest in my career, right? Because you have to have that courage sometimes to make choices that I know we'll see in politically speaking, what are the right thing to do? And you have to push through it. And you have to push through it. So the bottom line for me is that I don't think 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 topics culture is actually gaining, 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 state, deadline to say, "hey, in two years, we're going to make this happen. "What do we need to do to empower and enable "this change engines 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 samples of some of the roadblocks that I went through as I think transformation 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 was working 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 there're up and coming leaders that are not yet fully developed. We need to mentor those leaders and take bets on some of these talent, including young talent. We cannot be thinking in the past and just wait for people, three to five years for them to develop because the world is going to in a way that is super fast. The second area, and this is specifically to implementation of AI is very interesting to me because just example that I have with ThoughtSpot, right, we went to implementation and a lot of the way is the IT team function of the leaders look at technology, they look at it from the prism of the prior all success criteria for the traditional Bi's. And that's not going to work. Again the opportunity here is that you need to really find what successful look like. In my case, I want the user experience of our workforce to be the same as user experience you have at home is a very simple concept. And so we need to think about how do we gain the user experience with this augmented analytics tools and then work backwards to have the right talent processes and technology to enable that. And finally, with COVID a lot of pressuring organizations, and companies to do more with less. And the solution that most leaders I see are taking is to just minimize costs, sometimes in cut budget, we have to do the opposite. We have to actually invest some 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, 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 efficiency, and it's not working in the way that you might want to work. So there is a lot of opportunity there. And you just to put into some perspective, there have studies in the past about, how do we kind of measure the impact of data. And obviously this is going to vary by your organization maturity, is going to, 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 think 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 attack line or attack 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 have 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 any percent 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 is just for you to really think about as a CIO CTO, 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 that 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 various, right. I think the key is I am in analytics. I know statistics obviously, and love modeling and 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 called free up 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, the right leaders, because you need to focus on the leaders that you're going to make the most progress. 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 solution. And finally you need to make it super simple for the, in this case, I was working with the HR teams in other areas, so they can have access to one portal. They don't have to be confused in 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 IT get leadership support, find the budgeting, get everybody on board, make sure the safe 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 manufacturers. But one thing that is really important is as you bring along your audience on this, you're going from Excel, in some cases or Tableau to other tools like, ThoughtSpot, you need to really explain them what is the difference and how these tools can truly replace, some of the spreadsheets or some of the views that you might have on these other kind 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 point. I 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 the station. Like I said, it's been years for us to kind of lay the foundation, get the leadership, and shaping culture so people can understand why you truly need to invest on (indistinct) analytics. And so what I'm showing here is an example of how do we use basically, a tool to capture in 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 or a mission was to have 10 hours per week per employee save on average user experience, or 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. Our 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 teams 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 a courage to make the 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 very source for this organization. And that gave me the confidence to know that the work has been done and we are now in a different stage for the organization. And so for me, it to say, thank you for everybody who has believed, obviously in our vision, everybody who has believe in the word that we were trying to do and to make the life of four workforce or customers or in 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 what would mentors, what would people in this industry that can help you out and guide you on this kind of a transformation is not easy to do is high effort, but is 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. (air whooshing) >> Okay, now we're going to go into the panel and bring Cindi, Michelle, Tom, and Gustavo back and have an open discussion. And 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. And 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. And as you rightly pointed out, Tom, the pandemic has accelerated the need for really leaning into this. The old saying, if it ain't broke don't fix it. Well COVID is broken everything. And it's great to hear from our experts, 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 say, in tune to what is happening, not only in your specific field, like I have a passion for analytics, I can do this for 50 years plus, but I think you need to understand wellbeing other areas across not only a specific business, as you know I come from, Sam's club Walmart, retail, I mean 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 use lean 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 transformation that make me 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, change of mindset required for these kinds of efforts. >> Michelle, you're at the intersection of tech and sports and what a great combination, but they're both typically male oriented fields. I mean, we've talked a little bit about how that's changing, but two questions. Tell us how you found your voice and talk about why diversity matters so much more than ever now. >> No, I found my voice really as a young girl, and I think I had such amazing support from men in my life. And I think the support and sponsorship as well as sort of mentorship along the way, I've had amazing male mentors who have helped me understand that my voice is just as important as anyone else's. I mean, I have often heard, and I think it's been written about that a woman has to believe they'll 100% master topic before they'll talk about it where a man can feel much less mastery and go on and on. So I was that way as well. And I learned just by watching and being open, to have my voice. And honestly at times demand a seat at the table, which can be very uncomfortable. And you really do need those types of, support networks within an organization. And diversity of course is important and it has always been. But I think if anything, we're seeing in this country right now is that diversity among all types of categories is front and center. And we're realizing that we don't all think alike. We've always known this, but we're now talking about things that we never really talked about before. And we can't let this moment go unchecked and on, and not change how we operate. So having diverse voices within your company and in the field of tech and sports, I am often the first and only I'm was the first, CIO at the NFL, the first female senior executive. It was fun to be the first, but it's also, very challenging. And my responsibility is to just make sure that, I don't leave anyone behind and make sure that I leave it good for the next generation. >> Well, thank you for that. That is inspiring. And Cindi, you love data and the data's pretty clear that diversity is a good business, but I wonder if you can 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 in 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. I mean, I feel like everybody in our businesses 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 a digital business over the last, 12 months, really, even in celebration, right? Once COVID hit, we really saw that in the 200 countries and territories that we operate in today and service our customers, today, that there's been a huge need, right? To send money, to support family, to support, friends and support loved ones across the world. And as part of that we are very, honored to get to support those customers that we, across all the centers today. But as part of that acceleration we need to make sure that we had 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 there were 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 it's one of those ways is actually by sending money to them, support them financially. And that's where, really our part of that our services come into play that we really support those families. So it was really a great opportunity for us to really support and really bring some of our products to this 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, you were pushing the envelope too much in doing things with data or the technology that 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, again, whenever I go to an organization, I ask the question, hey, how fast you would like transform. And, based on the agreements from 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 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, efficiency goal. "The only way for us to really do more with less "is for us to continue this path. "We cannot 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 you Tom, we were talking earlier with Sudheesh and Cindi, about that bungee jumping moment. What could you share? >> Yeah, I think you hit upon it, right now, the pace of change with the slowest pace that you see for the rest of your career. So as part of that, right, that's what I tell my team is that you need to be, you need to feel comfortable being uncomfortable. I mean, that we have to be able to basically scale, right, expand and support that the ever-changing needs in the marketplace and industry 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, as you look at what, how you're operating today in your current business model, right. Things are only going to get faster. So you have to plan into a line into drive the agile transformation so that you can scale even faster in the future. So as part of that, that's what we're putting in place here, right, is 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, some of the advice you gave when you were at Gartner, which is pre COVID, maybe sometimes clients didn't always act on it. They're not on my watch for whatever variety of reasons, but it's being forced on them now. But knowing what you know now that 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 and 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's the dish going to go bungee jumping. >> 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 the Cube 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. 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 tremendous results. Yeah, 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, the Cube team, and thank 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 had 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 along. That is such an important point. Oftentimes, you know that I think 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've 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 voices are 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 building 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. So 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 topspot.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've 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 the Thought Spot Beyond. Thank you. Thank you so much.
SUMMARY :
and the change every Cindi, great to see you Nice to join you virtually. it's good to talk to you again. and of course, to our audience but that is the hardest step to take. and talk to you about being So you and I share a love of And I'm getting the feeling now, that you need to satisfy? And that means listening to and the time to maturity the business to act quickly and how long have you to support those customers going forward. And now I'm excited to are the right thing to do? All right, let's go to the panel. and it is critical to that's just going to take you so far. Tell us how you found your voice and in the field of tech and sports, and the data's pretty clear and the models and how they're applied, everybody in our businesses and the right platforms and how you got through it? and the vision that we want to take place, How about you Tom, is that you need to be, some of the advice you gave and how to bring people along the right culture is going to is to leave you with a takeaway
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Sri Satish Ambati, H20.ai | CUBE Conversation, May 2020
>> connecting with thought leaders all around the world, this is a CUBE Conversation. Hi, everybody this is Dave Vellante of theCUBE, and welcome back to my CXO series. I've been running this through really since the start of the COVID-19 crisis to really understand how leaders are dealing with this pandemic. Sri Ambati is here, he's the CEO and founder of H20. Sri, it's great to see you again, thanks for coming on. >> Thank you for having us. >> Yeah, so this pandemic has obviously given people fits, no question, but it's also given opportunities for companies to kind of reassess where they are. Automation is a huge watchword, flexibility, business resiliency and people who maybe really hadn't fully leaned into things like the cloud and AI and automation are now realizing, wow, we have no choice, it's about survival. Your thought as to what you're seeing in the marketplace. >> Thanks for having us. I think first of all, kudos to the frontline health workers who have been ruthlessly saving lives across the country and the world, and what you're really doing is a fraction of what we could have done or should be doing to stay away the next big pandemic. But that apart I think, I usually tend to say BC is before COVID. So if the world was thinking about going digital after COVID-19, they have been forced to go digital and as a result, you're seeing tremendous transformation across our customers, and a lot of application to kind of go in and reinvent their business models that allow them to scale as effortlessly as they could using the digital means. >> So, think about, doctors and diagnosis machines, in some cases, are helping doctors make diagnoses, they're sometimes making even better diagnosis, (mumbles) is informing. There's been a lot of talk about the models, you know how... Yeah, I know you've been working with a lot of healthcare organizations, you may probably familiar with that, you know, the Medium post, The Hammer and the Dance, and if people criticize the models, of course, they're just models, right? And you iterate models and machine intelligence can help us improve. So, in this, you know, you talk about BC and post C, how have you seen the data and in machine intelligence informing the models and proving that what we know about this pandemic, I mean, it changed literally daily, what are you seeing? >> Yeah, and I think it started with Wuhan and we saw the best application of AI in trying to trace, literally from Alipay, to WeChat, track down the first folks who were spreading it across China and then eventually the rest of the world. I think contact tracing, for example, has become a really interesting problem. supply chain has been disrupted like never before. We're beginning to see customers trying to reinvent their distribution mechanisms in the second order effects of the COVID, and the the prime center is hospital staffing, how many ventilator, is the first few weeks so that after COVID crisis as it evolved in the US. We are busy predicting working with some of the local healthcare communities to predict how staffing in hospitals will work, how many PPE and ventilators will be needed and so henceforth, but that quickly and when the peak surge will be those with the beginning problems, and many of our customers have begin to do these models and iterate and improve and kind of educate the community to practice social distancing, and that led to a lot of flattening the curve and you're talking flattening the curve, you're really talking about data science and analytics in public speak. That led to kind of the next level, now that we have somewhat brought a semblance of order to the reaction to COVID, I think what we are beginning to figure out is, is there going to be a second surge, what elective procedures that were postponed, will be top of the mind for customers, and so this is the kind of things that hospitals are beginning to plan out for the second half of the year, and as businesses try to open up, certain things were highly correlated to surgeon cases, such as cleaning supplies, for example, the obvious one or pantry buying. So retailers are beginning to see what online stores are doing well, e-commerce, online purchases, electronic goods, and so everyone essentially started working from home, and so homes needed to have the same kind of bandwidth that offices and commercial enterprises needed to have, and so a lot of interesting, as one side you saw airlines go away, this side you saw the likes of Zoom and video take off. So you're kind of seeing a real divide in the digital divide and that's happening and AI is here to play a very good role to figure out how to enhance your profitability as you're looking about planning out the next two years. >> Yeah, you know, and obviously, these things they get, they get partisan, it gets political, I mean, our job as an industry is to report, your job is to help people understand, I mean, let the data inform and then let public policy you know, fight it out. So who are some of the people that you're working with that you know, as a result of COVID-19. What's some of the work that H2O has done, I want to better understand what role are you playing? >> So one of the things we're kind of privileged as a company to come into the crisis, with a strong balance and an ability to actually have the right kind of momentum behind the company in terms of great talent, and so we have 10% of the world's top data scientists in the in the form of Kaggle Grand Masters in the company. And so we put most of them to work, and they started collecting data sets, curating data sets and making them more qualitative, picking up public data sources, for example, there's a tremendous amount of job loss out there, figuring out which are the more difficult kind of sectors in the economy and then we started looking at exodus from the cities, we're looking at mobility data that's publicly available, mobility data through the data exchanges, you're able to find which cities which rural areas, did the New Yorkers as they left the city, which places did they go to, and what's to say, Californians when they left Los Angeles, which are the new places they have settled in? These are the places which are now busy places for the same kind of items that you need to sell if you're a retailer, but if you go one step further, we started engaging with FEMA, we start engaging with the universities, like Imperial College London or Berkeley, and started figuring out how best to improve the models and automate them. The SEER model, the most popular SEER model, we added that into our Driverless AI product as a recipe and made that accessible to our customers in testing, to customers in healthcare who are trying to predict where the surge is likely to come. But it's mostly about information right? So the AI at the end of it is all about intelligence and being prepared. Predictive is all about being prepared and that's kind of what we did with general, lots of blogs, typical blog articles and working with the largest health organizations and starting to kind of inform them on the most stable models. What we found to our not so much surprise, is that the simplest, very interpretable models are actually the most widely usable, because historical data is actually no longer as effective. You need to build a model that you can quickly understand and retry again to the feedback loop of back testing that model against what really happened. >> Yeah, so I want to double down on that. So really, two things I want to understand, if you have visibility on it, sounds like you do. Just in terms of the surge and the comeback, you know, kind of what those models say, based upon, you know, we have some advanced information coming from the global market, for sure, but it seems like every situation is different. What's the data telling you? Just in terms of, okay, we're coming into the spring and the summer months, maybe it'll come down a little bit. Everybody says it... We fully expect it to come back in the fall, go back to college, don't go back to college. What is the data telling you at this point in time with an understanding that, you know, we're still iterating every day? >> Well, I think I mean, we're not epidemiologists, but at the same time, the science of it is a highly local response, very hyper local response to COVID-19 is what we've seen. Santa Clara, which is just a county, I mean, is different from San Francisco, right, sort of. So you beginning to see, like we saw in Brooklyn, it's very different, and Bronx, very different from Manhattan. So you're seeing a very, very local response to this disease, and I'm talking about US. You see the likes of Brazil, which we're worried about, has picked up quite a bit of cases now. I think the silver lining I would say is that China is up and running to a large degree, a large number of our user base there are back active, you can see the traffic patterns there. So two months after their last research cases, the business and economic activity is back and thriving. And so, you can kind of estimate from that, that this can be done where you can actually contain the rise of active cases and it will take masking of the entire community, masking and the healthy dose of increase in testing. One of our offices is in Prague, and Czech Republic has done an incredible job in trying to contain this and they've done essentially, masked everybody and as a result they're back thinking about opening offices, schools later this month. So I think that's a very, very local response, hyper local response, no one country and no one community is symmetrical with other ones and I think we have a unique situation where in United States you have a very, very highly connected world, highly connected economy and I think we have quite a problem on our hands on how to safeguard our economy while also safeguarding life. >> Yeah, so you can't just, you can't just take Norway and apply it or South Korea and apply it, every situation is different. And then I want to ask you about, you know, the economy in terms of, you know, how much can AI actually, you know, how can it work in this situation where you have, you know, for example, okay, so the Fed, yes, it started doing asset buys back in 2008 but still, very hard to predict, I mean, at this time of this interview you know, Stock Market up 900 points, very difficult to predict that but some event happens in the morning, somebody, you know, Powell says something positive and it goes crazy but just sort of even modeling out the V recovery, the W recovery, deep recession, the comeback. You have to have enough data, do you not? In order for AI to be reasonably accurate? How does it work? And how does at what pace can you iterate and improve on the models? >> So I think that's exactly where I would say, continuous modeling, instead of continuously learning continuous, that's where the vision of the world is headed towards, where data is coming, you build a model, and then you iterate, try it out and come back. That kind of rapid, continuous learning would probably be needed for all our models as opposed to the typical, I'm pushing a model to production once a year, or once every quarter. I think what we're beginning to see is the kind of where companies are beginning to kind of plan out. A lot of people lost their jobs in the last couple of months, right, sort of. And so up scaling and trying to kind of bring back these jobs back both into kind of, both from the manufacturing side, but also lost a lot of jobs in the transportation and the kind of the airlines slash hotel industries, right, sort of. So it's trying to now bring back the sense of confidence and will take a lot more kind of testing, a lot more masking, a lot more social empathy, I think well, some of the things that we are missing while we are socially distant, we know that we are so connected as a species, we need to kind of start having that empathy for we need to wear a mask, not for ourselves, but for our neighbors and people we may run into. And I think that kind of, the same kind of thinking has to kind of parade, before we can open up the economy in a big way. The data, I mean, we can do a lot of transfer learning, right, sort of there are new methods, like try to model it, similar to the 1918, where we had a second bump, or a lot of little bumps, and that's kind of where your W shaped pieces, but governments are trying very well in seeing stimulus dollars being pumped through banks. So some of the US case we're looking for banks is, which small medium business in especially, in unsecured lending, which business to lend to, (mumbles) there's so many applications that have come to banks across the world, it's not just in the US, and banks are caught up with the problem of which and what's growing the concern for this business to kind of, are they really accurate about the number of employees they are saying they have? Do then the next level problem or on forbearance and mortgage, that side of the things are coming up at some of these banks as well. So they're looking at which, what's one of the problems that one of our customers Wells Fargo, they have a question which branch to open, right, sort of that itself, it needs a different kind of modeling. So everything has become a very highly good segmented models, and so AI is absolutely not just a good to have, it has become a must have for most of our customers in how to go about their business. (mumbles) >> I want to talk a little bit about your business, you have been on a mission to democratize AI since the beginning, open source. Explain your business model, how you guys make money and then I want to help people understand basic theoretical comparisons and current affairs. >> Yeah, that's great. I think the last time we spoke, probably about at the Spark Summit. I think Dave and we were talking about Sparkling Water and H2O our open source platforms, which are premium platforms for democratizing machine learning and math at scale, and that's been a tremendous brand for us. Over the last couple of years, we have essentially built a platform called Driverless AI, which is a license software and that automates machine learning models, we took the best practices of all these data scientists, and combined them to essentially build recipes that allow people to build the best forecasting models, best fraud prevention models or the best recommendation engines, and so we started augmenting traditional data scientists with this automatic machine learning called AutoML, that essentially allows them to build models without necessarily having the same level of talent as these great Kaggle Grand Masters. And so that has democratized, allowed ordinary companies to start producing models of high caliber and high quality that would otherwise have been the pedigree of Google, Microsoft or Amazon or some of these top tier AI houses like Netflix and others. So what we've done is democratize not just the algorithms at the open source level. Now, we've made it easy for kind of rapid adoption of AI across every branch inside a company, a large organization, also across smaller organizations which don't have the access to the same kind of talent. Now, third level, you know, what we've brought to market, is ability to augment data sets, especially public and private data sets that you can, the alternative data sets that can increase the signal. And that's where we've started working on a new platform called Q, again, more license software, and I mean, to give you an idea there from business models endpoint, now majority of our software sales is coming from closed source software. And sort of so, we've made that transition, we still make our open source widely accessible, we continue to improve it, a large chunk of the teams are improving and participating in building the communities but I think from a business model standpoint as of last year, 51% of our revenues are now coming from closed source software and that change is continuing to grow. >> And this is the point I wanted to get to, so you know, the open source model was you know, Red Hat the one company that, you know, succeeded wildly and it was, put it out there open source, come up with a service, maintain the software, you got to buy the subscription okay, fine. And everybody thought that you know, you were going to do that, they thought that Databricks was going to do and that changed. But I want to take two examples, Hortonworks which kind of took the Red Hat model and Cloudera which does IP. And neither really lived up to the expectation, but now there seems to be sort of a new breed I mentioned, you guys, Databricks, there are others, that seem to be working. You with your license software model, Databricks with a managed service and so there's, it's becoming clear that there's got to be some level of IP that can be licensed in order to really thrive in the open source community to be able to fund the committers that you have to put forth to open source. I wonder if you could give me your thoughts on that narrative. >> So on Driverless AI, which is the closest platform I mentioned, we opened up the layers in open source as recipes. So for example, different companies build their zip codes differently, right, the domain specific recipes, we put about 150 of them in open source again, on top of our Driverless AI platform, and the idea there is that, open source is about freedom, right? It is not necessarily about, it's not a philosophy, it's not a business model, it allows freedom for rapid adoption of a platform and complete democratization and commodification of a space. And that allows a small company like ours to compete at the level of an SaaS or a Google or a Microsoft because you have the same level of voice as a very large company and you're focused on using code as a community building exercise as opposed to a business model, right? So that's kind of the heart of open source, is allowing that freedom for our end users and the customers to kind of innovate at the same level of that a Silicon Valley company or one of these large tech giants are building software. So it's really about making, it's a maker culture, as opposed to a consumer culture around software. Now, if you look at how the the Red Hat model, and the others who have tried to replicate that, the difficult part there was, if the product is very good, customers are self sufficient and if it becomes a standard, then customers know how to use it. If the product is crippled or difficult to use, then you put a lot of services and that's where you saw the classic Hadoop companies, get pulled into a lot of services, which is a reasonably difficult business to scale. So I think what we chose was, instead, a great product that builds a fantastic brand, that makes AI, even when other first or second.ai domain, and for us to see thousands of companies which are not AI and AI first, and even more companies adopting AI and talking about AI as a major way that was possible because of open source. If you had chosen close source and many of your peers did, they all vanished. So that's kind of how the open source is really about building the ecosystem and having the patience to build a company that takes 10, 20 years to build. And what we are expecting unfortunately, is a first and fast rise up to become unicorns. In that race, you're essentially sacrifice, building a long ecosystem play, and that's kind of what we chose to do, and that took a little longer. Now, if you think about the, how do you truly monetize open source, it takes a little longer and is much more difficult sales machine to scale, right, sort of. Our open source business actually is reasonably positive EBITDA business because it makes more money than we spend on it. But trying to teach sales teams, how to sell open source, that's a much, that's a rate limiting step. And that's why we chose and also explaining to the investors, how open source is being invested in as you go closer to the IPO markets, that's where we chose, let's go into license software model and scale that as a regular business. >> So I've said a few times, it's kind of like ironic that, this pandemic is as we're entering a new decade, you know, we've kind of we're exiting the era, I mean, the many, many decades of Moore's law being the source of innovation and now it's a combination of data, applying machine intelligence and being able to scale and with cloud. Well, my question is, what did we expect out of AI this decade if those are sort of the three, the cocktail of innovation, if you will, what should we expect? Is it really just about, I suggest, is it really about automating, you know, businesses, giving them more agility, flexibility, you know, etc. Or should we should we expect more from AI this decade? >> Well, I mean, if you think about the decade of 2010 2011, that was defined by software is eating the world, right? And now you can say software is the world, right? I mean, pretty much almost all conditions are digital. And AI is eating software, right? (mumbling) A lot of cloud transitions are happening and are now happening much faster rate but cloud and AI are kind of the leading, AI is essentially one of the biggest driver for cloud adoption for many of our customers. So in the enterprise world, you're seeing rebuilding of a lot of data, fast data driven applications that use AI, instead of rule based software, you're beginning to see patterned, mission AI based software, and you're seeing that in spades. And, of course, that is just the tip of the iceberg, AI has been with us for 100 years, and it's going to be ahead of us another hundred years, right, sort of. So as you see the discovery rate at which, it is really a fundamentally a math, math movement and in that math movement at the beginning of every century, it leads to 100 years of phenomenal discovery. So AI is essentially making discoveries faster, AI is producing, entertainment, AI is producing music, AI is producing choreographing, you're seeing AI in every walk of life, AI summarization of Zoom meetings, right, you beginning to see a lot of the AI enabled ETF peaking of stocks, right, sort of. You're beginning to see, we repriced 20,000 bonds every 15 seconds using H2O AI, corporate bonds. And so you and one of our customers is on the fastest growing stock, mostly AI is powering a lot of these insights in a fast changing world which is globally connected. No one of us is able to combine all the multiple dimensions that are changing and AI has that incredible opportunity to be a partner for every... (mumbling) For a hospital looking at how the second half will look like for physicians looking at what is the sentiment of... What is the surge to expect? To kind of what is the market demand looking at the sentiment of the customers. AI is the ultimate money ball in business and then I think it's just showing its depth at this point. >> Yeah, I mean, I think you're right on, I mean, basically AI is going to convert every software, every application, or those tools aren't going to have much use, Sri we got to go but thanks so much for coming to theCUBE and the great work you guys are doing. Really appreciate your insights. stay safe, and best of luck to you guys. >> Likewise, thank you so much. >> Welcome, and thank you for watching everybody, this is Dave Vellante for the CXO series on theCUBE. We'll see you next time. All right, we're clear. All right.
SUMMARY :
Sri, it's great to see you Your thought as to what you're and a lot of application and if people criticize the models, and kind of educate the community and then let public policy you know, and starting to kind of inform them What is the data telling you of the entire community, and improve on the models? and the kind of the airlines and then I want to help people understand and I mean, to give you an idea there in the open source community to be able and the customers to kind of innovate and being able to scale and with cloud. What is the surge to expect? and the great work you guys are doing. Welcome, and thank you
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Sri Satish Ambati, H20.ai | CUBE Conversation, May 2020
>> Starting the record, Dave in five, four, three. Hi, everybody this is Dave Vellante, theCUBE, and welcome back to my CXO series. I've been running this through really since the start of the COVID-19 crisis to really understand how leaders are dealing with this pandemic. Sri Ambati is here, he's the CEO and founder of H20. Sri, it's great to see you again, thanks for coming on. >> Thank you for having us. >> Yeah, so this pandemic has obviously given people fits, no question, but it's also given opportunities for companies to kind of reassess where they are. Automation is a huge watchword, flexibility, business resiliency and people who maybe really hadn't fully leaned into things like the cloud and AI and automation are now realizing, wow, we have no choice, it's about survival. Your thought as to what you're seeing in the marketplace. >> Thanks for having us. I think first of all, kudos to the frontline health workers who have been ruthlessly saving lives across the country and the world, and what you're really doing is a fraction of what we could have done or should be doing to stay away the next big pandemic. But that apart I think, I usually tend to say BC is before COVID. So if the world was thinking about going digital after COVID-19, they have been forced to go digital and as a result, you're seeing tremendous transformation across our customers, and a lot of application to kind of go in and reinvent their business models that allow them to scale as effortlessly as they could using the digital means. >> So, think about, doctors and diagnosis machines, in some cases, are helping doctors make diagnoses, they're sometimes making even better diagnosis, (mumbles) is informing. There's been a lot of talk about the models, you know how... Yeah, I know you've been working with a lot of healthcare organizations, you may probably familiar with that, you know, the Medium post, The Hammer and the Dance, and if people criticize the models, of course, they're just models, right? And you iterate models and machine intelligence can help us improve. So, in this, you know, you talk about BC and post C, how have you seen the data and in machine intelligence informing the models and proving that what we know about this pandemic, I mean, it changed literally daily, what are you seeing? >> Yeah, and I think it started with Wuhan and we saw the best application of AI in trying to trace, literally from Alipay, to WeChat, track down the first folks who were spreading it across China and then eventually the rest of the world. I think contact tracing, for example, has become a really interesting problem. supply chain has been disrupted like never before. We're beginning to see customers trying to reinvent their distribution mechanisms in the second order effects of the COVID, and the the prime center is hospital staffing, how many ventilator, is the first few weeks so that after COVID crisis as it evolved in the US. We are busy predicting working with some of the local healthcare communities to predict how staffing in hospitals will work, how many PPE and ventilators will be needed and so henceforth, but that quickly and when the peak surge will be those with the beginning problems, and many of our customers have begin to do these models and iterate and improve and kind of educate the community to practice social distancing, and that led to a lot of flattening the curve and you're talking flattening the curve, you're really talking about data science and analytics in public speak. That led to kind of the next level, now that we have somewhat brought a semblance of order to the reaction to COVID, I think what we are beginning to figure out is, is there going to be a second surge, what elective procedures that were postponed, will be top of the mind for customers, and so this is the kind of things that hospitals are beginning to plan out for the second half of the year, and as businesses try to open up, certain things were highly correlated to surgeon cases, such as cleaning supplies, for example, the obvious one or pantry buying. So retailers are beginning to see what online stores are doing well, e-commerce, online purchases, electronic goods, and so everyone essentially started working from home, and so homes needed to have the same kind of bandwidth that offices and commercial enterprises needed to have, and so a lot of interesting, as one side you saw airlines go away, this side you saw the likes of Zoom and video take off. So you're kind of seeing a real divide in the digital divide and that's happening and AI is here to play a very good role to figure out how to enhance your profitability as you're looking about planning out the next two years. >> Yeah, you know, and obviously, these things they get, they get partisan, it gets political, I mean, our job as an industry is to report, your job is to help people understand, I mean, let the data inform and then let public policy you know, fight it out. So who are some of the people that you're working with that you know, as a result of COVID-19. What's some of the work that H2O has done, I want to better understand what role are you playing? >> So one of the things we're kind of privileged as a company to come into the crisis, with a strong balance and an ability to actually have the right kind of momentum behind the company in terms of great talent, and so we have 10% of the world's top data scientists in the in the form of Kaggle Grand Masters in the company. And so we put most of them to work, and they started collecting data sets, curating data sets and making them more qualitative, picking up public data sources, for example, there's a tremendous amount of job loss out there, figuring out which are the more difficult kind of sectors in the economy and then we started looking at exodus from the cities, we're looking at mobility data that's publicly available, mobility data through the data exchanges, you're able to find which cities which rural areas, did the New Yorkers as they left the city, which places did they go to, and what's to say, Californians when they left Los Angeles, which are the new places they have settled in? These are the places which are now busy places for the same kind of items that you need to sell if you're a retailer, but if you go one step further, we started engaging with FEMA, we start engaging with the universities, like Imperial College London or Berkeley, and started figuring out how best to improve the models and automate them. The SaaS model, the most popular SaaS model, we added that into our Driverless AI product as a recipe and made that accessible to our customers in testing, to customers in healthcare who are trying to predict where the surge is likely to come. But it's mostly about information right? So the AI at the end of it is all about intelligence and being prepared. Predictive is all about being prepared and that's kind of what we did with general, lots of blogs, typical blog articles and working with the largest health organizations and starting to kind of inform them on the most stable models. What we found to our not so much surprise, is that the simplest, very interpretable models are actually the most widely usable, because historical data is actually no longer as effective. You need to build a model that you can quickly understand and retry again to the feedback loop of back testing that model against what really happened. >> Yeah, so I want to double down on that. So really, two things I want to understand, if you have visibility on it, sounds like you do. Just in terms of the surge and the comeback, you know, kind of what those models say, based upon, you know, we have some advanced information coming from the global market, for sure, but it seems like every situation is different. What's the data telling you? Just in terms of, okay, we're coming into the spring and the summer months, maybe it'll come down a little bit. Everybody says it... We fully expect it to come back in the fall, go back to college, don't go back to college. What is the data telling you at this point in time with an understanding that, you know, we're still iterating every day? >> Well, I think I mean, we're not epidemiologists, but at the same time, the science of it is a highly local response, very hyper local response to COVID-19 is what we've seen. Santa Clara, which is just a county, I mean, is different from San Francisco, right, sort of. So you beginning to see, like we saw in Brooklyn, it's very different, and Bronx, very different from Manhattan. So you're seeing a very, very local response to this disease, and I'm talking about US. You see the likes of Brazil, which we're worried about, has picked up quite a bit of cases now. I think the silver lining I would say is that China is up and running to a large degree, a large number of our user base there are back active, you can see the traffic patterns there. So two months after their last research cases, the business and economic activity is back and thriving. And so, you can kind of estimate from that, that this can be done where you can actually contain the rise of active cases and it will take masking of the entire community, masking and the healthy dose of increase in testing. One of our offices is in Prague, and Czech Republic has done an incredible job in trying to contain this and they've done essentially, masked everybody and as a result they're back thinking about opening offices, schools later this month. So I think that's a very, very local response, hyper local response, no one country and no one community is symmetrical with other ones and I think we have a unique situation where in United States you have a very, very highly connected world, highly connected economy and I think we have quite a problem on our hands on how to safeguard our economy while also safeguarding life. >> Yeah, so you can't just, you can't just take Norway and apply it or South Korea and apply it, every situation is different. And then I want to ask you about, you know, the economy in terms of, you know, how much can AI actually, you know, how can it work in this situation where you have, you know, for example, okay, so the Fed, yes, it started doing asset buys back in 2008 but still, very hard to predict, I mean, at this time of this interview you know, Stock Market up 900 points, very difficult to predict that but some event happens in the morning, somebody, you know, Powell says something positive and it goes crazy but just sort of even modeling out the V recovery, the W recovery, deep recession, the comeback. You have to have enough data, do you not? In order for AI to be reasonably accurate? How does it work? And how does at what pace can you iterate and improve on the models? >> So I think that's exactly where I would say, continuous modeling, instead of continuously learning continuous, that's where the vision of the world is headed towards, where data is coming, you build a model, and then you iterate, try it out and come back. That kind of rapid, continuous learning would probably be needed for all our models as opposed to the typical, I'm pushing a model to production once a year, or once every quarter. I think what we're beginning to see is the kind of where companies are beginning to kind of plan out. A lot of people lost their jobs in the last couple of months, right, sort of. And so up scaling and trying to kind of bring back these jobs back both into kind of, both from the manufacturing side, but also lost a lot of jobs in the transportation and the kind of the airlines slash hotel industries, right, sort of. So it's trying to now bring back the sense of confidence and will take a lot more kind of testing, a lot more masking, a lot more social empathy, I think well, some of the things that we are missing while we are socially distant, we know that we are so connected as a species, we need to kind of start having that empathy for we need to wear a mask, not for ourselves, but for our neighbors and people we may run into. And I think that kind of, the same kind of thinking has to kind of parade, before we can open up the economy in a big way. The data, I mean, we can do a lot of transfer learning, right, sort of there are new methods, like try to model it, similar to the 1918, where we had a second bump, or a lot of little bumps, and that's kind of where your W shaped pieces, but governments are trying very well in seeing stimulus dollars being pumped through banks. So some of the US case we're looking for banks is, which small medium business in especially, in unsecured lending, which business to lend to, (mumbles) there's so many applications that have come to banks across the world, it's not just in the US, and banks are caught up with the problem of which and what's growing the concern for this business to kind of, are they really accurate about the number of employees they are saying they have? Do then the next level problem or on forbearance and mortgage, that side of the things are coming up at some of these banks as well. So they're looking at which, what's one of the problems that one of our customers Wells Fargo, they have a question which branch to open, right, sort of that itself, it needs a different kind of modeling. So everything has become a very highly good segmented models, and so AI is absolutely not just a good to have, it has become a must have for most of our customers in how to go about their business. (mumbles) >> I want to talk a little bit about your business, you have been on a mission to democratize AI since the beginning, open source. Explain your business model, how you guys make money and then I want to help people understand basic theoretical comparisons and current affairs. >> Yeah, that's great. I think the last time we spoke, probably about at the Spark Summit. I think Dave and we were talking about Sparkling Water and H2O or open source platforms, which are premium platforms for democratizing machine learning and math at scale, and that's been a tremendous brand for us. Over the last couple of years, we have essentially built a platform called Driverless AI, which is a license software and that automates machine learning models, we took the best practices of all these data scientists, and combined them to essentially build recipes that allow people to build the best forecasting models, best fraud prevention models or the best recommendation engines, and so we started augmenting traditional data scientists with this automatic machine learning called AutoML, that essentially allows them to build models without necessarily having the same level of talent as these Greek Kaggle Grand Masters. And so that has democratized, allowed ordinary companies to start producing models of high caliber and high quality that would otherwise have been the pedigree of Google, Microsoft or Amazon or some of these top tier AI houses like Netflix and others. So what we've done is democratize not just the algorithms at the open source level. Now, we've made it easy for kind of rapid adoption of AI across every branch inside a company, a large organization, also across smaller organizations which don't have the access to the same kind of talent. Now, third level, you know, what we've brought to market, is ability to augment data sets, especially public and private data sets that you can, the alternative data sets that can increase the signal. And that's where we've started working on a new platform called Q, again, more license software, and I mean, to give you an idea there from business models endpoint, now majority of our software sales is coming from closed source software. And sort of so, we've made that transition, we still make our open source widely accessible, we continue to improve it, a large chunk of the teams are improving and participating in building the communities but I think from a business model standpoint as of last year, 51% of our revenues are now coming from closed source software and that change is continuing to grow. >> And this is the point I wanted to get to, so you know, the open source model was you know, Red Hat the one company that, you know, succeeded wildly and it was, put it out there open source, come up with a service, maintain the software, you got to buy the subscription okay, fine. And everybody thought that you know, you were going to do that, they thought that Databricks was going to do and that changed. But I want to take two examples, Hortonworks which kind of took the Red Hat model and Cloudera which does IP. And neither really lived up to the expectation, but now there seems to be sort of a new breed I mentioned, you guys, Databricks, there are others, that seem to be working. You with your license software model, Databricks with a managed service and so there's, it's becoming clear that there's got to be some level of IP that can be licensed in order to really thrive in the open source community to be able to fund the committers that you have to put forth to open source. I wonder if you could give me your thoughts on that narrative. >> So on Driverless AI, which is the closest platform I mentioned, we opened up the layers in open source as recipes. So for example, different companies build their zip codes differently, right, the domain specific recipes, we put about 150 of them in open source again, on top of our Driverless AI platform, and the idea there is that, open source is about freedom, right? It is not necessarily about, it's not a philosophy, it's not a business model, it allows freedom for rapid adoption of a platform and complete democratization and commodification of a space. And that allows a small company like ours to compete at the level of an SaaS or a Google or a Microsoft because you have the same level of voice as a very large company and you're focused on using code as a community building exercise as opposed to a business model, right? So that's kind of the heart of open source, is allowing that freedom for our end users and the customers to kind of innovate at the same level of that a Silicon Valley company or one of these large tech giants are building software. So it's really about making, it's a maker culture, as opposed to a consumer culture around software. Now, if you look at how the the Red Hat model, and the others who have tried to replicate that, the difficult part there was, if the product is very good, customers are self sufficient and if it becomes a standard, then customers know how to use it. If the product is crippled or difficult to use, then you put a lot of services and that's where you saw the classic Hadoop companies, get pulled into a lot of services, which is a reasonably difficult business to scale. So I think what we chose was, instead, a great product that builds a fantastic brand, that makes AI, even when other first or second.ai domain, and for us to see thousands of companies which are not AI and AI first, and even more companies adopting AI and talking about AI as a major way that was possible because of open source. If you had chosen close source and many of your peers did, they all vanished. So that's kind of how the open source is really about building the ecosystem and having the patience to build a company that takes 10, 20 years to build. And what we are expecting unfortunately, is a first and fast rise up to become unicorns. In that race, you're essentially sacrifice, building a long ecosystem play, and that's kind of what we chose to do, and that took a little longer. Now, if you think about the, how do you truly monetize open source, it takes a little longer and is much more difficult sales machine to scale, right, sort of. Our open source business actually is reasonably positive EBITDA business because it makes more money than we spend on it. But trying to teach sales teams, how to sell open source, that's a much, that's a rate limiting step. And that's why we chose and also explaining to the investors, how open source is being invested in as you go closer to the IPO markets, that's where we chose, let's go into license software model and scale that as a regular business. >> So I've said a few times, it's kind of like ironic that, this pandemic is as we're entering a new decade, you know, we've kind of we're exiting the era, I mean, the many, many decades of Moore's law being the source of innovation and now it's a combination of data, applying machine intelligence and being able to scale and with cloud. Well, my question is, what did we expect out of AI this decade if those are sort of the three, the cocktail of innovation, if you will, what should we expect? Is it really just about, I suggest, is it really about automating, you know, businesses, giving them more agility, flexibility, you know, etc. Or should we should we expect more from AI this decade? >> Well, I mean, if you think about the decade of 2010 2011, that was defined by software is eating the world, right? And now you can say software is the world, right? I mean, pretty much almost all conditions are digital. And AI is eating software, right? (mumbling) A lot of cloud transitions are happening and are now happening much faster rate but cloud and AI are kind of the leading, AI is essentially one of the biggest driver for cloud adoption for many of our customers. So in the enterprise world, you're seeing rebuilding of a lot of data, fast data driven applications that use AI, instead of rule based software, you're beginning to see patterned, mission AI based software, and you're seeing that in spades. And, of course, that is just the tip of the iceberg, AI has been with us for 100 years, and it's going to be ahead of us another hundred years, right, sort of. So as you see the discovery rate at which, it is really a fundamentally a math, math movement and in that math movement at the beginning of every century, it leads to 100 years of phenomenal discovery. So AI is essentially making discoveries faster, AI is producing, entertainment, AI is producing music, AI is producing choreographing, you're seeing AI in every walk of life, AI summarization of Zoom meetings, right, you beginning to see a lot of the AI enabled ETF peaking of stocks, right, sort of. You're beginning to see, we repriced 20,000 bonds every 15 seconds using H2O AI, corporate bonds. And so you and one of our customers is on the fastest growing stock, mostly AI is powering a lot of these insights in a fast changing world which is globally connected. No one of us is able to combine all the multiple dimensions that are changing and AI has that incredible opportunity to be a partner for every... (mumbling) For a hospital looking at how the second half will look like for physicians looking at what is the sentiment of... What is the surge to expect? To kind of what is the market demand looking at the sentiment of the customers. AI is the ultimate money ball in business and then I think it's just showing its depth at this point. >> Yeah, I mean, I think you're right on, I mean, basically AI is going to convert every software, every application, or those tools aren't going to have much use, Sri we got to go but thanks so much for coming to theCUBE and the great work you guys are doing. Really appreciate your insights. stay safe, and best of luck to you guys. >> Likewise, thank you so much. >> Welcome, and thank you for watching everybody, this is Dave Vellante for the CXO series on theCUBE. We'll see you next time. All right, we're clear. All right.
SUMMARY :
Sri, it's great to see you Your thought as to what you're and a lot of application and if people criticize the models, and kind of educate the community and then let public policy you know, is that the simplest, What is the data telling you of the entire community, and improve on the models? and the kind of the airlines and then I want to help people understand and I mean, to give you an idea there in the open source community to be able and the customers to kind of innovate and being able to scale and with cloud. What is the surge to expect? and the great work you guys are doing. Welcome, and thank you
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Announcement: Sri Ambati, H2O.ai | CUBE Converstion, August 2019
(upbeat music) >> Announcer: From our studios, in the heart of Silicon Valley, Palo Alto, California, this is a Cube conversation. >> Everyone, welcome to this special Cube conversation here in Palo Alto Cube studios. I'm John Furrier, host of the Cube. We have special breaking news here, with Sri Ambati who is the founder and CEO of H2O.ai with big funding news. Great to see you Cube alumni, hot startup, you got some hot funding news, share with us. >> We are very excited to announce our Series D. Goldman Sachs, one of our leading customers and Ping An from China are leading our round. It's a round of $72 million, and bringing our total fundraise to 147. This is an endorsement of their support of our mission to democratize AI and an endorsement of the amazing teamwork behind the company and its customer centricity. Customers have now come to lead two of our rounds. Last round was Series C led by Wells Fargo and NVIDIA and I think it just goes to say how critical a thing we are for their success in AI. >> Well congratulations, I've been watching you guys build this company from scratch, we've had many conversations going back to 2013, '14 on The Cube. You call it-- >> You covered us long before. >> You guys were always on the wave, and you really created a category, this is a new category that Cloud 2.0 is creating which is a DevOps mindset, entrepreneurial mindset, creating a category to enable people to have the kind of infrastructure and tooling and software to enable them to do all the heavy lifting of AI without doing the heavy lifting. As the quote for cloud is, that Amazon always quotes is you do all of the undifferentiated heavy lifting that's required to stand up stuff and then provide tooling for the heavy differentiated lifting to make it easy to use. This has been a key thing. Has that been the-- >> Customers have be core to our, company building. H2O is here to build an amazing piece of innovation and technology and innovation is not new for Silicon Valley, as you know. But I think innovation, with a purpose and with a focus of customer success is something we represent and that's been kind of the key north finder for us. In terms of making things simpler, when we started, it was a grassroots movement in open source and we wanted the mind share of millions of users worldwide and that mind share got us a lot of feedback. And that feedback is how we then built the second generation of the product lines, which is driverless AI. We are also announcing our mission to make every company an AI company, this funding will power that transformation of several businesses that can then go on to build the AI superpower. >> And certainly, cloud computing, more compute more elastic resources is always a great tailwind. What are you guys going to do with the funding in terms of focus? >> You mentioned cloud which is a great story. We're obviously going to make things easier for folks who are doing the cloud, but they are the largest players, as well, Google, Microsoft, Amazon. They're right there, trying to innovate. AI is at the center of every software moment because AI eating software, software is eating the world. And so, all the software players are right there, trying to build a large AI opportunity for the world and we think in ecosystems, not just empires. So our mission is to uplift the entire AI to the place where businesses can use it, verticalize it, build new products, globalize. We are building our sales and marketing efforts now with a much bigger, faster systems-- >> So a lot of, go to market expansion, more customer focus. More field sales and support kind of thing. >> Build our center for AI research in Prague, within the CND, now we are building it in Chennai and Ottawa, and so globalizing the operation, going to China, going to build focus in Asia as well. >> So nice step up on funding at 72 million, you said? >> 72.5 million. >> 72.5 million, that's almost double what you've raised to date, nice kickup. So global expansion, nice philosophy. That's important to you guys, isn't it? >> The world has become a small village. There's no changing that, and data is global. Things are a wide global trend, it's amazing to see that AI is not just transforming the US, it's also transforming China, it's also transforming India. It's transforming Africa. Pay through mobile is a very common theme worldwide and I think data is being collected globally. I think there is no way to unbox it and box it back to a small place, so our vision is very borderless and global and we want the AI companies of the valley to also compete in a global arena and I think that's kind of why we think it's important to be-- >> Love competition, that's certainly going to force everyone to be more open. I got to ask you about the role of the developer. I love the democratization, putting AI in the hands of everybody, it's a great mission. You guys do a lot of AI for Good efforts. So congratulations on that, but how does this change the nature of the developer, because you're seeing with cloud and DevOps, developers are becoming closer to the front lines, they're becoming kingmakers. They're becoming really, really important. So the role of the developer is important. How do you change that role, if any. How do you expand it, what happens? >> There are two important transformations happening right now in the tech world. One is the role of data scientists and the role of the software engineer. Right, so they're coming closer in many ways, in actually in some of the newer places, software engineers are deploying data science models, data scientists are deploying software engineering. So Python has been a good new language, the new languages that are coming up that help that happen more closely. Software engineering as we know it, which was looking at data creating the rules and the logic that runs a program is now being automated to a degree where that logic is being generated from data using data science. So that's where the brains behind how programs run how computers build is now being, is AI inside. And so that's where the world is transforming, software engineers now get to do a lot more with a lot less of tinkering on a daily basis for little modules. They can probably build a whole slew of an application what would take 18 months to build is now compressing into 18 weeks or 18 days. >> Sri, I love how you talk about software engineering and data scientists, very specific. I was having a debate with my young son around what is computer science was the question. Well, computer science is the study of computers the science of computers. It used to be if you were a CS or a comp sci major which is not cool to say anymore but, when you were a computer science major, you were really a software engineer, that was the discipline. Now, computer science as a field has spread so far and so broad, you've got software engineering you've got data science, you have newer roles are emerging. But that brings up the question I want to put to you which is, the whole idea of, I'm a full stack developer. Well, if what you're saying you're doing is true, you're essentially cutting the stack in half. So it's a half stack developer on one end and a data scientist that's got the other half. So the notion of the full stack developer kind of goes away with the idea of horizontally scalable infrastructure and vertically specialized data and AI. Your thoughts, what's your reaction to that? >> I think the most... I would say the most scarce resource in the world is empathy, right? When developers have empathy for their users, they now start building design that cares for the users. So the design becomes still the limiting factor where you can't really automate a lot of that design. So the full stack engineer is now going closer to the front and understanding their users and making applications that are perceptive of how the users are using them and building that empathy into the product. A lot of the full stack, we used to learn how to build up a kernel, deploy it on cloud, scale it on your own servers. All of that is coming together in reasonably easier ways. With cloud is helping there, AI is helping there, data is helping there, and lessons from the data. But I think what has not gone away is imagination, creativity, and how to power that creativity with AI and get it in the hands of someone quickly. Marketing has become easier in the new world. So it's not just enough to make products, you have to make markets for your products and then deliver and get that success for customers-- >> So what you're saying-- >> The developers become-- >> The consistency of the lower end of the stack of wiring together the plumbing and the kernel and everything else is done for you. So you can move up. >> Up the stack. >> So the stack's growing, so it's still kind of full. No one calls themselves a half stack developer. I haven't met anyone say "Yeah I'm a half stack developer." They're full stack developers, but the roles are changing. >> I think what-- >> There's more to do on the front end of creativity so the stack's extending. >> Creativity is changing, I think the one thing we have learned. We've gone past Moore's Law in the valley and people are innovating architectures to run AI faster. So AI is beginning to eat hardware. So you've seen the transformation in microprocessors as well I think once AI starts being part of the overall conversation, you'll see a much more richer coexistence with being how a human programmer and a computer programmer is going to be working closely. But I think this is just the beginning of a real richness when you talk about rich interactive applications, you're going to talk about rich interactive appliances, where you start seeing intelligence really spread around the form. >> Sri, if we really want to have some fun we can just talk about what a 10x engineer is. No I'm only kidding, we're not going to go there. It's always a good debate on Twitter what a 10x engineer is. Sri, congratulations on the funding. $72.5 million in finance for global expansion on the team side as well as in geographies, congratulations. >> Thank you. >> H2O.ai >> The full stack engineer of the future is, finishing up your full stack engineer conversation is going to get that courage and become a leader. Going from managers to leaders, developers to founders. I think it's become easier to democratize entrepreneurship now than ever before and part of our mission as a company is to democratize things, democratize AI, democratize H2O like in the AI for Good, democratize water. But also democratize the art of making more entrepreneurs and remove the common ways to fail and that's also a way to create more opportunity more ownership in the world and so-- >> And I think society will benefit from this globally because in the data is truth, in the data is the notion of being transparent, if it's all there and we're going to get to the data faster and that's where AI helps us. >> That's what it is. >> Sri, congratulations, $72 million of funding for H2O. We're here with the founder and CEO Sri Ambati. Great success story here in Silicon Valley and around the world. I'm John Furrier with the Cube, thanks for watching. >> Sri: Thank you. (upbeat music)
SUMMARY :
in the heart of Silicon Valley, Palo Alto, California, I'm John Furrier, host of the Cube. and an endorsement of the amazing teamwork conversations going back to 2013, '14 on The Cube. As the quote for cloud is, that Amazon always quotes and that's been kind of the key north finder for us. What are you guys going to do with the funding AI is at the center of every software moment So a lot of, go to market expansion, more customer focus. and Ottawa, and so globalizing the operation, That's important to you guys, isn't it? and I think data is being collected globally. So the role of the developer is important. and the role of the software engineer. and a data scientist that's got the other half. So the full stack engineer is now going closer to the front The consistency of the lower end of the stack So the stack's growing, so it's still kind of full. so the stack's extending. So AI is beginning to eat hardware. Sri, congratulations on the funding. and remove the common ways to fail because in the data is truth, in the data is the notion and around the world. Sri: Thank you.
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Influencer Panel | IBM CDO Summit 2019
>> Live from San Francisco, California, it's theCUBE covering the IBM Chief Data Officers Summit, brought to you by IBM. >> Welcome back to San Francisco everybody. I'm Dave Vellante and you're watching theCUBE, the leader in live tech coverage. This is the end of the day panel at the IBM Chief Data Officer Summit. This is the 10th CDO event that IBM has held and we love to to gather these panels. This is a data all-star panel and I've recruited Seth Dobrin who is the CDO of the analytics group at IBM. Seth, thank you for agreeing to chip in and be my co-host in this segment. >> Yeah, thanks Dave. Like I said before we started, I don't know if this is a promotion or a demotion. (Dave laughing) >> We'll let you know after the segment. So, the data all-star panel and the data all-star awards that you guys are giving out a little later in the event here, what's that all about? >> Yeah so this is our 10th CDU Summit. So two a year, so we've been doing this for 5 years. The data all-stars are those people that have been to four at least of the ten. And so these are five of the 16 people that got the award. And so thank you all for participating and I attended these like I said earlier, before I joined IBM they were immensely valuable to me and I was glad to see 16 other people that think it's valuable too. >> That is awesome. Thank you guys for coming on. So, here's the format. I'm going to introduce each of you individually and then ask you to talk about your role in your organization. What role you play, how you're using data, however you want to frame that. And the first question I want to ask is, what's a good day in the life of a data person? Or if you want to answer what's a bad day, that's fine too, you choose. So let's start with Lucia Mendoza-Ronquillo. Welcome, she's the Senior Vice President and the Head of BI and Data Governance at Wells Fargo. You told us that you work within the line of business group, right? So introduce your role and what's a good day for a data person? >> Okay, so my role basically is again business intelligence so I support what's called cards and retail services within Wells Fargo. And I also am responsible for data governance within the business. We roll up into what's called a data governance enterprise. So we comply with all the enterprise policies and my role is to make sure our line of business complies with data governance policies for enterprise. >> Okay, good day? What's a good day for you? >> A good day for me is really when I don't get a call that the regulators are knocking on our doors. (group laughs) Asking for additional reports or have questions on the data and so that would be a good day. >> Yeah, especially in your business. Okay, great. Parag Shrivastava is the Director of Data Architecture at McKesson, welcome. Thanks so much for coming on. So we got a healthcare, couple of healthcare examples here. But, Parag, introduce yourself, your role, and then what's a good day or if you want to choose a bad day, be fun the mix that up. >> Yeah, sounds good. Yeah, so mainly I'm responsible for the leader strategy and architecture at McKesson. What that means is McKesson has a lot of data around the pharmaceutical supply chain, around one-third of the world's pharmaceutical supply chain, clinical data, also around pharmacy automation data, and we want to leverage it for the better engagement of the patients and better engagement of our customers. And my team, which includes the data product owners, and data architects, we are all responsible for looking at the data holistically and creating the data foundation layer. So I lead the team across North America. So that's my current role. And going back to the question around what's a good day, I think I would say the good day, I'll start at the good day. Is really looking at when the data improves the business. And the first thing that comes to my mind is sort of like an example, of McKesson did an acquisition of an eight billion dollar pharmaceutical company in Europe and we were creating the synergy solution which was based around the analytics and data. And actually IBM was one of the partners in implementing that solution. When the solution got really implemented, I mean that was a big deal for me to see that all the effort that we did in plumbing the data, making sure doing some analytics, is really helping improve the business. I think that is really a good day I would say. I mean I wouldn't say a bad day is such, there are challenges, constant challenges, but I think one of the top priorities that we are having right now is to deal with the demand. As we look at the demand around the data, the role of data has got multiple facets to it now. For example, some of the very foundational, evidentiary, and compliance type of needs as you just talked about and then also profitability and the cost avoidance and those kind of aspects. So how to balance between that demand is the other aspect. >> All right good. And we'll get into a lot of that. So Carl Gold is the Chief Data Scientist at Zuora. Carl, tell us a little bit about Zuora. People might not be as familiar with how you guys do software for billing et cetera. Tell us about your role and what's a good day for a data scientist? >> Okay, sure, I'll start by a little bit about Zuora. Zuora is a subscription management platform. So any company who wants to offer a product or service as subscription and you don't want to build your billing and subscription management, revenue recognition, from scratch, you can use a product like ours. I say it lets anyone build a telco with a complicated plan, with tiers and stuff like that. I don't know if that's a good thing or not. You guys'll have to make up your own mind. My role is an interesting one. It's split, so I said I'm a chief data scientist and we work about 50% on product features based on data science. Things like churn prediction, or predictive payment retries are product areas where we offer AI-based solutions. And then but because Zuora is a subscription platform, we have an amazing set of data on the actual performance of companies using our product. So a really interesting part of my role has been leading what we call the subscription economy index and subscription economy benchmarks which are reports around best practices for subscription companies. And it's all based off this amazing dataset created from an anonymized data of our customers. So that's a really exciting part of my role. And for me, maybe this speaks to our level of data governance, I might be able to get some tips from some of my co-panelists, but for me a good day is when all the data for me and everyone on my team is where we left it the night before. And no schema changes, no data, you know records that you were depending on finding removed >> Pipeline failures. >> Yeah pipeline failures. And on a bad day is a schema change, some crucial data just went missing and someone on my team is like, "The code's broken." >> And everybody's stressed >> Yeah, so those are bad days. But, data governance issues maybe. >> Great, okay thank you. Jung Park is the COO of Latitude Food Allergy Care. Jung welcome. >> Yeah hi, thanks for having me and the rest of us here. So, I guess my role I like to put it as I'm really the support team. I'm part of the support team really for the medical practice so, Latitude Food Allergy Care is a specialty practice that treats patients with food allergies. So, I don't know if any of you guys have food allergies or maybe have friends, kids, who have food allergies, but, food allergies unfortunately have become a lot more prevalent. And what we've been able to do is take research and data really from clinical trials and other research institutions and really use that from the clinical trial setting, back to the clinical care model so that we can now treat patients who have food allergies by using a process called oral immunotherapy. It's fascinating and this is really personal to me because my son as food allergies and he's been to the ER four times. >> Wow. >> And one of the scariest events was when he went to an ER out of the country and as a parent, you know you prepare your child right? With the food, he takes the food. He was 13 years old and you had the chaperones, everyone all set up, but you get this call because accidentally he ate some peanut, right. And so I saw this unfold and it scared me so much that this is something I believe we just have to get people treated. So this process allows people to really eat a little bit of the food at a time and then you eat the food at the clinic and then you go home and eat it. Then you come back two weeks later and then you eat a little bit more until your body desensitizes. >> So you build up that immunity >> Exactly. >> and then you watch the data obviously. >> Yeah. So what's a good day for me? When our patients are done for the day and they have a smile on their face because they were able to progress to that next level. >> Now do you have a chief data officer or are you the de facto CFO? >> I'm the de facto. So, my career has been pretty varied. So I've been essentially chief data officer, CIO, at companies small and big. And what's unique about I guess in this role is that I'm able to really think about the data holistically through every component of the practice. So I like to think of it as a patient journey and I'm sure you guys all think of it similarly when you talk about your customers, but from a patient's perspective, before they even come in, you have to make sure the data behind the science of whatever you're treating is proper, right? Once that's there, then you have to have the acquisition part. How do you actually work with the community to make sure people are aware of really the services that you're providing? And when they're with you, how do you engage them? How do you make sure that they are compliant with the process? So in healthcare especially, oftentimes patients don't actually succeed all the way through because they don't continue all the way through. So it's that compliance. And then finally, it's really long-term care. And when you get the long-term care, you know that the patient that you've treated is able to really continue on six months, a year from now, and be able to eat the food. >> Great, thank you for that description. Awesome mission. Rolland Ho is the Vice President of Data and Analytics at Clover Health. Tell us a little bit about Clover Health and then your role. >> Yeah, sure. So Clover is a startup Medicare Advantage plan. So we provide Medicare, private Medicare to seniors. And what we do is we're because of the way we run our health plan, we're able to really lower a lot of the copay costs and protect seniors against out of pocket. If you're on regular Medicare, you get cancer, you have some horrible accident, your out of pocket is infinite potentially. Whereas with Medicare Advantage Plan it's limited to like five, $6,000 and you're always protected. One of the things I'm excited about being at Clover is our ability to really look at how can we bring the value of data analytics to healthcare? Something I've been in this industry for close to 20 years at this point and there's a lot of waste in healthcare. And there's also a lot of very poor application of preventive measures to the right populations. So one of the things that I'm excited about is that with today's models, if you're able to better identify with precision, the right patients to intervene with, then you fundamentally transform the economics of what can be done. Like if you had to pa $1,000 to intervene, but you were only 20% of the chance right, that's very expensive for each success. But, now if your model is 60, 70% right, then now it opens up a whole new world of what you can do. And that's what excites me. In terms of my best day? I'll give you two different angles. One as an MBA, one of my best days was, client calls me up, says, "Hey Rolland, you know, "your analytics brought us over $100 million "in new revenue last year." and I was like, cha-ching! Excellent! >> Which is my half? >> Yeah right. And then on the data geek side the best day was really, run a model, you train a model, you get ridiculous AUC score, so area under the curve, and then you expect that to just disintegrate as you go into validation testing and actual live production. But the 98 AUC score held up through production. And it's like holy cow, the model actually works! And literally we could cut out half of the workload because of how good that model was. >> Great, excellent, thank you. Seth, anything you'd add to the good day, bad day, as a CDO? >> So for me, well as a CDO or as CDO at IBM? 'Cause at IBM I spend most of my time traveling. So a good day is a day I'm home. >> Yeah, when you're not in an (group laughing) aluminum tube. >> Yeah. Hurdling through space (laughs). No, but a good day is when a GDPR compliance just happened, a good day for me was May 20th of last year when IBM was done and we were, or as done as we needed to be for GDPR so that was a good day for me last year. This year is really a good day is when we start implementing some new models to help IBM become a more effective company and increase our bottom line or increase our margins. >> Great, all right so I got a lot of questions as you know and so I want to give you a chance to jump in. >> All right. >> But, I can get it started or have you got something? >> I'll go ahead and get started. So this is a the 10th CDO Summit. So five years. I know personally I've had three jobs at two different companies. So over the course of the last five years, how many jobs, how many companies? Lucia? >> One job with one company. >> Oh my gosh you're boring. (group laughing) >> No, but actually, because I support basically the head of the business, we go into various areas. So, we're not just from an analytics perspective and business intelligence perspective and of course data governance, right? It's been a real journey. I mean there's a lot of work to be done. A lot of work has been accomplished and constantly improving the business, which is the first goal, right? Increasing market share through insights and business intelligence, tracking product performance to really helping us respond to regulators (laughs). So it's a variety of areas I've had to be involved in. >> So one company, 50 jobs. >> Exactly. So right now I wear different hats depending on the day. So that's really what's happening. >> So it's a good question, have you guys been jumping around? Sure, I mean I think of same company, one company, but two jobs. And I think those two jobs have two different layers. When I started at McKesson I was a solution leader or solution director for business intelligence and I think that's how I started. And over the five years I've seen the complete shift towards machine learning and my new role is actually focused around machine learning and AI. That's why we created this layer, so our own data product owners who understand the data science side of things and the ongoing and business architecture. So, same company but has seen a very different shift of data over the last five years. >> Anybody else? >> Sure, I'll say two companies. I'm going on four years at Zuora. I was at a different company for a year before that, although it was kind of the same job, first at the first company, and then at Zuora I was really focused on subscriber analytics and churn for my first couple a years. And then actually I kind of got a new job at Zuora by becoming the subscription economy expert. I become like an economist, even though I don't honestly have a background. My PhD's in biology, but now I'm a subscription economy guru. And a book author, I'm writing a book about my experiences in the area. >> Awesome. That's great. >> All right, I'll give a bit of a riddle. Four, how do you have four jobs, five companies? >> In five years. >> In five years. (group laughing) >> Through a series of acquisition, acquisition, acquisition, acquisition. Exactly, so yeah, I have to really, really count on that one (laughs). >> I've been with three companies over the past five years and I would say I've had seven jobs. But what's interesting is I think it kind of mirrors and kind of mimics what's been going on in the data world. So I started my career in data analytics and business intelligence. But then along with that I had the fortune to work with the IT team. So the IT came under me. And then after that, the opportunity came about in which I was presented to work with compliance. So I became a compliance officer. So in healthcare, it's very interesting because these things are tied together. When you look about the data, and then the IT, and then the regulations as it relates to healthcare, you have to have the proper compliance, both internal compliance, as well as external regulatory compliance. And then from there I became CIO and then ultimately the chief operating officer. But what's interesting is as I go through this it's all still the same common themes. It's how do you use the data? And if anything it just gets to a level in which you become closer with the business and that is the most important part. If you stand alone as a data scientist, or a data analyst, or the data officer, and you don't incorporate the business, you alienate the folks. There's a math I like to do. It's different from your basic math, right? I believe one plus one is equal to three because when you get the data and the business together, you create that synergy and then that's where the value is created. >> Yeah, I mean if you think about it, data's the only commodity that increases value when you use it correctly. >> Yeah. >> Yeah so then that kind of leads to a question that I had. There's this mantra, the more data the better. Or is it more of an Einstein derivative? Collect as much data as possible but not too much. What are your thoughts? Is more data better? >> I'll take it. So, I would say the curve has shifted over the years. Before it used to be data was the bottleneck. But now especially over the last five to 10 years, I feel like data is no longer oftentimes the bottleneck as much as the use case. The definition of what exactly we're going to apply to, how we're going to apply it to. Oftentimes once you have that clear, you can go get the data. And then in the case where there is not data, like in Mechanical Turk, you can all set up experiments, gather data, the cost of that is now so cheap to experiment that I think the bottleneck's really around the business understanding the use case. >> Mm-hmm. >> Mm-hmm. >> And I think the wave that we are seeing, I'm seeing this as there are, in some cases, more data is good, in some cases more data is not good. And I think I'll start it where it is not good. I think where quality is more required is the area where more data is not good. For example like regulation and compliance. So for example in McKesson's case, we have to report on opioid compliance for different states. How much opioid drugs we are giving to states and making sure we have very, very tight reporting and compliance regulations. There, highest quality of data is important. In our data organization, we have very, very dedicated focus around maintaining that quality. So, quality is most important, quantity is not if you will, in that case. Having the right data. Now on the other side of things, where we are doing some kind of exploratory analysis. Like what could be a right category management for our stores? Or where the product pricing could be the right ones. Product has around 140 attributes. We would like to look at all of them and see what patterns are we finding in our models. So there you could say more data is good. >> Well you could definitely see a lot of cases. But certainly in financial services and a lot of healthcare, particularly in pharmaceutical where you don't want work in process hanging around. >> Yeah. >> Some lawyer could find a smoking gun and say, "Ooh see." And then if that data doesn't get deleted. So, let's see, I would imagine it's a challenge in your business, I've heard people say, "Oh keep all the, now we can keep all the data, "it's so inexpensive to store." But that's not necessarily such a good thing is it? >> Well, we're required to store data. >> For N number of years, right? >> Yeah, N number of years. But, sometimes they go beyond those number of years when there's a legal requirements to comply or to answer questions. So we do keep more than, >> Like a legal hold for example. >> Yeah. So we keep more than seven years for example and seven years is the regulatory requirement. But in the case of more data, I'm a data junkie, so I like more data (laughs). Whenever I'm asked, "Is the data available?" I always say, "Give me time I'll find it for you." so that's really how we operate because again, we're the go-to team, we need to be able to respond to regulators to the business and make sure we understand the data. So that's the other key. I mean more data, but make sure you understand what that means. >> But has that perspective changed? Maybe go back 10 years, maybe 15 years ago, when you didn't have the tooling to be able to say, "Give me more data." "I'll get you the answer." Maybe, "Give me more data." "I'll get you the answer in three years." Whereas today, you're able to, >> I'm going to go get it off the backup tapes (laughs). >> (laughs) Yeah, right, exactly. (group laughing) >> That's fortunately for us, Wells Fargo has implemented data warehouse for so many number of years, I think more than 10 years. So we do have that capability. There's certainly a lot of platforms you have to navigate through, but if you are able to navigate, you can get to the data >> Yeah. >> within the required timeline. So I have, astonished you have the technology, team behind you. Jung, you want to add something? >> Yeah, so that's an interesting question. So, clearly in healthcare, there is a lot of data and as I've kind of come closer to the business, I also realize that there's a fine line between collecting the data and actually asking our folks, our clinicians, to generate the data. Because if you are focused only on generating data, the electronic medical records systems for example. There's burnout, you don't want the clinicians to be working to make sure you capture every element because if you do so, yes on the back end you have all kinds of great data, but on the other side, on the business side, it may not be necessarily a productive thing. And so we have to make a fine line judgment as to the data that's generated and who's generating that data and then ultimately how you end up using it. >> And I think there's a bit of a paradox here too, right? The geneticist in me says, "Don't ever throw anything away." >> Right. >> Right? I want to keep everything. But, the most interesting insights often come from small data which are a subset of that larger, keep everything inclination that we as data geeks have. I think also, as we're moving in to kind of the next phase of AI when you can start doing really, really doing things like transfer learning. That small data becomes even more valuable because you can take a model trained on one thing or a different domain and move it over to yours to have a starting point where you don't need as much data to get the insight. So, I think in my perspective, the answer is yes. >> Yeah (laughs). >> Okay, go. >> I'll go with that just to run with that question. I think it's a little bit of both 'cause people touched on different definitions of more data. In general, more observations can never hurt you. But, more features, or more types of things associated with those observations actually can if you bring in irrelevant stuff. So going back to Rolland's answer, the first thing that's good is like a good mental model. My PhD is actually in physical science, so I think about physical science, where you actually have a theory of how the thing works and you collect data around that theory. I think the approach of just, oh let's put in 2,000 features and see what sticks, you know you're leaving yourself open to all kinds of problems. >> That's why data science is not democratized, >> Yeah (laughing). >> because (laughing). >> Right, but first Carl, in your world, you don't have to guess anymore right, 'cause you have real data. >> Well yeah, of course, we have real data, but the collection, I mean for example, I've worked on a lot of customer churn problems. It's very easy to predict customer churn if you capture data that pertains to the value customers are receiving. If you don't capture that data, then you'll never predict churn by counting how many times they login or more crude measures of engagement. >> Right. >> All right guys, we got to go. The keynotes are spilling out. Seth thank you so much. >> That's it? >> Folks, thank you. I know, I'd love to carry on, right? >> Yeah. >> It goes fast. >> Great. >> Yeah. >> Guys, great, great content. >> Yeah, thanks. And congratulations on participating and being data all-stars. >> We'd love to do this again sometime. All right and thank you for watching everybody, it's a wrap from IBM CDOs, Dave Vellante from theCUBE. We'll see you next time. (light music)
SUMMARY :
brought to you by IBM. This is the end of the day panel Like I said before we started, I don't know if this is that you guys are giving out a little later And so thank you all for participating and then ask you to talk and my role is to make sure our line of business complies a call that the regulators are knocking on our doors. and then what's a good day or if you want to choose a bad day, And the first thing that comes to my mind So Carl Gold is the Chief Data Scientist at Zuora. as subscription and you don't want to build your billing and someone on my team is like, "The code's broken." Yeah, so those are bad days. Jung Park is the COO of Latitude Food Allergy Care. So, I don't know if any of you guys have food allergies of the food at a time and then you eat the food and then you When our patients are done for the day and I'm sure you guys all think of it similarly Great, thank you for that description. the right patients to intervene with, and then you expect that to just disintegrate Great, excellent, thank you. So a good day is a day I'm home. Yeah, when you're not in an (group laughing) for GDPR so that was a good day for me last year. and so I want to give you a chance to jump in. So over the course of the last five years, Oh my gosh you're boring. and constantly improving the business, So that's really what's happening. and the ongoing and business architecture. in the area. That's great. Four, how do you have four jobs, five companies? In five years. really count on that one (laughs). and you don't incorporate the business, Yeah, I mean if you think about it, Or is it more of an Einstein derivative? But now especially over the last five to 10 years, So there you could say more data is good. particularly in pharmaceutical where you don't want "it's so inexpensive to store." So we do keep more than, Like a legal hold So that's the other key. when you didn't have the tooling to be able to say, (laughs) Yeah, right, exactly. but if you are able to navigate, you can get to the data astonished you have the technology, and then ultimately how you end up using it. And I think there's a bit of a paradox here too, right? to have a starting point where you don't need as much data and you collect data around that theory. you don't have to guess anymore right, if you capture data that pertains Seth thank you so much. I know, I'd love to carry on, right? and being data all-stars. All right and thank you for watching everybody,
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Eric Herzog, IBM | CUBEConversation, March 2019
(upbeat music) [Announcer] From our studios in the heart of Silicon Valley Palo Alto, California. This is a CUBE conversation. >> Hi, I'm Peter Burris, and welcome to another CUBE conversation from our studios in beautiful Palo Alto, California. One of the biggest challenges that every user faces is how are they going to arrange their resources that are responsible for storing, managing, delivering, and protecting data. And that's a significant challenge, but it gets even worse when we start talking about multi-cloud. So, today we've got Eric Herzog who's the CMO and VP of Worldwide Storage Channels at IBM Storage to talk a bit about the evolving relationship of what constitutes a modern, comprehensive storage portfolio and multi-cloud. Eric, welcome to theCUBE. >> Peter, Thank you, thank you. >> So, start off, what's happening with IBM Storage these days, and let's get into this kind of how multi-cloud is affecting some of your decisions, and some of your customer's decisions. >> So, what we've done, is we've started talking about multi-cloud over two years ago. When Ed Walsh joined the company as a general manager, we went on an analyst roadshow, in fact, we came here to theCUBE and shot a video, and we talked about how the IBM Storage Division is all about multi-cloud. And we look about that in three ways. First of all, if you are creating a private cloud, we work with you. From a container, whether you're Vmware based, whether you are doing a more traditional cloud- private cloud. Now the modern private cloud, all container based. Second is Hybrid Cloud, data on parem, out to a public cloud provider. And the third aspect, and in fact, you guys have written about it in one of your studies is that no one is going to use one public cloud provider, they're going to use multiple cloud providers. So whether that be IBM Cloud, which of course we love because we're IBM shareholders, but we work with Amazon, we work with Google, and in fact we work with any cloud provider. Our Spectrum Protect backup product, which is one of the most awarded enterprise backup packages can backup to any cloud. In fact, over 350 small to medium cloud providers, the engine for their backup as a service, is Spectrum Protect. Again, completely heterogeneous, we don't care what cloud you use, we support everyone. And we started that mantra two and a half years ago, when Ed first joined the company. >> Now, I remember when you came on, we talked a lot about this notion of data first and the idea that data driven was what we talked about >> Right, data driven. >> And increasingly, we talked about, or we made the observation that enterprises were going to take a look at the natural arrangement of their data, and that was going to influence a lot of their cloud, a lot of their architecture, and certainly a lot of their storage divisions or decisions. How is that playing out? Is that still obtaining? Are you still seeing more enterprises taking this kind of data driven approach to thinking about their overall cloud architectures? >> Well the world is absolutely data-centric. Where does the data go? What are security issues with that data? How is it close to the compute when I need it? How do I archive I, how do I back it up? How do I protect it? We're here in Silicon Valley. I'm a native Palo Alton, by the way, and we really do have earthquakes here, and they really do have earthquakes in Japan and China and there is all kinds of natural disasters. And of course as you guys have pointed out, as have almost all of the analysts, the number one cause of data loss besides humans is actually still fire. Even with fire suppressant data centers. >> And we have fires out here in Northern California too. >> That's true. So, you've got to make sure that you're backing up that data, you're archiving the data. Cloud could be part of that strategy. When does it need to be on parem, when does it need to be off parem? So, it's all about being a data-driven, and companies look at the data, profile the date and time, What sort of storage do I need? Can I go high end, mid-range and entry, profile that data, figure that out, what they need to do. And then do the same thing now with on parem and off parem. For certain data sets, for security reasons, legal reasons you probably are not going to put it out into a public cloud provider. But other data sets are ideal for that and so all of those decisions that are being made by: What's the security of the data? What's the legality of that data? What's the performance I need of that data? And, how often do I need the data? If you're going to constantly go back and forth, pull data back in, going to a public cloud provider, which charge both for in and out of the data, that actually may cost more than buying an Array on parem. And so, everyone's using that data-centricity to figure out how do they spend their money, and how do they optimize the data to use it in their applications, workloads and use cases. >> So, if you think about it, the reality is by application, workload, location, regulatory issues, we're seeing enterprises start to recognize and increase specialization of their data assets. And that's going to lead to a degree of specializations in the classes of data management and storage technologies that they utilize. Now, what is the challenge of choosing a specific solution versus looking at more of a portfolio of solutions, that perhaps provide a little bit more commonality? How are customers, how are the IMB customer base dealing with that question. >> Well, for us the good thing was to have a broad portfolio. When you look at the base storage Arrays we have file, block and object, they're all award winning. We can go big, we can go medium, and we can go small. And because of what we do with our Array family we have products that tend to be expensive because of what they do, products that mid-price and products that are perfect for Herzog's Bar and Grill. Or maybe for 5,000 different bank branches, 'cause that bank is not going to buy expensive storage for every branch. They have a small Array there in case core goes down, of course. When you or I go in to get a check or transact, if the core data center is down, that Wells Fargo, BofA, Bank of Tokyo. >> Still has to do business. >> They are all transacting. There's a small Array there. Well you don't want to spend a lot of money for that, you need a good, reliable all flash Array with the right RAS capability, right? The availability, capability, that's what you need, And we can do that. The other thing we do is, we have very much, cloud-ified everything we do. We can tier to the cloud, we can backup to the cloud. With object storage we can place it in the cloud. So we've made the cloud, if you will, a seamless tier to the storage infrastructure for our customers. Whether that be backup data, archive data, primary data, and made it so it's very easy to do. Remember, with that downturn in '08 and '09 a lot of storage people left their job. And while IT headcount is back up to where it used to be, in fact it's actually exceeded, if there was 50 storage guys at Company X, and they had to let go 25 of them, they didn't hire 25 storage guys now, but they got 10 times the data. So they probably have 2 more storage guys, they're from 25 to 27, except they're managing 10 times the data, so automation, seamless integration with clouds, and being multi-cloud, supporting hybrid clouds is a critical thing in today's storage world. >> So you've talked a little bit about format, data format issues still impact storage decisions. You've talked about how disasters or availability still impact storage decisions, certainly cost does. But you've also talked about some of the innovative things that are happening, security, encryption, evolved backup and and restore capabilities, AI and how that's going to play, what are some of the key thing that your customer base is asking for that's really driving some of your portfolio decisions? >> Sure, well when we look beyond making sure we integrate with every cloud and make it seamless, the other aspect is AI. AI has taken off, machine learning, big data, all those. And there it's all about having the right platform from an Array perspective, but then marrying it with the right software. So for example, our scale-out file system, Spectrum Scale can go to Exabyte Class, in fact the two fastest super computers on this planet have almost half an exabyte of IBM Spectrum Scale for big data, analytics, and machine learning workloads. At the same time you need to have Object Store. If you're generating that huge amount of data set in AI world, you want to be able to put it out. We also now have Spectrum discover, which allows you to use Metadata, which is the data about the data, and allow and AI app, a machine learning app, or an analytics app to actually access the metadata through an API. So that's one area, so cloud, then AI, is a very important aspect. And of course, cyber resiliency, and cyber security is critical. Everyone thinks, I got to call a security company, so the IBM Security Division, RSA, Check Point, Symantec, McAfee, all of these things. But the reality is, as you guys have noted, 98% of all enterprises are going to get broken into. So while they're in your house, they can steal you blind. Before the cops show up, like the old movie, what are they doing? They're loading up the truck before the cops show up. Well guess what, what if that happened, cops didn't show up for 20 minutes, but they couldn't steal anything, or the TV was tied to your fingerprint? So guess what, they couldn't use the TV, so they couldn't steal it, that's what we've done. So, whether it be encryption everywhere, we can encrypt backup sets, we can encrypt data at rest, we can even encrypt Arrays that aren't ours with our Spectrum Virtualize family. Air gapping, so that if you have ransomware or malware you can air-gap to tape. We've actually created air gapping out with a cloud snapshot. We have a product called Safeguard Copy which creates what I'll call a faux air gap in the mainframe space, but allows that protection so it's almost as if it was air gapped even though it's on an Array. So that's a ransomware and malware, being able to detect that, our backup products when they see an unusual activity will flag the backup restore jam and say there is unusual activity. Why, because ransomware and malware generate unusual activity on back up data sets in particular, so it's flaky. Now we don't go out and say, "By the way, that's Herzog ransomware, or "Peter Burris ransomware." But we do say "something is wrong, you need to take a look." So, integrating that sort of cyber resiliency and cyber security into the entire storage portfolio doesn't mean we solve everything. Which is why when you get an overall security strategy, you've got that Great Wall of China to keep the enemy out, you've got the what I call, chase software to get the bad guy once he's in the house, the cops that are coming to get the bad guy. But you've got to be able to lock everything down, you'll do it. So a comprehensive security strategy, and resiliency strategy involves not only your security vendor, but actually your storage vendor. And IBM's got the right cyber resiliency and security technology on the storage side to marry up, regardless of which security vendor they choose. >> Now you mention a number of things that are associated with how an enterprise is going to generate greater leverage, greater value out of data that you already know. So, you mentioned, you know, encryption end to end, you mention being able to look at metadata for AI applications. As we move to a software driven world of storage where physical volumes can still be made more virtual so you can move them around to different workloads. >> Right. >> And associate the data more easily, tell us a little bit about how data movement becomes an issue in the storage world, because the storage has already been associated with it's here. But increasingly, because of automation, because of AI, because of what businesses are trying to do, it's becoming more associated with intelligent, smart, secure, optimized movement of data. How is that starting to impact the portfolio? >> So we look at that really as data mobility. And data mobility can be another number of different things, for example, we already mentioned, we treat clouds as transparent tiers. We can backup to cloud, that's data mobility. We also tier data, we can tier data within an Array, or the Spectrum Virtualize product. We can tier data, block data cross 450 Arrays, most of which aren't IBM logo'd. We can tier from IBM to EMC, EMC can then tier to HDS, HDS can tier to Hitachi, and we do that on Arrays that aren't ours. So in that case what you're doing is looking for the optimal price point, whether it be- >> And feature set. >> And feature sets, and you move things, data around all transparently, so it's all got to be automated, that's another thing, in the old days we thought we had Nirvana when the tiering was automatically moved the data when it's 30 days old. What if we automatically move data with our Easy Tier technology through AI, when the data is hot moves it to the hottest tier, when the data is cold it puts it out to the lowest cost tier. That's real automation leveraging AI technology. Same thing, something simple, migration. How much money have all the storage companies made on migration services? What if you could do transparent block migration in the background on the fly, without ever taking your servers down, we can do that. And what we do is, it's so intelligent we always favor the data set, so when the data is being worked on, migration slows down. When the data set slows down, guess what? Migration picks up. But the point is, data mobility, in this case from an old Array to an new Array. So whether it be migrating data, whether it be tiering data, whether you're moving data out to the cloud, whether it be primary data or backup data, or object data for archive, the bottom line is we've infused not only the cloudification of our storage portfolio, but the mobility aspects of the portfolio. Which does of course include cloud. But all tiering more likely is on premise. You could tier to the cloud, but all flash Array to a cheap 7200 RPM Array, you save a lot of money and we can do that using AI technology with Easy Tier. All examples of moving data around transparently, quickly, efficiently, to save cost both in CapEx, using 7200 RPM Arrays of course to cut costs, but actually OpEx the storage admin, there aren't a hundred storage admins at Burris Incorporated. You had to let them go, you've hired 100 of the people back, but you hired them all for DevOps so you have 50 guys in storage >> Actually there are, but I'm a lousy businessman so I'm not going to be in business long. (laughing) One more question, Eric. I mean look you're an old style road warrior, you're out with customers a lot. Increasingly, and I know this because we've talked about it, you're finding yourself trying to explain to business people, not just IT people how digital business, data and storage come together. When you're having these conversations with executives on the business side, how does this notion of data services get discussed? What are some of the conversations like? >> Well I think the key thing you got to point out is storage guys love to talk speeds and feeds. I'm so old I can still talk TPI and BPI on hard drives and no one does that anymore, right? But, when you're talking to the CEO or the CFO or the business owner, it's all about delivering data at the right performance level you need for your applications, workloads and use cases, your right resiliency for applications, workloads and use cases, your right availability, so it's all about application, workloads, and use cases. So you don't talk about storage speeds and feeds that you would with Storage Admin, or maybe in the VP of infrastructure in the Fortune 500, you'd talk about it's all about the data, keeping the data secure, keeping the data reliable, keeping it at right performance. So if it's on the type of workload that needs performance, for example, let's take the easy one, Flash. Why do I need Flash? Well, Mr. CEO, do you use logistics? Of course we do! Who do you use, SAP. Oh, how long does that logistics workload take? Oh, it takes like 24 hours to run. What if I told you you could run that every night, in an hour? That's the power of Flash. So you translate what you and I are used to, storage nerdiness, we translate it into businessfied, in this case, running that SAP workload in an hour vs. 24 has a real business impact. And that's the way you got to talk about storage these days. When you're out talking to a storage admin, with the admin, yes, you want to talk latency and IOPS and bandwidth. But the CEO is just going to turn his nose up. But when you say I can run the MongoDB workload, or I can do this or do that, and I can do it. What was 24 hours in an hour, or half an hour. That translates to real data, and real value out of that data. And that's what they're looking for, is how to extract value from the data. If the data isn't performant, you get less value. If the data isn't there, you clearly have no value. And if the data isn't available enough so that it's down part time, if you are doing truly digital business. So, if Herzog's Bar and Grill, actually everything is done digitally, so before you get that pizza, or before you get that cigar, you have to order it online. If my website, which has a database underneath, of course, so I can handle the transactions right, I got to take the credit card, I got to get the orders right. If that is down half the time, my business is down, and that's an example of taking IT and translating it to something as simple as a Bar and Grill. And everyone is doing it these days. So when you talk about, do you want that website up all the time? Do you need your order entry system up all the time? Do you need your this or that? Then they actually get it, and then obviously, making sure that the applications run quickly, swiftly, and smoothly. And storage is, if you will, that critical foundation underneath everything. It's not the fancy windows, it's not the fancy paint. But if that foundation isn't right, what happens? The whole building falls down. And that's exactly what storage delivers regardless of the application workload. That right critical foundation of performance, availability, reliability. That's what they need, when you have that all applications run better, and your business runs better. >> Yeah, and the one thing I'd add to that, Eric, is increasingly the conversations that we're having is options. And one of the advantages of a large portfolio or a platform approach is that the things you're doing today, you'll discover new things that you didn't anticipate, and you want the option to be able to do them quickly. >> Absolutely. >> Very, very important thing. So, applications, workload, use cases, multi-cloud storage portfolio. Eric, thanks again for coming on theCUBE, always love having you. >> Great, thank you. >> And once again, I'm Peter Burris, talking with Eric Herzog, CMO, VP of Worldwide Storage Channels at IBM Storage. Thanks again for watching this CUBE conversation, until next time. (upbeat music)
SUMMARY :
[Announcer] From our studios in the heart One of the biggest challenges that every user faces how multi-cloud is affecting some of your And the third aspect, and in fact, you guys have take a look at the natural arrangement of their And of course as you guys have pointed out, as have What's the legality of that data? How are customers, how are the IMB customer base And because of what we do with our Array family We can tier to the cloud, we can backup to the cloud. AI and how that's going to play, But the reality is, as you guys have noted, 98% of data that you already know. And associate the data more easily, tell us a little HDS, HDS can tier to Hitachi, and we cloudification of our storage portfolio, but the What are some of the conversations like? And that's the way you got to talk about storage these days. Yeah, and the one thing I'd add to that, Eric, is multi-cloud storage portfolio. And once again, I'm Peter Burris, talking with
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StrongbyScience Podcast | Cory Schlesinger, Stanford | Ep. 2 - Part One
>> Produced from the Cube studios. This's strong by science, in depth conversations about science based training, sports performance and all things health and wellness. Here's your hose, Max Marzo. I'm with >> the one and only Cory Slush Inger Cory is the director of men's sorry, director of performance from men's basketball at Stanford University. Good friend of mine, extremely passionate human. And for those you don't know former college basketball Hooper Corey really happened. Happy on a day to thank you for being here. >> No, man, it's an absolute pleasure. Me, Max. It's It's kind of crazy how our relationship has evolved throughout the years. Ah, start with Diem. You know, that's how it usually goes, the way your T shirt and he's got hair. So I wish I was that God, like I got it down here, but I got it out talk. So don't worry, Max. I'm going to make you a T shirt and I'm sending Teo. You said >> make a T shirt. I >> will wear >> until you plant cast with you again. >> Be careful with the pick. Might be >> way careful with that. Wait. Speaking of that, Corey, I mean, before we went on air here, you have a little story about your beard. And not to say you're only known for the beard, but the beer definitely is a staple in the slashing. Your appearance give me back for that. I want to hear it, and they will dive into some of the science. >> Yeah, man. So as far as the beard, I mean, it started at you. Maybe we're on a Spanish tour went overseas, and I did. One of those crazy handlebar mustache is right. I mean, it was gnarly, but being overseas just didn't shave, right? I mean, we're there for almost a week and a half, and I just started growing out the stubble. And then people are like, keep it going. And so I kept going and we were winning a lot of games. And then we end up winning a championship. And so it became like the tournament beard or became like the season beard. And so I just kept rolling it from there, and yeah, that's that's kind of where the beard is stated for now. And then when I realized, like if I could, it almost looks like a cancer patient. So I needed a key because he's blond eyebrows, man from five feet away. It looks like I'm ball period like I can't grow here. So, yeah, that's where the beard states is at this point. >> Well, Iet's fifty. I'm getting mine going. I'm not going to your caliber. I keep it trimmed, but it makes me feel like I'm a scientist or something. If I have a beard, makes you more intelligent, but getting off the topic here. When it comes to developing anybody, people say, you know, athletes, athletes, athletes athletes are what zero point zero zero one percent of population when it comes to developing anybody at all. We got talking about the bass aspects of human movement human development. You have an interesting take on this, and I don't want to spoil it for the listeners. I'd rather have you say it first, cause I'll just bastardized and screw it up. You're going to take on developing anybody regardless if they're an athlete or just general population, >> right? I mean, if you look through human evolution one or two things that we used to do, I used to farm. We used to kill things with our hands. We used to climb, you know, we used to throw things, you know? I mean, look at the the early Olympics, right? I mean, that's basically what the events wass. He wrestled someone. You ran faster than someone. You ran further than someone, and you threw some things. I and basically that's what human capacity is. So my goal before we actually trained them to be better athletes, is to make them better humans first, because if I can express their ability to be a better human, then they will be able to express their ability to be a better athlete. >> Joshua and with those movements, selections. If you have unique choice food people who don't follow up Instagram better weigh on your instagram handle at the end. But the selections of exercises you pick, it's not traditional a sense. Let's load a bar up. Let's do a hand claim you really take ownership of different shaped objects for that way, whether it be a yoke, whether it be a kettle bell, how do you come up with the most movements? Elections? What goes into that decision making? And for any individual out there, whether they are fast ball player who's seven one or a guy who's five eight, how do you decide which of those implements are best fitted for you? >> Well, everything that shaped the way I believe is one hundred ten percent based off my environment. And look, I played college basketball. Don't look at my stats. I was not that good, but I trained in or I've played with, and now for ten years I've trained that basketball athletic population, so you can imagine with me. Okay, I'm five foot ten. Very average, at best, especially with my links, man. Now imagine six foot six, but a seven foot two weeks man and all those things that I was good at, clean snatched jerk. You know, I was a purist in the beginning. I mean, of course I was right. I was just learning what strength iss How to be strong. Now, I'm trying to imagine further. Like, how do I have impact? How do I have quote unquote transfer? What? I'm trying to load these freaks. I mean, these guys are not normal human beings, right? They got seven foot two wings fans and short torso, so their levers are crazy. So now I'm asking them to do the same things that got me strong. Being at five. Ten, it just doesn't make much sense to me now, Not saying they don't have the capacity to do it mean help. Be honest with you. Some of my best weightlifters actually been seven foot tall, But that being said, if there's a way I can load them, that makes a lot more sense. That's easy to teach. I could do it often, and it's right in their comfort zone now, not comfort as in like we're not training hard, but like in their center of mass, where they can actually manipulate loads heavy loads at that with decent speeds. Then, yeah, I'm going to do that. So, for instance, we look at a bar bell, clean snatches all good. Why can't we do the same intent with a trap door? I mean, we could still pull. We could still triple extend and then we can still catch in that power position. The only thing that changes is the complexity of the movement. Now I'm not manipulating myself around a straight bar bell. It's in my centre of mass. And now I, Khun Express quote unquote force. Ah, lot more efficient, Effective. So now I can load it more loaded faster and do less teaching. Yeah, I do that. That makes a lot of things So that's really what it came from. And then to be honest with you, But how do you experience that light? How do you know a seven foot feels like? How do you know? And so you know, I've dabbled town some ways too. Open up my consciousness, if you will, to allow me to feel that ord, allow the imagination, my creativity to tryto understand what that could feel like. And then, of course, obviously feedback from my athletes. But I mean, why you always see, like the old school dues were just like, Oh, this is weak. This is squad. We we box what we what do we do? Whatever to get strong. But it's like, you know, it makes sense. If you're five foot six, it doesn't make much sense if your seven foot tall so you've got a truly find ways to experience it yourself. And now by the means that you do that probably not going to talk about on this podcast. But the way I did it work. >> Yeah, well, we'll refrain from diving that specific. I'd appreciate it on because to each his own one of the things you mentioned like talking about Hooper's I played basketball. I played your Batch three point shooter. Anyone's listening, too, By the way, when my feet are set, I'm not. I'm not an athlete, but I could shoot the shit out of basketball. I'LL be very blunt with you. I've >> been on the receiving end of that on one of our own game. You don't have to talk when you busted my ask way >> down to like. A lot of basketball players are bad movers, and what I mean by that it's their very good when you put a ball in their hands. That is something you talked about, too. But when you get them in a dance room right there, a lot different than football players and I mean by that is you don't see a bad end zone celebration, right? Want touchdown dances look really good, Odell Beckham being very soon and a lot of it's because those patterns are done without a ball in their hand. This is my opinion and they're very primal and natural with a minute and basketball everything's doing the ball in their hand and then when they start to move, especially because they're developing this, you starts. We're like a third rate. Now they have to only play basketball. And typically you don't play football and basketball, especially football. The high level, because you know you prepping for the basketball season itself. >> You get that deal in Scotland. Shit, bro, >> You have to play basketball for every waking hour the next fifteen years to get there. I'm kidding, but I'm thinking about my head is we're not exposed to those different movement. Parents were stuck in this ninety foot unless you're how light is forty six feet, something like that with court that really constrains how we move. And then you put someone in a waiting room where all the son of dealing with external loads and very unique movement patterns you get guys who just looked walking and I think you talked about this on different podcast, but I want to get into a little bit. Here was, I think so. That stems from our coaching of a young athletes and our physical education that we no longer does. Have we used to have back in the day and how that's really affecting athletes as they get older. >> I couldn't agree more. I mean, I get these quote unquote specialized athletes. And to be honest with you, I don't have athletes like I have guys who have a basketball in their hand. They got really long levers and they have some skill, right? They have some skill to be able to go from point A to point B and put on orange round ball into a cellar. That's that's so happen to be ten foot off the ground. That's what I have. I don't have a true athlete who can pick things up off the floor who could sit down on the floor and stand up, who can throw things who can sprint, who could jump onto things. I mean, some of the best vertical jumps that you see in basketball are not even close to what you would see in football and track and field. When you think this is a sport with the high flyers counter movement, jump hands on hips averages that I've seen on teams eighteen inches and everybody is like Oh, that's terrible But that's a true counter movement jump with long levers. So now if we add some momentum to that and add a seven foot two wingspan and then all of a sudden their elbows above the ramp. Right? So that's the difference we get. We see this a NRI or this false thought, or this false vision of what athleticism is because they're so long. But in reality. And then you put a bunch of cornerbacks out there that would be really special to see, because these are guys that are like five foot ten and the most explosive fast dude you've ever seen. There's don't have the skill to play basketball. So you know, with the way we are, physical education is set up now, obviously has been chopped in half, half, half so no more education. Physical education is what we get to. They only play one sport. They sit in chairs that they're not really made to be. They live in this wart western society where every chair they sit in Is that it? His ninety, which for them is more like this, right? And then they get up and down on these beds that their feet are hanging off of. So I don't know what sleep looks like for that. And if you saw my guys get on an airplane, a commercial airplane, you would be cringing the entire time because they're literally bundled up like this. And so not on ly. Are we trying to correct childhood development? I'm trying to correct what they deal with on a daily basis. Just walking the class. We watching my guys duck through door frames constantly. It is like some some of them are guards and they're ducking through frames. And you're just like I don't know how you've made it this far without knocking yourself out. So there's so many that it's really all about the environment and her. When I've trained my athletes, it's all about giving them the environment they have never had. So that's why we utilize the resting room. The gymnastics room. It's soft had so they know, so they don't necessarily fear the ground. They don't fear their interactions gravity. So now I'm giving them the ability to learn how to change levels. You know, little guys. So I don't see six foot ten guys wrestling, right? So I have an opportunity. Now they learn how to interact and change levels, and then even more so you put somebody with them. So now we're like pushing and pulling, just like you see in football. So now they know where they put their feet. So now we're not stepping on feet constantly looking. I mean, God, Hey, these guys are like because sixteen seventeen shoes like, of course, I'm going to step on each other's speed. But if they have that awareness in that sense of where other people are, then maybe they don't make that misstep. Or maybe they get their self out of harm's way and then even more so just learning how to fall. They learn how to fall properly from standing toe floor transitions. Then, when they jumped through the air at forty two inch words, whatever you see, that's make believe for you. Switch vertical right word, but and then they get hit in the air, and now they've got to figure out the most effective way. Not the break there. Nash. Well, most of the guys are going to do everything they can to stay on their feet. Well, that's where you want to get blown out, right? So now if I can give them a tumbling strategy, so now that they can interact with the floor a lot more smoother, athletic, well, then maybe they have a chance to not get hurt and be be back in the action, right? So it's performance enhancing as well as injury mitigation. >> I >> know that. I mean, I don't know where to begin. I have about nine comments off that. First. I love the idea of talking about how these guys are living in a world built for some one, five, ten. I'm six two and Kelsey, my girlfriend. But, hey, can you reach above and grab the top? Can apostle whatever I'm like? Yeah, Okay. But you look at a guy until you actually play hoops. I think, and really appreciate how big these dudes are. You play. It's a guy who's seven one. You look at him and go, Oh, my gosh, like that's at a different human. And then you know his shoe size next to you and you shake his hand and you get to the other side of his hand. You start to understand, like, who we dealing with here, right? You look at these, you know the body needs to heal when it goes into a stress or whatever, and we're putting these guys in positions that the body would not otherwise deem for recovery right now, like this call. Time out. Is that the funniest thing? MBA timeouts. Aside from LeBron James, that's got the nine foot chair right? These guys come out and these will stools that are too small for meaning, and >> so they're not really >> rusting. And you got a dude who's trying to recover his heart rate, but really the whole time, he's in a hip flexion. He's never been in the past, you know, thirty years, right? And if you're thinking about really taking care of an athlete, we spend so much time in the weight room and all this great stuff we can do. So Muchmore. If we had a liberty, too, I use we usually more like you, um, to you, then develop an environment that conducive to them. I know University. Kentucky did that. If you look at their dorm rooms, they had ESPN going on two years ago when they built at the new facility. For the basketball players, the sinks were higher, the magical tired, they were longer. And if you ever wash a guy who's seven foot dragging on the water fountain, I mean the amount of spinal flexion he has to go under. It's ridiculous. The guy's curling up in a C. And I mean, that's crazy to think about because the whole time on the way we were talking about how do we get these guys in a position that they can function successfully? And right now it's like optimally because obviously would have been something we did fifteen years ago to get in a position, right? But how do we get them to be successful? So I pose the question to your court. I'm gonna give you the keys to the castle. The kingdom. Okay, Philip, um, maybe not the whole environment. But there's three things you like to change the outside of the weight room that you had the crystal ball and you could go either back in time more just socially. Okay. I want to change his guys. You know, the size of his car. You know that the chair he sits and we're three things that you pick and dio >> number one. I would get them involved and dance or martial arts as their first sport. That would be probably number one so or gymnastics something. I don't care how tall you are like Who cares if you're not trying Win a gold medal at three, Right? Is just learning how to do those things right? Understanding your body number two. I would change how physical education is and in western society, um, and then number three. Let's give you something actual physical number three. If I could make what? I >> got some for you. Well, you're thinking, OK, I got you want to think your third for me? Basketball players eat horribly. You're so single, teacher. Yeah, basketball players, at least by team. And I will make this universal blanket statement. They just don't like to eat for some reason. Right? Who for? Three hours and drinking game and call it good. And I don't get it like I have a fat ass. My play. I gained weight in season. Really? Team he'll know what a food I take over which you're pulling their postgame meals. And that's when they remove the snack girl. Remember the snack role when, uh, >> you know, you have todo I had Taco Bell, bro. Like we won. We got talking about, you know? So I asked the level Appalachia, which we suck. >> I think I'm going to go a little. Can't you apologize? We're going to go play and that's a D three hoops. That's finest. We're rolling to a game. It's up north took a four hour drive and we stopped at the rude crib an hour and a half before taking a corner booth buffet of ribs. They got a bunch of island boys here. The rib crib you bring up platters were basically, you know, and capacity. And when they get like five points because our center had to pull out the throat at halftime. >> Yeah, it is. Did you ever have to drive the team ban? Because I have ways in the backseat in the bag who thought that was, like level once again, level athlete, that unreal. But I would say that the third thing Don't be wrong. Yes, food. But if there's a way, I mean, if there's a truly economical way across the board to just look, it got health, we could do that, don't care. But I can change your environment that could change your internal environment and will, And the number one is if I can just poof your gut and I can look at everything, then that will be the number one, because just a little moving world. But I don't know how you're absorbing it. I don't know what's going on. And then you wantto talk about these kids that you know, a phD or these kids that are super restless. Well, I think it starts with the gut, because if you're got health sucks, so does this. So that would be the third thing. >> No, that's crazy That way. May I have a little bit of experience is our company. I don't deal with the actual read now that the things I've learned and seeing the idea of taking that integrated approach. So hey, let's actually look at your stomach. Yes, you have to collect your poop three times a day, and I'm sorry. If you're going to do that, you can start to look at what you produced and way of excreting and whether or not you're absorbing what you need to absorb. And we start looking at injuries and no tendon, health and muscle tissue, everything as a holistic approach. What? We gotta look at the internal environment if any of our environments messed up inside and we're trying to impose a stressor on the body. But we have no idea what the internal systems like, and you have certain deficiencies or certain aspects that your lack and these were certain areas where it again people go, Oh, that's not scientific. There's no study. Well, unfortunately, if you understand complex systems and their dynamic interactions and not to get too detail, I'Ll explain it as simple as I can. But what happens is we have an outcome like a strange angle, and we say, Oh, and go weak angle get hurt, right? Well, kind of grooming. Or maybe it's ankle week. That's a risk factor. Athlete didn't sleep enough the past three nights. Risk factor Athlete had some sort of physical contact during the game. That critter there system risk factor athlete. Nutritionally, it wasn't recovering from previous workouts and games. Risk factors so happens of all these risk factors, and that's just a very there's no all the risk factors. A lot involved, all but these risk factors come about and then we have the probabilistic nature of something toe happen. So oh, how likely is it that something bad will go wrong and we see the last straw on the camel's back sprain an ankle and we go a week. But maybe it's didn't sleep enough Ankle week. All this other stuff and that ankle sprain. For people interested in complex systems, it's called an emergent pattern. So there's a common pattern that occurs when you have things go wrong. So if the money C l it's like, Oh, gluten medias is weak knee Val Agus. All right, you're a muscular control all these things that go into and nothing can pinpoint it. So if we're including these bomber, you know about mechanical factors and Eve Alvis, why aren't we including some internal factors like gut health Or, you know, the blood wood for the micro nutrient efficient season? Yes, I know I'm not versed enough to speak on micronutrient deficiencies and our interactions off, you know, health and whatnot. But something as simple as college in environments haven't adequate vitamin C for, you know, ten and healing instead of, you know, repair is obviously a factor. And so when we start looking the bottom, we gotta look at the big picture. It's not just how your knee bends. It's not how you shoot a jump shot. It's not how you land every time. >> Where are you? Our body is so much more resilient and durable than you. Give it credit for me. We've survived as a species. We're a very long time. You're very harsh conditions and you're going to tell me it's that one jump that got you one job. One job is the one that Oh, that needs a little dalliance. That's the one that got you. I mean, if you super slow mo A lot of these great expressions of physical capacity in sport it was you would be like, Oh, my God, they're neither this there that But in reality, like that's I'm close to the reason why they like break or don't Break. And Jordan shallow, brilliant dude, He gave me this metaphor. He was saying to Philip, a pond, Well, it's like this fungus that will Philip a pond and it doubles its size every day. So if it starts off it like, you know, point two, then the next day be point for and he asked me, he's like, Okay, if it's going to Philip in thirty days, Philip, the whole pond, What's the day? It's half full. Then I thought for a second it took me a lot longer than I should have thought about it. But he's like, but he an injection goes day twenty nine. I >> don't want an answer, by the way. >> Yeah, was like Day twenty nine I. That's why I look at the human body like that is literally the last thing and then pull. And so it's all these. We could have had all these interventions from day to today twenty eight or day twenty nine. Even the notes that one just last. Ah, strong. The camel's back to just there goes, you know, And that's what's great about being in the collegiate setting. And being a Stanford is we have a lot of safety nets for our safety, and that's if you will. So we try to have as many quote unquote KP eyes and objective measurements to give us an idea of what could possibly happen. But in reality, it's still the dynamic environment, so I don't understand. Like I can't account for school. I can't account for their sleep. I mean, we could through, like, grouper or or whatever, but it's not realistic and thine and are setting and in their gut hell's like way picking up poop. Three times a day. They were not drawn blood once. We're not doing these things. So unless we're doing that, then you're just trying to create most resilient, durable human beings so they can withstand the stressors some more than others. But hopefully have a successful season. >> No, that's like I hate to break it to people. We don't know what we're doing. We're doing our best. I think chase Wells with him. A Stanford. Get a great line, he said. We can't guarantee success. We can almost guarantee you're not guaranteed to fail. And what I mean by that is that you can't always KP eyes and really, we're looking at. If you jump nine inches, we're probably not going to be very good basketball unless you're seven. No, right. And so we're looking at the human system as a means of understanding what is going on really lagged behind in regards to your performance assessment and what might be hindering you in regards to launch into no tracking? Can I get a little bit of data? A lot? The way explain it is kind of like I don't ask my girlfriend Kelsey, how she's doing. Once a week, you know. I asked her every day and why I asked that every day is to realize, you know, all my clothes that I left out pissing her off. You know, I did. I forget that we're supposed to go on a date last night. You know, I might not have forgot a wallet last night. We went to dinner from now on, Accent, all supposed to buy. But that's a true story. WeII >> brought up. I mean, that's the most important thing is you gotta have feedback daily, right? And wait here. It's really simple. We take a controlled environment, do some things in it before they go into a dynamic environment, which is basketball games of basketball practice. So what we do is we call that microdot. It's our way of training. Every day, in some form or fashion, these individuals come into their work, their human capacity, a Siri's, if you will. Then after that, they go into their B series, which is complex. This is really what I know what's going on. I don't get me wrong when they walk in to get their weight, are joking or making eye contact and get that handshake. How firm is that handshake thes air, All the quantitative things that I'm trying to pick up as they're coming through the door. Then you watch them say We're hitting clean, complex and they're going through the motions and their consulate changing grip or or the pool isn't looking too good, and any sharp today will boom. That's my control Now. It's not the most objective feedback, but at least it's a constant. And so that's my way of having once against safety nets from a safety nets and then weekly or depending on how many games we have that we do, our force plate jumps. So once again, another safety net, and then we have our connects on day. So our GPS data that they do on the practice gym once again any one of those in isolation doesn't tell me much. But if I have a bunch of them, then I can at least paint a better picture from quantitative qualitative, and then I can go and knit. Pick what I think they're intervention may need to be, and so it's not going to be perfect, not even close, but as long as you have a constant and yours is beautiful. Like you said, Just something simple. You get daily. Hey, how are you doing? And you know how they express that. I'm doing good. I'm doing good. I'm cool. I'm great. Like, you know, what there was in flux is are like, you know what? They're how they're truly feeling. Just based off that one question alone. But once again, if you can set up your system or your program or whatever toe have safety nets for your safety nets, then I think you can You can catch a >> lot of those along the way. >> Yeah. No, that makes sense. It's how you provide context to a situation. And the more information that we can apply that we didn't classifier more to a system like jumping is, you know, your lower body strength and your verbal expressions, your most emotional state on DH, maybe even sweep or other things that go into that, the more we could understand what's actually happening to the person. So I was kind of really bad for a second. You said some of micro dose in and term overdose. You refer into training a little bit often. Yep. And Corey is well known for this and for those at home listening, I'm going to my best to explain it. Short weeks. I got a question off of it. If you know, explains it will stay here for another hour and a half because great to listen to. But I want Teo a little bit of a different direction off of athletics about it. Firstly, micro doses the idea that we're applying a moderate level toe, low level stressor consistently, and that adaptation occurs from the aggravation off those dresses over a period of time. So we're never going to Hi, we're never going to low. And the idea is that training in the weight room is only one small piece of your life. They even programmed High Day, and you don't sleep that night or you have emotional stressor for your case, your practice. Then all of a sudden, that high, big, magnified and starts spilling over the bar and becomes too much the idea of micro dozing, especially a non controlled external environment where it's called life, and we're trying to apply enough that you can handle. If someone's feeling good, then they can push a little bit that they themselves. Now My question for you, Cory, is I love an athletic sense. I also see it being very applicable to anyone out there general population and especially in terms of I got two things. Us too. In terms of one, someone learned a movement. You get a chance to do it often and daily and someone who wants to learn how to be in the weight room. And secondly, because there are, let's say we do it eight out of ten days. If you only miss one day, you're only missing ten percent of your entire workout, right? So instead of doing looking at this whole one workout one day, you look at like a ten day period. If you got eight days of pick from and you just can't do one, you only missed ten percent versus if you only had five days of pick one and you miss one, you missed twenty percent, right? And so now we have the ability to be more flexible in our environment. So how does that fit in like a general population? If it was my dad or my girlfriend trying to learn howto use some of this micro dose in the weight room. How do you plan? >> So one hundred percent with micro dozing. The reason why it came about was it was a solution to a problem. My problem is I don't have enough exposure to my guys. So how do I create more training frequency? And now we got rid of warm up something that was just kind of getting them ready for practice. That kind of don't care about it. The coach hated seen me do it. I personally hated doing it. So now it was a solution. What it turned into was motor learning. Now you want to learn how to train, will do it all the time. So that's where complex comes in. It's the value of orcs work, right? So basically, you take a bar bill and you do every movement that you would do in a weight room, in some sense, in one set, so you'd hinge You do a hip flexion. You do a press, do a pool. If I break down each one of those into isolation, it would look like already else Squad, Polish, military, press or row, those air all movements that you would do and if you separated each exercise in an isolation you would go more resistance on, just like you would see in general fitness, right? Like we're going to do three sets of ten on bench press or three sets a tent on back squad. Well, that's great. How about we just put it all in one and now we have more exposure. So now I'm learning how to do the movements, and then you can't tell me that doing one thing once a week is actually going to make you learn the movement. So now you learn those little small video sequences that you see with thirty year experience power lifters who truly understand, like, move from body, this foot stance, or this is how I start to hinge here within my squat X degree. And that's how they perfected is because they have so much exposure to it. So we're doing the same thing. We're just trying to create exposure at lower thresholds and and in doing it often now as faras general population, what's the number one concern? But I don't have enough time. Oh, really? You don't have a thirty minute today, twenty to thirty minutes a day to not kind ofwork. Now. Every day I call B s. I say You just don't want to train. So that's where my producing to me is beautiful in the general population is because it's living the way you start your day. It's lunch, or it's when you get off work. Perfect. You can pick any of those three slots twenty, thirty minutes. You can eat and shower and get backto work or before work. So you can't tell me that everybody doesn't have that situation. So now, creating training frequency, you're getting enough volume throughout the week. Now we have on and then most importantly, like you brought up if I just had to miss that one day, it's ten percent of my training like it's not well, only train twice a week, So fifty percent of my training is gone. So that's where I think it's beautiful. And that's where he could work from general population to the most elite athletes in the world and the reason why I say the most elite athletes in the world because I just so happen to train to of So I do it with all these populations
SUMMARY :
Produced from the Cube studios. And for those you don't know former I'm going to make you a T shirt and I'm sending Teo. I Be careful with the pick. Speaking of that, Corey, I mean, before we went on air here, you have a little story about your beard. So as far as the beard, I mean, it started at you. When it comes to developing anybody, people say, you know, I mean, if you look through human evolution one or two things that we used to do, But the selections of exercises you pick, And so you know, I'd appreciate it on because to each his own one of the things you mentioned You don't have to talk when you busted my ask And typically you don't play football and basketball, especially football. You get that deal in Scotland. And then you put someone in a waiting room where all the son of dealing with external loads I mean, some of the best vertical jumps that you see in size next to you and you shake his hand and you get to the other side of his hand. So I pose the question to your court. I don't care how tall you are like Who cares if And I don't get it like I have a fat ass. you know, you have todo I had Taco Bell, bro. The rib crib you bring up platters were basically, you know, and capacity. And then you wantto talk about these kids that you know, a phD or these kids that are super restless. to look at what you produced and way of excreting and whether or not you're absorbing what you need to absorb. I mean, if you super slow mo A lot And being a Stanford is we have a lot of safety nets for our safety, and that's if you will. is that you can't always KP eyes and really, we're looking at. I mean, that's the most important thing is you gotta have feedback daily, and you don't sleep that night or you have emotional stressor for your case, is because it's living the way you start your day.
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Mitch Gudgeon, TalentFit AI | CUBEConversation, March 2019
(upbeat jazzy music) >> From our studios in the heart of Silicon Valley, Palo Alto, California, this is a Cube conversation. >> Hey, welcome back, everybody, Jeff Frick here with theCUBE. We're in our Palo Alto studios today for a CUBE conversation. You know, every place we go, a lot of the conversation is about the future of work. And oftentimes it's really in the context of the tools, whether Slack, or Asana, or Facebook Groups, everybody's trying to get into this. But there's a lot more to the future of work and is really about talent, to getting talent, a hyper-competitive talent space, it's about culture, and ethics, and morals, and especially some of the stuff that we've seen recently, with what happened at Wells Fargo, and obviously what's goin' on at Facebook. There's a much more complicated part of the story in terms of the people side, and we're excited to have somebody who's applying kind of AI, and all the technology that we talk about all the time with the shows to culture, and so for the first time, we'd like to welcome Mitch Gudgeon. He is the Co-Founder and CEO of TalentFit AI. Mitch, great to see you. >> Hey, nice to see you Jeff. Thanks for having me here today. >> Absolutely! So before we get into it, because a lot of fun stuff, just give people kind of the quick overview of what you guys are all about at TalentFit AI. >> Yeah, definitely. So we make it easy to find the right person for your context, so your culture of your organization. Basically we take an evidence-based approach to calibrating your culture, and then quantifying culture fit, so you're actually reduce bias for the hiring process, at least through the phases that we take you through, and then ultimately you end up saving time, energy, money hiring and retaining the right people. >> So it's both the culture at the company, and then then it's the culture for the applicant, and trying to make a match. >> Yeah, basically matching their ideal cultures, so what they want to get, their sort of fundamental values, their needs, the norms that they have, and then matching that to what the company actually has internally, not what's necessarily written on the wall for-- >> Right. (laughs) I was going to say. I would imagine the first big point of conversation, what so you do a culture assessment at a company, do you come at it from the company point of view? Or more from the employee applicant point of view? >> Yeah, so we actually start by calibrating the culture by understanding what the culture is across the organization based on employee feedback. From that, we're able to extract that. We use some validation stuff, based on performance, based on, you know, engagement scores, other things like that. And then from there, anybody's an applicant who's applying, we can actually help them actually, or help the company actually assess, do they actually fit this company culture or not-- >> Right. So I would imagine it's kind of like reputation, right? You think your reputation is not what you say it is, it's what people talk about when you're not in the room. And I would imagine when you're doing kind of a culture assessment, there's one just figuring it out, but I got to guess that there's a lot of times where the culture data that you collect based on real data, doesn't necessarily match what maybe the leadership team of the company thinks it is. >> Yeah, it's actually funny. That's kind of the inspiration for why I even started this company in the first place, is I actually finished my MBA and joined a company, and for me it was like, we went through the hiring process, did all the due diligence, and realized once I joined the team that, my ideal culture wasn't exactly what the culture was in the organization, not saying it was a bad culture, just saying it wasn't the right place for me. >> Right. >> And (mumbles) you know had the right personality traits and what not to do well in the role, at the same time I wasn't able to actually sort of feel that I got what I needed from the company, and then probably from me too, so, you know, it's one of those things. We help you basically not go into the wrong situation where you're not in a good place to succeed too. >> Right. And do you talk about a bunch of things that kind of determine culture, so there's the plaque on the wall, you know, as you walk in the front door, but it's really, and you outline it a bunch on your... it's the norms, it's the behavior, it's how people are rewarded. So there's a bunch of real discrete things that you guys can measure through your process that actually define culture in a way that you can put numbers on it, and you can compare Culture A to Culture B. >> Yeah. >> What do you see as some of the most important things, or where do people usually miss between what they think is the culture and where they execute the culture? >> Yeah, it kind of varies from company to company. So we use a thing called the cultural signature, this is saying that you and I can both sign a check, hopefully both our checks are going to actually pass and they won't bounce, but your signature is no better than mine, mine is no better than yours, it's just unique, right? To your own situation. And sometimes you'll see that leadership especially may not be in touch with what the culture of the organization actually is based on their employees' feedback. And so this is what we kind of do, it's kind of like understanding what the culture is, seeing those gaps between what leadership thinks and what it actually is, and then leadership, if they do care about culture, which most of our customers would, they can start making those appropriate changes to get to their aspirational state if they want to. >> Right. And then when we first started were getting ready to do this interview and I was thinking to myself, well wait, if you're just bringing in people that kind of fit the culture, are you just kind of going birds of a feather, are you missing the opportunity of what's so important right now in terms of diversity, diversity of opinion, diversity of background, diversity of point of view. But you're saying personality fit and culture fit are two very different things. So how do you look at the difference between personality and getting diversity in the company, which is good, versus getting cultural misfit, which is not good? >> Yeah exactly. So yeah they're definitely very different things, and there are some ties to it, but you think of people often associate with culture fit as hey I can sit down and have a beer with you or we talked to a couple of companies like hey, are you a gamer? Then you'll be able to work with us because you fit our culture. But that's not really what it is, right? At the end of the day it's about these fundamental values that you have within your organization. You know, what you actually want out of the organization, and that it's matching your needs. So and we actually have an advisor who's one of the top diversity inclusion people in Canada for a global organization, and she's also helping us through this process of ensuring auditing our algorithm, making sure that we're taking the right steps, and managing and ensuring that the we're tracking demographic data, so that we actually do not have bias in our algorithm at the end of the day. So, it's kind of where were going. >> Yeah, so I'm curious about where the bounds of the culture in terms of number of people, if you will. So, there's obviously, do we fit as an employer and employee? You get along with your boss, you have a culture. There's your group that you're intimately involved with, who you work with with day to day, whether that's, I don't know, six people, 10 people, I'm curious if there's a natural bound, and then maybe you're part of a department, and obviously if you work at a company like Amazon, just to pick a name out of the hat, they have over 600,000 people. So where the limits of culture, or can they successfully span from all the way at the top, all the way down to those little micro groups? >> Yeah, so usually we think of it as there's core culture to the organization, and that's kind of things that are aligned across the entire organization, right? So you think of person organization fit is how they define it in their research. You get into things like person group fit, so this could be the specific team you work on, and there's also cultures with the sub-cultures in the teams, so the way we've built our algorithm is actually taking and being inspired by pieces of research, that actually look at group fit, look at organization fit, and then be able to match people effectively sort of both of those. >> So you try to look at it all. But at the end of the day, is your probability of success within an organization more determined by that kind of close intimate group? Or the bigger group because then maybe you find a different path if that immediate group doesn't work for you. >> Yes. >> What do you find? Yes, so right now we're still pretty early stage, right? So we're going to be tracking stats and seeing how people actually fit to the overall organization, how they fit to the groups. Right now we're doing matching to specific groups and teams, because there are sub-cultures within the organization. Those teams will still have those core values of the organization too, but things like their leader may be a bit different, the way they manage their people, right? So that's kind of what we're looking at right now. >> And do you find that senior leadership really understands the importance of culture? Because you mention it in some of your posts on your website, and some of the articles that you reference that culture can be a great asset, right? Then view Patty McCord with the work she did at Netflix is, you know, kind of legendary, and everyone goes to that deck, it's 127 page slides. I don't like slides, I went through the whole deck, it's amazing. But it can also be a real negative. It can be a real problem, and does leadership understand that to the point where they're making the investments to make sure that culture is a asset and not a liability? >> Yeah, and I think it's changing a lot. I think it used to be leadership kind of set the direction, and you kind of had to listen to what was going on, and you had to abide by the rules of the culture, and if you didn't you're kind of gone. You know, I think that's shifting a lot, because people are more attracted to organizations that they know they fit the culture, they feel they align with the culture. They're more likely to accept job offers, they're likely to actually take a pay cut even, a lot of the research is showing. So I think those are factors that are coming into the equation now, and companies are realizing that if we want to attract the top talent, great. Everyone can pay X amount of money, right, for a candidate to join. Now at the same time, if you're being recruited by five different firms, and they're all offering the same pay, what's your differentiator, right? And so culture can be a differentiator and people, and especially leaders I think are realizing it can be a competitive advantage, right? It's going back to this whole talk of like culture eats strategy for breakfast, right? >> Right. >> And I think that's an important thing to think about is that I think companies are buying into that more than ever now. >> Right. But ultimately it's about execution, right? You got to execute it, you got to walk the walk, and talk the talk. And clearly, when it works well, it works really well, and one of the examples we use around here, just because it's so easy and in your face is the Warriors, right? Perennial losing organization, Lose lose lose lose lose. They get a change at the top, before you know it, they're the premiere kind of brand in the NBA right now, and that's really been top down, driven by Joe Lacob, all the way down to the players. But I wonder, is it more of a stick or more of a carrot? Is it because employers now have to do this, because the employment market is so tight? Is it because they're trying to get the younger kids who are coming out of the school who are much more mission driven than maybe I was when I got out of school? I just wanted to get a job and get going. Or are they really thinking more holistically, kind of lifetime value of that employment relationship with these people? >> I think it's a bit of both, to be honest. I think they obviously see the benefit from the hey we can attract the top people here, but they also see the business benefit of it now too, right? And I think that's the one thing that is often forgotten in the past. And I love the example of the Warriors, right? And I think this is one thing that the whole is greater than the sum of the parts is another... I like using these kind of phrases, right? >> Right. >> But the Warriors is a great example because they have five A players on their team, if you want to call them A players, and they're able to work together for the most part, although earlier in this season they had some issues with their culture, and if you probably look at the winning record there, it was actually pretty low probably during those when they're having issues internally. So I think it's one of those things. You can also help players even level up, so it's like you don't have to recruit that A player every time, you can actually make a B Player on the right team that they fit into turn into this kind of A player in that situation and that context. >> Yeah, last question, before I let you go, because I think it's another interesting thing that's happening is this blurring between professional life and your regular life, and we've seen it with hours, right? Nobody's working eight to five anymore, because you've got meetings with Europe, you've got meetings with Asia Pacific, you've got meetings with the East Coast from here, so people are on and off the meetings all the time, you're on and off your phone, you're getting Slack notifications all through the day. And at the same time, people want their employees to be engaged and feel part of that. They want them to retweet the company line, but they won't necessarily give them the rights to retweet in the name of the company. So how do you see the motivation of people and this blurring between professional and personal life, and yet companies want employees that are bought in, that are kind of emotionally vested, into these mission driven cultures? Do you see more conflict there? Is it working, or what should people be thinking about? >> Yeah I think it really comes down to what people want at the end of the day too, right? If you don't want to be in tapped in all the time, then you probably don't want to fit with that, or you're probably not going to fit with that kind of organizational culture. And there's lots of other companies out there that may be not like that, for instance. So I think it's one of those things. You really just have to understand like what do you value as an individual? What is a company's value? And then, how do those things align for you? And do you want to be on your phone 24/7, or do you want to... and have the flexibility you know to be able to take holidays when you want? Or do you want that nine to five job that's more structured? And so what we're doing is giving that transparency to both the job seeker and the company now, to say like hey is it a fit right up front? And if it is, okay let's start taking you through the hiring process, and then if you don't? That's okay with us, because we're both not going to benefit from this. It's a two-sided street, right? So it's building that transparency and helping people find a place that they'll ideally match with. >> Right, well Mitch it's really an interesting story, and we didn't really talk about deep into the AI, but you guys are using big science and big data to try to basically increase the probability of success, because a miss is expensive for both sides. >> Yes, it's really costly, right? It's, you know some of the estimates can be up to three times salary is what it's costs when you make a bad hire. Companies, I think it was like 85% of companies say they've made a bad hire in the last year. And from the job seekers' side it's like they're more likely to accept job offers, even at lower pay from companies that they feel they align with the values of the organization. It would be pretty nice now to be able to say like hey, you actually align and the data shows this too. This is all based in top tier research too. >> Right Mitch, well thanks for sharing your story. We'll keep an eye as you keep growing and best of luck to you and the team. >> Awesome, thanks Jeff. I really appreciate you having me today. >> Alright. He's Mitch, I'm Jeff. You're watching theCUBE. We're at our Palo Alto studios. Thanks for watching, we'll see you next time. (upbeat jazzy music)
SUMMARY :
in the heart of Silicon Valley, Palo Alto, California, and all the technology that we talk Hey, nice to see you Jeff. what you guys are all about at TalentFit AI. and then ultimately you end up saving time, energy, money So it's both the culture at the company, what so you do a culture assessment at a company, based on, you know, engagement scores, that you collect based on real data, and realized once I joined the team that, And (mumbles) you know had the right personality traits and you can compare Culture A to Culture B. this is saying that you and I can both sign a check, So how do you look at the difference that you have within your organization. of the culture in terms of number of people, if you will. so this could be the specific team you work on, But at the end of the day, is your probability of success of the organization too, that you reference that culture can be a great asset, right? and if you didn't you're kind of gone. And I think that's an important thing and one of the examples we use around here, And I love the example of the Warriors, right? and if you probably look at the winning record there, So how do you see the motivation of people You really just have to understand like what do you value but you guys are using big science and big data and the data shows this too. and best of luck to you and the team. I really appreciate you having me today. Thanks for watching, we'll see you next time.
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Mohit Aron, Cohesity | CUBEConversation, February 2019
>> Welcome to the Special Cube conversation. We're here in Palo Alto, California Cube headquarters. I'm John for a host of the Cube were Mohit parents, founder and CEO of Cohesive Serial entrepreneur. Successful Distribute computing, phD, computer science. Welcome to the Cube. Thanks for having me here. So thanks for coming. You guys been very successful. You found the couple in twenty thirteen. Great traction. Great success, Great technology. What's the vision of Cohee City? >> Let me first start by describing the problem. And then I'll go under describing the vision. The problem in a nutshell, is ah what we call mass data fragmentation. It refers to the fact that everything sets in silos, whether it's the sender or whether it's the cloud All our data sets in silos in appliances. Just expect all across the whole universe. And our vision is to basically consolidate that onto one platform I The easiest way to understand our vision is to look at it. What a smartphone that in the consumer space before the smartphone came the all used to carry multiple devices, right? Phone, music, player, camera, and so on. So forth. Uh, the smartphone came. It put all of those on one platform gave us a single U I to manage it all, um, gave us the notion ofthe marketplace from where we could download maps and run on this platform and gave us machine learning. Our vision is something very similar for the world of leader in the world. That data is the most valuable resource today in the world, much more so than oil. And he had the infrastructure. Where we put that data is very fragmented. Let's look at the ladies under backups is one silo probably bought from different renders test. And there was another side of analytics is another one five chairs and object storage is another one. Our vision is is to put all of that on one platform, make it very simple. Make that platform span the data center and the cloud manager using one us bring machine learning concepts to it and at a market place from where people >> could, you know, the smart phones. A good analogy. I like that because you had a market where they made devices to make phone calls and then text messaging. Beak was like killer half of the time. But having the computer enable the whole new class of services functionality, usability and capability and that that iPhone was a seminal moment There. You see, the same thing in Tech right now with Cloud Cloud has changed again. Seeing cloud be successful. Scale is a huge thing. So functionality, new kinds of functionality and large scales with cloud computing has proven. And APS have come around that. So I gotta ask you, you know, backup has been in category that has been dominated. Public offerings dated domain, but the list is endless of great companies built great backup solutions or a K phones. And I think that's what you're getting at the phones is the backup. You guys are building new functions. I want to explain the reels, um, capabilities that's going to come out of the data because if you have data being backed up, you're touching the data. So if you built a platform for scale, it seems that you guys have talked about that product. What is the unique thinking behind it? How did you come to it? And what are some of the examples? >> Yeah, so let's start one step at a time. So, uh, even though it's a platform that can do multiple things just like the smartphone had to be a great phone to begin with. This is a great backup product to begin with. And once we've solved the back a problem for the customer, then we encouraged them to do more on this may be to file shares, baby to object storage. Maybe start using the clouds and sunset. The next thing you'LL say that. Imagine you will work on that data. So you've ingested some data using backups and you want to get some insights from that data today? What you're forced to do is you probably have to copy that data out into another side of creating one more fragment. One more copy of the data. Why not move APS to the data? But other than dated adapts. So our whole concept is that take this platform and take whatever happened. You wanted to run outside off this just running on this platform and thereby you're moving APS to the data. Not the dinner, perhaps moving their eyes. Heart. It is. Ah, is big moving abscess. Easy. So and that's what the hell is this about On That's the platform. That's the capability of the platform. It's a distributed platform. Let's you're on APS close to where that it is. That's the underlying a lot of >> people say I remember we're going back a couple years now talking about Cloud or once I want to be like Google. I want to be like Amazon because they were offering at large scale using open source software. You can. You were lead engineer on Google file system, so you know a lot about scale. But a lot of people wanted the scale and functionality of Google, but they wanted the ease of use of Apple. And I've heard you mentioned that when were before we came on. So this is actually an interesting dynamic. But not everyone's like, Oh, but they have now data scaling similar challenges that Google has one song or another's large scale. Talk about that dynamic because you're changing the game on backup did since you touching the data, you're going to make that more valuable beyond just backing up. And this the concept of moving absolute data talkabout this dynamic of scale, functionality and ease of use because if you're doing all the work with the data, why not extend that out? This is essentially what you're doing. Can you explain that? >> Yeah. I think about the problems that Google would have if they were dealing with lots and lots of fragments of data. If everything was studying in a different appliance, Uh, with the volume of data that day deal that they'LL just be going knots pulling their hair all day long, right? So they built a web scale system that was sort of like a single platform. I was fortunate to be part ofthe some of those technologies, like the Google file system. So they built that Web scale file system to make it look like make all of that look like one platform. And now that it was one platform, they could move the APP store. And we're basically trying tow do something similar to the realm ofthe second reader naps. Because we have lots and lots of data here today. It sets and silos be the backups or passed on diver filers, Object storage. We're gonna build one big platform that scales out in a Google like fashion which can be managed very simply, using one you Iike an apple like manageability. And with this concept, we become very similar to those hyper skill er's, and we bring some of the same innovations to people out there. I >> want to share a common e we were talking about before we came on camera. You were just preferred something. You said I'd like to solve one problem at a time and then move on. But what's interesting here? Competitive strategy wise, you're solving the backup problem. But why you got your hands on the data? You're actually going to re imagine the usability of that data. So you're essentially adding value to a basic function back up, putting a platform around and extending that out, perhaps to come to it. And it's kind >> of a >> land grab that's working. This is a unique It's a different way to think about, Is that right? >> So I like to say that we like the master's off one trade at a time, nor Jack of all trades, uh, and that first trade for us that we would be masters off his backups once we're happy there. Then we can go on and focus on, you know, maybe filers or object storage. And this is how we build the platform right eye. I always say that when you architect a system, you have to think about all this from day one. You can't incrementally at patches and expect the system to grow right. I sometimes draw an analogy between why Google won the war against Yahoo. Google, Tara, Phil are all as a platform there. Thought about all the use cases they'd be, you know, putting on the platform. Yeah, who just build something that was good for search. Didn't think beyond that. That's why they you know about a bunch of naps. And >> that's where they saw it and thought of >> the Google file system and then YouTube on top and Gmail on top and blah, blah, blah. No. So I was the same approach. We've talked about the problem and the problem off. The problem We want to address mastered a recommendation up front, and our system has bean architected to solve that. Even if we start by being masters of backups first, the system has been architected tto do way more than that. >> So it be safe to say that cohesive from a software core competency standpoint is distributed computing core competence or disputed systems large scale from a computer science, you know standpoint and then data. So expertise are those two is intact. >> Yes. Oh, distributed computing and distributed file systems. Those would be there to core competencies. But then again, depending on like whether it's backups or its testing, that their competences of within those domains. >> So I want to get into the private tech. First of all, thanks for saying you have responded to that. The product text. Phenomenal. You have platform can do multiple things. I want to talk about span F S on Spann Os. You have some news. You've got something share on overview of what that is and what the new news is. >> So when you're trying to control on manage of lots and lots of data, you better have a distributed file system. So we built one, and we call it Spanish Fast. The name comes from the fact that it's supposed to span nodes in the very center that's supposed to span multiple kinds of storage in the data center. It's supposed to span the data center and your multi cloud environment, their hands the names pan a fast, But since we were building it like a platform, that's not just there for your data. It also runs apse on top off this platform. Uh, the span of fast is not enough. It becomes full scale us, if you may want to call it. What? So where's it has a file system and it has the ability to run laps on the file system, and the same ability was built here. And the name's patter well, so we can store data, but we can also naps close to that >> and with multi cloud on the horizon are actually president today. A lot of people use multiple clouds, and certainly Salesforce's considered cloud you got Amazon. So especially this moment clouds of existing today in the Enterprise, the coordinated all but hybrid and and these things they're going on. Premise. It's cloud operations. This becomes an important part of the distributed environments that need to be managed. Talk about the impact of multi cloud in today's world because it's a systems thinking. You gotta think about it from day one, which is kind of today. I got on premise. I got multiple clouds out there, and some clouds or great, depending on the workload, picked the cloud for the workload. I'm a big believer in that. Your thoughts, though, on as people tried to get their arms around this and make it, you know, one environment with a lot of decoupled elements that are highly cohesive. Talk about that dynamic. >> Yeah. So Cloud is a very, um, nice entrant into the infrastructure world. It provides a lot ofthe functionality, but it doesn't quite solve that problem off massive fragmentation. When you put your dinner in the cloud, it's still fragmented. And when you're dealing with, often our customers are big. Customers are dealing with multiple clouds and the data centers, and they have dedicated people trying to move data and applications between them. That's the problem that Cohee City can actually solve very well, because we're building a platform that spans all this. Um, all of that becomes underlying infrastructure that we use. And now through us, they can easily move APS. They could easily move data. They can access the data anywhere. That's the value we been to them. We have a customer here in California, and that was spending, uh, hundred twenty thousand dollars per month. It's a new company, uh, one hundred one hundred twenty thousand dollars per month on the eight of us both after they consolidated that stuff threw us in the cloud, their ability used to seventeen thousand dollars per month. That's the kind of value we can bring. The customers >> well, the Amazon Dana. It's interesting cause you got storage and you got E C two of the compute you need compute to manage towards so against. Not just storage. That's the cost. It's it's data is driving the economics. That's where you're getting it. >> Yeah, So I think data and storage and compute go together as I'm a big fan off hyper convergence, which me, along with the rest of my team Edna tonics. And Monday it's gonna doing multiple things on the side I'm back from. And you can't do that without storage and compute both working in tandem >> so consolidating with cohesive because I'll be using cohesive, he allows the better management lower costs on Amazon. >> That's right. That's right, because we store the data efficiently on Amazon, cutting the costs, and then you can run your raps on top. You don't have to copy out the data toe, run your wraps, you can actually land on the platform and all that saves costs. >> That's a great tidbit. Notes no to the audience out there. Great to tip their pro tip. Talk about the announcement you have now have APS coming out. You got three native cohesively absence. My word. I don't know. You guys call it Think Caps is going to the Alps and then for third party application developers. So again, this kind of teases out there beyond backup story, which is platform. What of the apse, Where this come from? What? Some of the reasons why they're being built. Can you share specifics on that news? >> This goes back to our analogy to a smartphone on one of the innovations the smartphone, brother. The world was the notion of a marketplace. You could go to the marketplace and down wrap. Some of the gaps are from the vendor who built the smartphone. Some of them are from third parties. So we are. And when the first iphone came out that I had basically five straight and then now there are millions of them. So what we have seeded the system with is we have, ah, a couple ofthe third party apse for in particular one a splunk that runs on the platform with in a container. One is from a company called Menace. One is actually two laps are anti virus absent. One vendor is scented. One when is clam? Maybe, um though that third party APS But then we've built some, um, APs from cohesively itself when his app called spotlight on the security app. One is an app called Insight searches through the data when his app called Easy Scripts allows our customers to upload scraps on drawing them from Go easy. So these are the apse that I'd be exceeded the system where were also announcing an SD came in just like your smartphone has a nasty cave. The world out there can go and use that and build ups on top if he would like people out there in the world. Third parties are partners to build ups and run on this bathroom >> so moment, what's their motivation behind the app system or functionality? As the demand grows, functionalities needed. So I'll see platforms should be enabling, so I get why APS could build on platforms. But what was the motivation that around the apse now just l of evolution capabilities? What's the thoughts >> It goes back to our philosophy that if you need to do something, you shouldn't buy one more silo to do it. You should be able to extend your existing platform and then do stuff. That's what your smartphone does. Uh, basically, even you, by your smartphone, it can be a phone, and I'm number for the things. But then you extended the functionality of that by downloading maps. It's the same motivation, you know, extend the abilities of this platform. Just download maps and then extended right. >> Give the value proposition pitch for the developers out there. Why would they want to develop on? Complicity is it is a certain kind of developer. What's the makeup of the target audience? Who would build on obesity? >> So all kinds of people we expect to build on this platform. So the value for our customers, for instance, now rather than, uh, copying the data out of this platform onto one more silo and that's very expensive, they can actually build a nap that runs on this platform so that they don't have to move the data around, and it's very, very simple. That's the value for our customers. For the developers out there. Uh, it's the same value that they get when they build an app on a smart phone. Uh, they building up some cash, but out there can download that app and the APP and then pay that developer some money so they don't have to build the whole company or the whole thing. Now they can build a nap that runs on cohesive. It's really simple for them. They get a cut of whatever the customer pays, so there's value all around. It's a ven ven for everyone >> it's not. And it's good business model, too good community going to get an ecosystem developing its a classic growth growth opportunity for you guys. Congratulate. So what a business you guys have talked about a couple quarters ago Publicly, about two million to million dollars run rate. Give us the update on the business in terms of growth. Employee headcount. Key milestones. Can you share? Seok was empty, >> so you know the momentum is phenomenal. We're very flattered by the fact that despite the fact that we're a young company we've been selling for more than three years, of seventy percent of our customers are enterprise customers. The big guys with lots and lots of data. Uh, some of the biggest banks in the world now use us. Some of the biggest credit card companies in the world use us. Uh, a lot of the secret of federal agencies. You, us? Um, uh, some of the public customers I convention Hyatt uses us. Ah, big financial. Northern Trust uses us the famous. Uh uh, you know, food chain. Wendy's uses us. So those are the names I can I can mention that are actually using and benefiting from cohesive. Um, so lots of lots of great stuff. Um, we had three hundred percent year over year growth in revenue. Our head count, actually, er this week crossed one thousand people. So we spoke to our chief people. Officer. We should mention our one thousand employees in a special way. So all that great stuff is happening. >> It's like walking through the door. All the bills go office because you guys were two hundred last year. About this time >> when you get back, we are about to enter. People's a factor of five growth and about one years phenomenal had come growth. >> Well, that's massive growth. How big is this guy's a real state growing and buy more office space. >> Yeah, well, uh, they're headquartered in a building and son who's a downtown. We start, but we got it. That building about when you're back, we only had two floors were really expanded toe like five floors now and looking toe, you know, rent more. We've also expanded to other locations. Geographically, we now have an office and rally. We have ah, uh in office and cork in Ireland. We already had an office in Bangalore. We setting one up in pony. We're setting one up in Toronto, So lots and lots of expansion worldwide. Not >> really looking good as well. I mean, let's think about the economics. >> So this is the time they're being in mustard and growth. That's looking phenomenal on DH. There's a path to profitability. Um uh, it all depends on you know, our economics and what the board decides on how and when we wanna charge towards profitability, we can get there. It's looks easy, but I think it's our productive ity off our sales reps looks phenomenal. On average, productively is very high, which basically means that you know, we can get to profitability fairly quickly. If you want. >> We're going to say, very impressed with the growth and impressed that you go out on the road, talk to customers closing business. That's sign of a great CEO. Always make sure the customers are happy. >> Um, eventually, that sort of companies about a happy employees and be happy customers. Uh, and my job is to see you is to make sure what happened >> before we get in Some of the questions I have from the community. I prepare because people want knew you were coming on. I want to ask you about entrepreneurship in your journey. You've had quite the career Google image in that nutanix. And now here, >> Look at look at >> today's environment. I mean, it was a lot of talk about how entrepreneurship changed and starting a company, you know, you got a rocket ship, so you had a lot people coming on Now from the your journey you're on now. But a lot of other offers out there right now, kind of like looking transition. People say tech is bad, not good for society. Seen bad, negative press in their entrepreneurship is a great opportunity right now in tech. What's your thoughts on the current landscape and opportunities for, you know, folks out there building new things and going in solving a problem from old market and reimagining it for the new. Because a lot of new going on seeing a new sea change with cloud. And on premise, >> I would say, Um, this is probably the best time to do a company then ever in the past because technology is there to help people. Young entrepreneurs. Uh, there's plenty of money to be raised from the sea. Species are very happy to be helping. End of news a couple of pieces of caution that I wantto give to would be entrepreneurs. Uh, number one. Don't be in a hurry. Learn their hopes of doing a company first. Ah, before jumping and doing it because often I find that they burn their fingers and then they don't want to do a company again. First, go to a good company, learn the ropes of playing a company, and then do a company. That's number one number two. Uh, I would like to incorrigible and avenues to think about their ideas in the context. Off the following two thoughts one is, uh, the company needs to have a great entry point. That's how the company takes off. But then it also needs to have a bigger vision to look up to. And I often find that company's lack one or the other of these, Uh, and that's why they eventually fail or they never take off the ground. In our case, the entry point was backups, and the big vision is the consolidation off seconded and haps that I spoke about, Ah, one or the other if they're missing, it's not >> an extensive abilities key there, too. You get the beachheads real specific seconds, and then you see you point >> out of a vision. That's >> what broader beachhead without trying to take it all too fast or not knowing where to lay. That's gonna much the analogy. >> That's what I say. I beat master of one traitor, go ahead in the beachhead and then expanded the bigger >> and by the way, that's a classic proven way to do it. So, you know, just stay with what works, All right, let's get to the questions from the community. A lot of people wanted to ask your first question moment. You've a great perspective on the difference between hyper scale on enterprise worlds Is the enterprise still ten plus years behind the Giants in Tech? And how have you helped bring hyper scale thinking to the enterprise architecture? >> Um, the enterprise is, actually, surprisingly is getting closer and closer. Uh, with all the great technologies available, hyper convergence has bean. One of those technologies that has made hyper convergence combined with upscale, uh, is one of those technologies that has brought the enterprise were very close to the hyper scholars. Now they can buy products that are hyper energy that scale out in a group like fashion, and they can get some of the same benefits that the hyper scholars have enjoyed over the years, eh? So I won't say they have that far behind anymore. They're catching up, and they're catching up. Eyes >> used to be a few years ago, you could look at saying old relic, you know, modern cloud >> the and and the companies that I have found it have. I'm very flattered to say that have gonna, uh, hasten that journey. Uh, happy convergence. And he's even solving this problem of massive fragmentation. The hyper skills have kind of, you know, already solved that problem. They have massive, upscale systems that don't deliver data fragmentation. It's one platform, and you're gonna bring that value to the world through cohesive, >> great, great success. Okay, second question. There's a ton of money pouring into the data protection space again, a category that's there's a card in magic water for that. But again, you start Cummings that don't have magic watches because it's new. Why is this money pouring into space? Why now? >> Number one dealer is exploding. There's lots of lots of data. Ah, bulk off the data sets in what we call second story. It comes to it through back up straight. Your your production stuff has some production data, but eventually that data. Nobody wants to believe that they would keep it in there for at least six seven years, maybe forever. All dated, it comes to backups. The opportunity that people have seen is that they can actually now doom or with that data. It's not just dumb waiter sitting there, so it's not just data protection. It becomes more of a data management and you do data management through APS. That's what cohesion is exploding. We get the data onto a platform through backups, but then we expand into arrest of the vision and Kendra naps to extract value from the dealer right? That's why the money is coming. >> Well, you just answer the next question, which is, you know, why cohesively wind now the space is crowded, a lot of competition, So I'll just move on Ransomware, what's going on there and what's unique about Kohi City and what do you bring to the table with respect to Ransomware. >> So Ransomware is, uh, uh, something that we now live in. Its every enterprise is at risk, uh, being affected by ransomware. So what we have announced recently eating a month back, we announced our ransomware support. Uh, we can offer not just the detection, but also a number for the things we can detect Ransom where we can allow our customers toe apply fixes. When When that happens, we really allow things to be recovered once ransomware happened. So it's built into our data protection environment, right? That's how customers like it. So it adds value to the data that they already have. It's not just a dumb backup. >> And with all the third party and S t k stuff happening potential extensive bility on that core, >> that's right. Now we can have apse that can detect more round somewhere by virtue of the fact that we can support running absolutes to data. Some of those APs could be Andy dancing, perhaps help protect the data, do some custom stuff. Once said handsome, it is detected. All that becomes possible >> last question from the crowd here, the community multi cloud. Everyone's going up to the space. What is multi cloud data protection really about? And why cohesive? Isn't this just really a multi cloud vendor? Khun, do it all mean a lot of people saying they're multi cloud vendors. Y you what is multi cloud data protection all about? >> So, you know, big enterprise customers probably have a foot in every cloud, and they call it a multi cloud infrastructure. And if they want to protect the data and forced me, the data is very fragmented. So they need a backup solution for one for every cloud that's roughly multi cloudy. The production. Uh, we're cool. Here's the adds value. It's building one platform that spans your multicolored environment. So one platform can now take care ofall that those backups eso it really simplifies the job off doing backups or data protection in a multicolored environment. And that's where the Queen's devalue comes in. >> Well, congratulations. Final question for this interview. How would you summarize the state of cohesive the right now? Thousand employees growth on the customer traction side and revenue business funding. Males look good economic with a platform, certainly software margins looking very good growth. What's it all about right now? Culture value, proposition don't. >> It's kind of like a rocket ship, and we're just hanging on. But it's Ah, I think that focus is, um, when you grow this fast, uh, the challenge becomes, uh, keeping your culture intact and we tryto put a lot of effort on our culture. Our core values are cultural guidelines were fanatics about that. So we want everyone to feel that they're coming in and this is home away from home, and they treat others to make them feel it's home away from home. We're trying to build a family here, so there's a lot of emphasis on that. But at the same time, you know, we all work hard and let the company >> and the new ecosystem opportunity for you is looking really good because if he zaps takeoff, certainly the cohesively APS. And now you got third party with an S t. K. This is potentially a game changer for you as a company to a CZ Wells, you have product company. Software company makes a lot of scared, but now you're gonna be bringing developers and impact there. >> The impact, the talk, leadership impact. Uh, you know, I'm personally very fun off er you know I do these companies because I want to change the world. I won't change the way the world thinks this is the way I think. And if I can help the world think in this fashion contributed something to the world. And so that's the excitement that sort of mission is. Team is excited about that. It's just >> we got a great mind phD in computer science and two ships systems entrepreneur that thinks up new things that disrupt the status quo. And the old guard certainly track record their congratulations. Know what? Thanks for coming on The Cube. This's the Cube conversation here. Palo Alto. I'm John every year. Thanks for watching. What?
SUMMARY :
I'm John for a host of the Cube were Mohit parents, founder and CEO of Cohesive Serial What a smartphone that in the consumer space before capabilities that's going to come out of the data because if you have data being backed up, One more copy of the data. And I've heard you mentioned that when were before we came on. It sets and silos be the backups or passed on diver filers, Object storage. But why you got your hands on the data? Is that right? You can't incrementally at patches and expect the system to grow the Google file system and then YouTube on top and Gmail on top and blah, blah, So it be safe to say that cohesive from a software core competency standpoint is distributed that their competences of within those domains. First of all, thanks for saying you have responded to that. The name comes from the fact that it's supposed to span nodes in the very center that's supposed Talk about the impact of multi cloud in today's world because That's the kind of value we can bring. It's it's data is driving the economics. on the side I'm back from. so consolidating with cohesive because I'll be using cohesive, he allows the better management cutting the costs, and then you can run your raps on top. Talk about the announcement you Some of the gaps are from the vendor who built the smartphone. What's the thoughts It's the same motivation, you know, extend the What's the makeup of the target audience? So the value for our customers, So what a business you guys have talked about a couple quarters Uh, a lot of the secret of federal All the bills go office because you guys were two hundred last year. when you get back, we are about to enter. How big is this guy's a real state growing and buy more office space. So lots and lots of expansion worldwide. I mean, let's think about the economics. Um uh, it all depends on you know, We're going to say, very impressed with the growth and impressed that you go out on the road, talk to customers closing business. Uh, and my job is to see you is to make sure what happened I want to ask you about entrepreneurship in your journey. starting a company, you know, you got a rocket ship, so you had a lot people coming on Now from the your journey you're on now. ever in the past because technology is there to help people. You get the beachheads real specific seconds, That's That's gonna much the analogy. I beat master of one traitor, go ahead in the beachhead and then expanded the bigger You've a great perspective on the difference between hyper scale on enterprise worlds Is the same benefits that the hyper scholars have enjoyed over the years, eh? the and and the companies that I have found it have. But again, you start Cummings that don't have magic of the vision and Kendra naps to extract value from the dealer right? about Kohi City and what do you bring to the table with respect to Ransomware. just the detection, but also a number for the things we can detect Ransom where we protect the data, do some custom stuff. last question from the crowd here, the community multi cloud. the data is very fragmented. of cohesive the right now? But at the same time, and the new ecosystem opportunity for you is looking really good because if he zaps takeoff, And so that's the excitement that sort of mission is. And the old guard certainly track record their congratulations.
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