(upbeat music) >> Hello and welcome to today's session, theCUBE's presentation of the AWS Startup Showcase, New Breakthroughs in DevOps, Data Analytics, Cloud Management Tools, featuring Ascend.io for the data and analytics track. I'm your host, John Furrier with theCUBE. Today, we're proud joined by Sean Knapp, CEO and founder of Ascend.io and Jason Robinson who's the VP of Data Science and Engineering at Steady. Guys, thanks for coming on and congratulations, Sean, for the continued success, loves our cube conversation and Jason, nice to meet you. >> Great to meet you. >> Thanks for having us. >> So, the session today is really kind of looking at automating analytics workloads, right? So, and Steady as a customer. Sean, talk about the relationship with the customer Steady. What's the main product, what's the core relationship? >> Yeah, it's a really great question. when we work with a lot of companies like Steady we're working hand in hand with their data engineering teams, to help them onboard onto the Ascend platform, build these really powerful data pipelines, fueling their analytics and other workloads, and really helping to ensure that they can be successful at getting more leverage and building faster than ever before. So we tend to partner really closely with each other's teams and really think of them even as extensions of each other's own teams. I watch in slack oftentimes and our teams just go back and forth. And it's like, as if we were all just part of the same company. >> It's a really exciting time, Jason, great to have you on as a person cutting your teeth into this kind of what I call next gen data as intellectual property. Sean and I chat on theCUBE conversation previous to this event where every company is a data company, right? And we've heard that cliche. >> Right. >> But it's true, right? It's going to, it's getting more powerful with the edge. You seeing more diverse data, faster data, small, big, large, medium, all kinds of different aspects and patterns. And it's becoming a workflow kind of intellectual property paradigm for companies, not so much. >> That's right. >> Just the tech it's the database is you can, it's the data itself, data in flight, it's moving around, it's got value. What's your take-- >> Absolutely. >> On this trend? >> Basically, Steady helps our members and we have a community of members earn more income. So we want to help them steady their financial lives. And that's all based on data, so we have a web app, you could go to the iOS Store, you could go to the Google Play Store, you can download the app. And we have a large number of members, 3 million plus, who are actively using this. And we also have a very exciting new product called income passport. And this helps 1099 and mixed wage earners verify their income, which is very important for different government benefits. And then third, we help people with emergency cash grants as well as awards. So all of that is built on a bedrock of data, so if you're using our apps, it's all data powered. So what you were mentioning earlier from pipelines that are running it real time to yeah, anything, that's a kind of a small data aggregation, we do everything from small to real-time and large. >> You guys are like a multiple sided marketplace here, you've got it, you're a FinTech app, as well as the future of work and with virtual space-- >> That's right. >> Happening now, this is becoming, actually encapsulates kind of the critical problems that people trying to solve right now, you've got multiple stakeholders. >> That's right. >> In the data. >> Yes, we absolutely do. So we have our members, but we also, within the company, we have product, we have strategy, we have a growth team, we have operations. So data engineering and data science also work with a data analytics organization. So at Steady we're very much a data company. And we have a data organization led by our chief data officer and we have data engineering and data science, which are my teams, but also that business insights and analytics. So a lot of what we're building on the data engineering side is powering those insights and analytics that the business stakeholders use every day to run the organization. >> Sean, I want to get your thoughts on this because we heard from Emily Freeman in the keynote about how this revolution in DevOps or for premiering her talk around how, it's not just one persona anymore, I'm a release engineer, I'm this kind of engineer, you're seeing now all engineering, all developers are developers. You have some specialty, but for the most part, the team makeups are changing. We touched on this in our cube conversation. The journey of data is not just the data people, the data folks. It's like there's, they're developers too. So the confluence of data science, data management, developing, is changing the team and cultural makeup of companies. Could you share your thoughts on this dynamic and how it impacts customers? >> Absolutely, I think the, we're finding a similar trend to what we saw a number of years ago, when we talked about how software was eating the world and every company was now becoming a software company. And as a result, we saw this proliferation and expansion of what the software roles look like and thought of a company pulled through this entire new era of DevOps. We were finding that same pattern now emerging around data as not only is every company a software company, every company is a data company and data really is that field, that oil that fuels the business and in doing so, we're finding that as Jason describes it's pervasive across the team, it is no longer just one team that is creating some insights and reports around operational analytics, or maybe a team over here doing data science or machine learning. It is expensive. And I think the really interesting challenges that start to come with this too, are so many data teams are so over capacity. We did a recent study that highlighted that 96% of data teams are at, or over capacity, only 4% had spare capacity. But as a result, the net is being cast even wider to pull in people from even broader and more adjacent domains to all participate in the data future of their organization. >> Yeah, and I think I'd love to get your guys react to this conversation with Andy Jassy, who's now the CEO of Amazon, but when he was the CEO of AWS last year, I talked with him about how the old guard and new guard are thinking around team formations. Obviously team capacity is growing and challenged when you've got the right formula. So that's one thing, right? But what if you don't have the right formula? If you're in the skills gap, problem, or team formation side of it, where you maybe there was two years ago where the mandate came down? Well, we got to build a data team even in two years, if you're not inquisitive. And this is what Andy and I were talking about is the thinking and the mindset of that mission and being open to discovering and understanding the changes, because if you were deciding what your team was two, three years ago, that might have changed a lot. So team capacity, Sean, to your point, if you got it right, and that's a challenge in and of itself, but what if you don't have it, right? What do you guys think about this? >> Yeah, I think that's exactly right. Basically trying to see, look and gaze into the crystal ball and see what's going to happen in a year or two years, even six months is quite difficult. And if you don't have it right, you do spend a lot of time because of the technical debt that you've amassed. And we certainly spend quite a bit of time with technical debt for things we wanted to build. So, deconvolving that, getting those ETLs to a runnable state, getting performance there, that's what we spend a bit of time on. And yeah, it's something that it's really part of the package. >> What do you guys see as the big challenge on teams? The scaling challenge okay. Formation is one thing, Sean, but like, okay, getting it right, getting it formed properly and then scaling it, what are the big things you're seeing? >> One of the, I think the overarching management themes in general, it is the highest out by the highest performing teams are those where the individual with the context and the idea is able to execute as far and as fast and as efficiently as possible, and removing a lot of those encumbrances and put it a slightly different way. If DevOps was all basically boiled down to, how do we help more people write more software faster and safely data ops would be very similarly, how do we enable more people to do more things with data faster and safely? And to do that, I think the era of these massive multi-year efforts around data are gone and hopefully in the not too distant future, even these multi-quarter efforts around data are gone and we get into a much more agile, nimble methodology where smaller initiatives and smaller efforts are possible by more diverse skillsets across the business. And really what we should be doing is leveraging technology and automation to ensure that people are able to be productive and efficient and that we can trust our data and that systems are automated. And these are problems that technology is good at. And so in many ways, how in the early days Amazon would described as getting people out of the muck of DevOps. I think we're going to do the same thing around getting people out of the muck of the data and get them really focused on the higher level aspects. >> Yeah, we're going to get into that complexity, heavy lifting side muck, and then the heavy lifting taking away from the customers. But I want to go back to real quick with Jason while we're on this topic. Jason, I was just curious, how much has your team grown in the recent year and how much could've, should've grown, what's the status and how has Ascend helped you guys? What's the dynamic there? ' Cause that's their value proposition. So, take us through that. >> Absolutely, so, since the beginning of the year data engineering has doubled. So, we're a lean team, we certainly use the agile mindset and methodologies, but we have gone from, yeah, we've essentially doubled. So a lot of that is there's just so much to do and the capacity problem is certainly there. So we also spend a lot of time figuring out exactly what the right tooling is. And I was mentioning the technical debt. So you have those, there's the big O notation of whatever that involves technical debt. And when you're building new things, you're fixing old things. And then you're trying to maintain everything. That scaling starts to hit hard. So even if we continue to double, I mean, we could easily add more data engineers. And a lot of that is, I mean, you know about the hiring cycles, like, a lot of of great talent, but it's difficult to make all of those hires. So, we do spend quite a bit of time thinking about exactly what tools data engineering is using day-to-day. And what I mentioned, were technologies on the streaming side all the way to like the small batch things, but, like something that starts as a small batch getting grow and grow and grow and take, say 15 hours, it's possible, I've seen it. But, and getting that back down and managing that complexity while not overburdening people who probably don't want to spend all their waking hours building ETLs, maintaining ETL, putting in monitoring, putting in alerting, that I think is quite a challenge. >> It's so funny because you mentioned 18 hours, you got to kind of being, you didn't roll your eyes, but you almost did, but this is, but people want it yesterday, they want real time, so there's a lot of demand-- >> Yes. >> On the minds of the business outcome side of it. So, I got to ask you, because this comes up a lot with technical debt, and now we're starting to see that come into the data conversation. And so I always curious, is there a different kind of technical debt with data? Because again, data is like software, but it's a little bit of more elusive in the sense it's always changing. So is there, what kind of technical debt do you see in the data side that's different than say software side? >> Absolutely, now that's a great question. So a lot of thinking about your data and structuring your data and how you want to use that data going into a particular project might be different from what happens after stakeholders have a new considerations and new products and new items that need to be built. So thinking about how that, let's say you have a document store, or you have something that you thought was going to be nice and structured, how that can evolve and support those particular products can essentially, unless you take the time and go through and say, well, let's architect it perfectly so that we can handle that. You're going to make trade-offs and choices, and essentially that debt builds up. So you start cutting corners, you start changing your normalization. You start essentially taking those implicit schema that then tend to build into big things, big implicit schema. And then of course, with implicit schema, you're going to have a lot of null values, you're going to have a lot of items to deal with. So, how do you deal with that? And then you also have the opportunity to create keys and values and oops, do we take out those keys that were slightly misspelled? So, I could go on for hours, but basically the technical debt certainly is there with on data. I see a lot of this as just a spectrum of technical debt, because it's all trade-offs that you made to build a product, and the efficiency has start to hit you. So, the 15 hour ETL, I was mentioning, basically you start with something and you were building things for stakeholders and essentially you have so much complex logic within that. So for the transforms that you're doing from if you're thinking of the bronze, silver, gold, kind of a framework, going from that bronze to a silver, you may have a massive number of transformations or just a few, just to lightly dust it. But you could also go to gold with many more transformations and managing that, managing the complexity, managing what you're spending for servers day after day after day. That's another real challenge of that technical debt stuff. >> That's a great lead into my next question, for Sean, this is the disparate system complexity, technical debt and software was always kind of the belief was, oh yeah, I'll take some technical debt on and work it off once I get visibility and say, unit economics or some sort of platform or tool feature, and then you work it off as fast as possible. I was, this becomes the art and science of technical debt. Jason, what you're saying is that this can be unwieldy pretty quickly. You got state and you got a lot of different inter moving parts. This is a huge issue, Sean, this is where it's, technical debt in the data world is much different architecturally. If you don't get it right, this is a huge, huge issue. Could you aluminate why that is and what you guys are doing to help unify and change some of those conditions? >> Yeah, absolutely. When we think about technical debt and I'll keep drawing some parallels between DevOps and data ops, 'cause I think there's a tremendous number of similarities in these worlds. We used to always have the saying that "Your tech debt grows manually across microservices, "but exponentially within services." And so you want that right level of architecture and composibility if you will, of your systems where you can deploy changes, you can test, you can have high degrees of competence and the roll-outs. And I think the interesting part in the data side, as Jason highlighted, the big O-notation for tech debt in the data ecosystem, is still fairly exponential or polynomial in nature. As right now, we don't have great decomposition of the components. We have different systems. We have a streaming system, we have a databases, we have documents, doors and so on, but how the whole data pipeline data engineering part works generally tends to be pretty monolithic in nature. You take your whole data pipeline and you deploy the whole thing and you basically just cross your fingers, and hopefully it's not 15 hours, but if it is 15 hours, you go to sleep, you wake up the next morning, grab a coffee and then maybe it worked. And that iteration cycle is really slow. And so when we think about how we can improve these things, right? This is combinations of intelligent systems that do instantaneous schema detection, and validation, excuse me, it's combinations of things that do instantaneous schema detection and validation. It's things like automated lineage and dependency tracking. So you know that when you deploy code, what piece of data it affects, it's things like automated testing on individual core parts of your data pipelines to validate that you're getting the expected output that you need. So it's pulling a lot of these same DevOps style principles into the data world, which is really designed to going back to how do you help more people build more things faster and safely really rapid iterations for rapid feedback. So you know if there's breaks in the system much earlier on. >> Well, I think Sean, you're onto something really big there. And I think this is something that's emerging pretty quickly in the cloud scale that I called, 2.0, whatever, what version we're in, is the systems thinking mindset. 'Cause you mentioned the model that that was essentially a silo or subsystem. It was cohesive in it's own way, but now it's been monolithic. Now you have a broken down set of decomposed sets of data pieces that have to work together. So Jason, this is the big challenge that everyone, not really people are talking about, I think most these guys are, and you're using them. What are you unifying? Because this is a systems operating systems thinking, this is not like a database problem. It's a systems problem applied to data where databases are just pieces of it, what's your thoughts? >> That's absolutely right. And I would, so Sean touched on composibility of ETL and thinking about reusable components, thinking about pieces that all fit together, because as you're building something as complex as some of these ETS are, we do think about the platform itself and how that lends to the overarching output. So one thing, being able to actually see the different components of an ETL and blend those in and you as the dry principal, don't repeat yourself. So you essentially are able to take pieces that one person built, maybe John builds a couple of our connectors coming in, Sean also has a bunch of transforms and I just want this stuff out, so I can use a lot of what you guys have already built. I think that's key, because a lot of engineering and data engineering is about managing complexity. So taking that complexity and essentially getting it out fast and getting out error free, is where we're going with all of the data products we're building. >> What are some of the complexity that you guys have that you're dealing with? Can you be specific and share what these guys are doing to solve that problem for you? That's, this is a big problem everyone's having, I'm seeing that all over the place. >> Absolutely, so I could start at a couple of places. So I don't know if you guys are on the three Vs, four Vs or five Vs, but we have all of those. And if you go to that five, four or five V model, there is the veracity piece, which you have to ask yourself, is it true? Is it accurate when? So change happens throughout the pipeline, change can come from web hooks, change can come from users. You have to make sure that you're managing that complexity and what we we're building, I mentioned that we are paying down a lot of tech debt, but we're also building new products. And one pretty challenging, quite challenging ETL that we're building is something going from a document store to an analytical application. So in that document store, we talked about flexible schema. Basically, you don't really know exactly what you're going to get day to day, and you need to be able to manage that change through the whole process in a way that the ultimate business users find value. So, that's one of the key applications that we're using right now. And that's one that the team at Ascend and my team are working hand in hand going through a lot of those challenges. And it's, I also watch the slack just as Sean does, and it's a very active discussion board. So it is essentially like they're just partnering together. It's fabulous, but yeah-- >> And you're seeing kind of a value on this too, I mean, in terms of output what's the business results? >> Yes, absolutely. So essentially this is all, so yes, the fifth V value. So, getting to that value is essentially, there were a few pieces of the, to the value. So there's some data products that we're building within that product and their data science, data analytics based products that essentially do things with the data that help the user. There's also the question of exactly the usage and those kinds of metrics that people in ops want to understand as well as our growth team. So we have internal and external stakeholders for that. >> Jason, this is a great use case, a great customer, Sean, you guys are automating. For the folks watching, who were seeing their peer living the dream here and the data journey, as we say, things are happening. What's the message to customers that you guys want to send because you guys are really cutting your teeth into a whole another level of data engineering, data platform. That's really about the systems view and about cloud. What's the pitch, Sean? What should people know about the company? >> Absolutely, yeah, well, so one, I'd say even before the pitch, I would encourage people to not accept the status quo. And in particular, in data engineering today, the status quo is an incredibly high degree of pain and discomfort. And I think the important part of why Ascend exists and why we're so helpful for our customers, there is a much more automated future of how we build data products, how we optimize those and how we can get a larger cohort of builders into the data ecosystem. And that helps us get out of the muck as we talked about before and put really advanced technology to work for more people inside of our companies to build these data products, leveraging the latest and greatest technologies to drive increased business value faster. >> Jason, what's your assessment of these guys, as people are watching might say, hey, you know what, I'm going to contact them, I need this. How would you talk about Ascend into your peers? >> Absolutely, so I think just thinking about the whole process has been a great partnership. We started with a POC, I think Ascend likes to start with three use cases, I think we came out with four and we went through the ones that we really cared about and really wanted to bring value to the company with. So we have roadmaps for some, as we're paying down technical debt and transitioning, others we can go directly to. And I think that thinking about just like you're saying, John, that systems view of everything you're building, where that makes sense, you can actually take a lot of that complexity and encapsulate it in a way that you can essentially manage it all in that platform. So the Ascend platform has the composibility piece that we touched on. It also, not only can you compose it, but you can drill into it. And my team is super talented and is going to drill into it. So basically loves to open up each of those data flows each of the components therein and has the control there with the combination of Spark Sequel, PI Spark SQL Scala and so on. And I think that the variety of connections is also quite helpful. So thinking about the dry principle from a systems perspective is extremely useful because it's dry, you often get that in a code review, right? I think you can be a little bit more dry here. >> Yeah. >> But you can really do that in the way that you're composing your systems as well. >> That's a great, great point. One quick thing for the folks that they're watching that are trying to figure this out, and a lot of architecture is going on. A lot of people are looking at different solutions. What things have you learned that you could give them a tip like to avoid like maybe some scar tissue or tips of the trade, where you can say, hey, this way, be careful, what's some of the learnings? Could you give a few pointers to folks out there, if they're kicking tires on the direction, what's the wrong direction? What's the right direction look like? >> Absolutely, I think that, I think it through, and I don't know how much time we have that, that feels like a few days conversation as far as ways to go wrong. But absolutely, I think that thinking through exactly where want to be is the key. Otherwise it's kind of like when you're writing a ticket on Jarrah, if you don't have clear success criteria, if you don't know where you going to go, then you'll end up somewhere building something and it might work. But if you think through your exact destination that you want to be at, that will drive a lot of the decisions as you think backwards to where you started. And also I think that, so Sean also mentioned challenging the status quo. I think that you really have to be ready to challenge the status quo at every step of that journey. So if you start with some particular service that you had and its legacy, if it's not essentially performing what you need, then it's okay to just take a step back and say, well, maybe that's not the one. So I think that thinking through the system, just like you were saying, John, and also I think that having a visual representation of where you want to go is critical. So hopefully that encapsulates a lot of it, but yes, the destination is key. >> Yeah, and having an engineering platform that also unifies the multiple components and it's agile. >> That's right. >> It gets you out of the muck and on the last day and differentiate heavy lifting is a cloud plan. >> Absolutely. >> Sean, wrap it up for us here. What's the bumper sticker for your vision, share your founding principles of the company. >> Absolutely, for us, we started the company as a former in recovery and CTO. The last company I founded, we had nearly 60 people on our data team alone and had invested tremendous amounts of effort over the course of eight years. And one of the things that I've learned is that over time innovation comes just as much from deciding what you're no longer going to do as what you're going to do. And focusing heavily around, how do you get out of that muck? How do you continue to climb up that technology stack? Is incredibly important. And so really we are excited to be a part of it and taking the industry is continuing to climb higher and higher level. We're building more and more advanced levels of automation and what we call our data awareness into the automated engine of the Ascend platform that takes us across the entire data ecosystem, connecting and automating all data movement. And so we have a very exciting vision for this fabric that's emerging over time. >> Awesome, Sean, thank you so much for that insight, Jason, thanks for coming on customer of Ascend.io. >> Thank you. >> I appreciate it, gentlemen, thank you. This is the track on automating analytic workloads. We here at the end of us showcase, startup showcase, the hottest companies here at Ascend.io, I'm John Furrier, with theCUBE, thanks for watching. (upbeat music)

>>from around the globe. It's the Cube presenting innovation for good, brought to you by on shape. >>Hello, everyone, and welcome to Innovation for Good Program, hosted by the Cuban. Brought to You by on Shape, which is a PTC company. My name is Dave Valentin. I'm coming to you from our studios outside of Boston. I'll be directing the conversations today. It's a very exciting, all live program. We're gonna look at how product innovation has evolved and where it's going and how engineers, entrepreneurs and educators are applying cutting edge, cutting edge product development techniques and technology to change our world. You know, the pandemic is, of course, profoundly impacted society and altered how individuals and organizations they're gonna be thinking about an approaching the coming decade. Leading technologists, engineers, product developers and educators have responded to the new challenges that we're facing from creating lifesaving products to helping students learn from home toe how to apply the latest product development techniques and solve the world's hardest problems. And in this program, you'll hear from some of the world's leading experts and practitioners on how product development and continuous innovation has evolved, how it's being applied toe positive positively affect society and importantly where it's going in the coming decades. So let's get started with our first session fueling Tech for good. And with me is John Hirschbeck, who is the president of the Suffers, a service division of PTC, which acquired on shape just over a year ago, where John was the CEO and co founder, and Dana Grayson is here. She is the co founder and general partner at Construct Capital, a new venture capital firm. Folks, welcome to the program. Thanks so much for coming on. >>Great to be here, Dave. >>All right, John. >>You're very welcome. Dana. Look, John, let's get into it for first Belated congratulations on the acquisition of Von Shape. That was an awesome seven year journey for your company. Tell our audience a little bit about the story of on shape, but take us back to Day zero. Why did you and your co founders start on shape? Well, >>actually, start before on shaping the You know, David, I've been in this business for almost 40 years. The business of building software tools for product developers and I had been part of some previous products in the industry and companies that had been in their era. Big changes in this market and about, you know, a little Before founding on shape, we started to see the problems product development teams were having with the traditional tools of that era years ago, and we saw the opportunity presented by Cloud Web and Mobile Technology. And we said, Hey, we could use Cloud Web and Mobile to solve the problems of product developers make their Their business is run better. But we have to build an entirely new system, an entirely new company, to do it. And that's what on shapes about. >>Well, so notwithstanding the challenges of co vid and difficulties this year, how is the first year been as, Ah, division of PTC for you guys? How's business? Anything you can share with us? >>Yeah, our first year of PTC has been awesome. It's been, you know, when you get acquired, Dave, you never You know, you have great optimism, but you never know what life will really be like. It's sort of like getting married or something, you know, until you're really doing it, you don't know. And so I'm happy to say that one year into our acquisition, um, PTC on shape is thriving. It's worked out better than I could have imagined a year ago. Along always, I mean sales are up. In Q four, our new sales rate grew 80% vs Excuse me, our fiscal Q four Q three. In the calendar year, it grew 80% compared to the year before. Our educational uses skyrocketing with around 400% growth, most recently year to year of students and teachers and co vid. And we've launched a major cloud platform using the core of on shape technology called Atlas. So, um, just tons of exciting things going on a TTC. >>That's awesome. But thank you for sharing some of those metrics. And of course, you're very humble individual. You know, people should know a little bit more about you mentioned, you know, we founded Solid Works, co founded Solid where I actually found it solid works. You had a great exit in the in the late nineties. But what I really appreciate is, you know, you're an entrepreneur. You've got a passion for the babies that you you helped birth. You stayed with the salt systems for a number of years. The company that quiet, solid works well over a decade. And and, of course, you and I have talked about how you participated in the the M I T. Blackjack team. You know, back in the day, a zai say you're very understated, for somebody was so accomplished. Well, >>that's kind of you, but I tend to I tend Thio always keep my eye more on what's ahead. You know what's next, then? And you know, I look back Sure to enjoy it and learn from it about what I can put to work making new memories, making new successes. >>Love it. Okay, let's bring Dana into the conversation. Hello, Dana. You look you're a fairly early investor in in on shape when you were with any A And and I think it was like it was a serious B, but it was very right close after the A raise. And and you were and still are a big believer in industrial transformation. So take us back. What did you see about on shape back then? That excited you. >>Thanks. Thanks for that. Yeah. I was lucky to be a early investment in shape. You know, the things that actually attracted me. Don shape were largely around John and, uh, the team. They're really setting out to do something, as John says humbly, something totally new, but really building off of their background was a large part of it. Um, but, you know, I was really intrigued by the design collaboration side of the product. Um, I would say that's frankly what originally attracted me to it. What kept me in the room, you know, in terms of the industrial world was seeing just if you start with collaboration around design what that does to the overall industrial product lifecycle accelerating manufacturing just, you know, modernizing all the manufacturing, just starting with design. So I'm really thankful to the on shape guys, because it was one of the first investments I've made that turned me on to the whole sector. And while just such a great pleasure to work with with John and the whole team there. Now see what they're doing inside PTC. >>And you just launched construct capital this year, right in the middle of a pandemic and which is awesome. I love it. And you're focused on early stage investing. Maybe tell us a little bit about construct capital. What your investment thesis is and you know, one of the big waves that you're hoping to ride. >>Sure, it construct it is literally lifting out of any what I was doing there. Um uh, for on shape, I went on to invest in companies such as desktop metal and Tulip, to name a couple of them form labs, another one in and around the manufacturing space. But our thesis that construct is broader than just, you know, manufacturing and industrial. It really incorporates all of what we'd call foundational industries that have let yet to be fully tech enabled or digitized. Manufacturing is a big piece of it. Supply chain, logistics, transportation of mobility or not, or other big pieces of it. And together they really drive, you know, half of the GDP in the US and have been very under invested. And frankly, they haven't attracted really great founders like they're on in droves. And I think that's going to change. We're seeing, um, entrepreneurs coming out of the tech world orthe Agnelli into these industries and then bringing them back into the tech world, which is which is something that needs to happen. So John and team were certainly early pioneers, and I think, you know, frankly, obviously, that voting with my feet that the next set, a really strong companies are going to come out of the space over the next decade. >>I think it's a huge opportunity to digitize the sort of traditionally non digital organizations. But Dana, you focused. I think it's it's accurate to say you're focused on even Mawr early stage investing now. And I want to understand why you feel it's important to be early. I mean, it's obviously riskier and reward e er, but what do you look for in companies and and founders like John >>Mhm, Um, you know, I think they're different styles of investing all the way up to public market investing. I've always been early stage investors, so I like to work with founders and teams when they're, you know, just starting out. Um, I happened to also think that we were just really early in the whole digital transformation of this world. You know, John and team have been, you know, back from solid works, etcetera around the space for a long time. But again, the downstream impact of what they're doing really changes the whole industry. And and so we're pretty early and in digitally transforming that market. Um, so that's another reason why I wanna invest early now, because I do really firmly believe that the next set of strong companies and strong returns for my own investors will be in the spaces. Um, you know, what I look for in Founders are people that really see the world in a different way. And, you know, sometimes some people think of founders or entrepreneurs is being very risk seeking. You know, if you asked John probably and another successful entrepreneurs, they would call themselves sort of risk averse, because by the time they start the company, they really have isolated all the risk out of it and think that they have given their expertise or what they're seeing their just so compelled to go change something, eh? So I look for that type of attitude experience a Z. You can also tell from John. He's fairly humble. So humility and just focus is also really important. Um, that there's a That's a lot of it. Frankly, >>Excellent. Thank you, John. You got such a rich history in the space. Uh, and one of you could sort of connect the dots over time. I mean, when you look back, what were the major forces that you saw in the market in in the early days? Particularly days of on shape on? And how is that evolved? And what are you seeing today? Well, >>I think I touched on it earlier. Actually, could I just reflect on what Dana said about risk taking for just a quick one and say, throughout my life, from blackjack to starting solid works on shape, it's about taking calculated risks. Yes, you try to eliminate the risk Sa's much as you can, but I always say, I don't mind taking a risk that I'm aware of, and I've calculated through as best I can. I don't like taking risks that I don't know I'm taking. That's right. You >>like to bet on >>sure things as much as you sure things, or at least where you feel you. You've done the research and you see them and you know they're there and you know, you, you you keep that in mind in the room, and I think that's great. And Dana did so much for us. Dana, I want to thank you again. For all that, you did it every step of the way, from where we started to to, you know, your journey with us ended formally but continues informally. Now back to you, Dave, I think, question about the opportunity and how it's shaped up. Well, I think I touched on it earlier when I said It's about helping product developers. You know, our customers of the people build the future off manufactured goods. Anything you think of that would be manufacturing factory. You know, the chair you're sitting in machine that made your coffee. You know, the computer you're using, the trucks that drive by on the street, all the covert product research, the equipment being used to make vaccines. All that stuff is designed by someone, and our job is given the tools to do it better. And I could see the problems that those product developers had that we're slowing them down with using the computing systems of the time. When we built solid works, that was almost 30 years ago. If people don't realize that it was in the early >>nineties and you know, we did the >>best we could for the early nineties, but what we did. We didn't anticipate the world of today. And so people were having problems with just installing the systems. Dave, you wouldn't believe how hard it is to install these systems. You need toe speck up a special windows computer, you know, and make sure you've got all the memory and graphics you need and getting to get that set up. You need to make sure the device drivers air, right, install a big piece of software. Ah, license key. I'm not making this up. They're still around. You may not even know what those are. You know, Dennis laughing because, you know, zero cool people do things like this anymore. Um, and it only runs some windows. You want a second user to use it? They need a copy. They need a code. Are they on the same version? It's a nightmare. The teams change, you know? You just say, Well, get everyone on the software. Well, who's everyone? You know, you got a new vendor today? A new customer tomorrow, a new employee. People come on and off the team. The other problem is the data stored in files, thousands of files. This isn't like a spreadsheet or word processor, where there's one file to pass around these air thousands of files to make one, even a simple product. People were tearing their hair out. John, what do we do? I've got copies everywhere. I don't know where the latest version is. We tried like, you know, locking people out so that only one person can change it At the time that works against speed, it works against innovation. We saw what was happening with Cloud Web and mobile. So what's happened in the years since is every one of the forces that product developers experience the need for speed, the need for innovation, the need to be more efficient with their people in their capital. Resource is every one of those trends have been amplified since we started on shape by a lot of forces in the world. And covert is amplified all those the need for agility and remote work cove it is amplified all that the same time, The acceptance of cloud. You know, a few years ago, people were like cloud, you know, how is that gonna work now They're saying to me, You know, increasingly, how would you ever even have done this without the cloud. How do you make solid works work without the cloud? How would that even happen? You know, once people understand what on shapes about >>and we're the >>Onley full SAS solution software >>as a service, >>full SAS solution in our industry. So what's happened in those years? Same problems we saw earlier, but turn up the gain, their bigger problems. And with cloud, we've seen skepticism of years ago turn into acceptance. And now even embracement in the cova driven new normal. >>Yeah. So a lot of friction in the previous environments cloud obviously a huge factor on, I guess. I guess Dana John could see it coming, you know, in the early days of solid works with, you know, had Salesforce, which is kind of the first major independent SAS player. Well, I guess that was late nineties. So his post solid works, but pre in shape and their work day was, you know, pre on shape in the mid two thousands. And and but But, you know, the bet was on the SAS model was right for Crick had and and product development, you know, which maybe the time wasn't a no brainer. Or maybe it was, I don't know, but Dana is there. Is there anything that you would invest in today? That's not Cloud based? >>Um, that's a great question. I mean, I think we still see things all the time in the manufacturing world that are not cloud based. I think you know, the closer you get to the shop floor in the production environment. Um e think John and the PTC folks would agree with this, too, but that it's, you know, there's reliability requirements, performance requirements. There's still this attitude of, you know, don't touch the printing press. So the cloud is still a little bit scary sometimes. And I think hybrid cloud is a real thing for those or on premise. Solutions, in some cases is still a real thing. What what we're more focused on. And, um, despite whether it's on premise or hybrid or or SAS and Cloud is a frictionless go to market model, um, in the companies we invest in so sass and cloud, or really make that easy to adopt for new users, you know, you sign up, started using a product, um, but whether it's hosted in the cloud, whether it's as you can still distribute buying power. And, um, I would I'm just encouraging customers in the customer world and the more industrial environment to entrust some of their lower level engineers with more budget discretionary spending so they can try more products and unlock innovation. >>Right? The unit economics are so compelling. So let's bring it, you know, toe today's you know, situation. John, you decided to exit about a year ago. You know? What did you see in PTC? Other than the obvious money? What was the strategic fit? >>Yeah, Well, David, I wanna be clear. I didn't exit anything. Really? You >>know, I love you and I don't like that term exit. I >>mean, Dana had exit is a shareholder on and so it's not It's not exit for me. It's just a step in the journey. What we saw in PTC was a partner. First of all, that shared our vision from the top down at PTC. Jim Hempleman, the CEO. He had a great vision for for the impact that SAS can make based on cloud technology and really is Dana of highlighted so much. It's not just the technology is how you go to market and the whole business being run and how you support and make the customers successful. So Jim shared a vision for the potential. And really, really, um said Hey, come join us and we can do this bigger, Better, faster. We expanded the vision really to include this Atlas platform for hosting other SAS applications. That P D. C. I mean, David Day arrived at PTC. I met the head of the academic program. He came over to me and I said, You know, and and how many people on your team? I thought he'd say 5 40 people on the PTC academic team. It was amazing to me because, you know, we were we were just near about 100 people were required are total company. We didn't even have a dedicated academic team and we had ah, lot of students signing up, you know, thousands and thousands. Well, now we have hundreds of thousands of students were approaching a million users and that shows you the power of this team that PTC had combined with our product and technology whom you get a big success for us and for the teachers and students to the world. We're giving them great tools. So so many good things were also putting some PTC technology from other parts of PTC back into on shape. One area, a little spoiler, little sneak peek. Working on taking generative design. Dana knows all about generative design. We couldn't acquire that technology were start up, you know, just to too much to do. But PTC owns one of the best in the business. This frustrated technology we're working on putting that into on shaping our customers. Um, will be happy to see it, hopefully in the coming year sometime. >>It's great to see that two way exchange. Now, you both know very well when you start a company, of course, a very exciting time. You know, a lot of baggage, you know, our customers pulling you in a lot of different directions and asking you for specials. You have this kind of clean slate, so to speak in it. I would think in many ways, John, despite you know, your install base, you have a bit of that dynamic occurring today especially, you know, driven by the forced march to digital transformation that cove it caused. So when you sit down with the team PTC and talk strategy. You now have more global resource is you got cohorts selling opportunities. What's the conversation like in terms of where you want to take the division? >>Well, Dave, you actually you sounds like we should have you coming in and talking about strategy because you've got the strategy down. I mean, we're doing everything said global expansion were able to reach across selling. We got some excellent PTC customers that we can reach reach now and they're finding uses for on shape. I think the plan is to, you know, just go, go, go and grow, grow, grow where we're looking for this year, priorities are expand the product. I mentioned the breath of the product with new things PTC did recently. Another technology that they acquired for on shape. We did an acquisition. It was it was small, wasn't widely announced. It, um, in an area related to interfacing with electrical cad systems. So So we're doing We're expanding the breath of on shape. We're going Maura, depth in the areas were already in. We have enormous opportunity to add more features and functions that's in the product. Go to market. You mentioned it global global presence. That's something we were a little light on a year ago. Now we have a team. Dana may not even know what we have. A non shape, dedicated team in Barcelona, based in Barcelona but throughout Europe were doing multiple languages. Um, the academic program just introduced a new product into that space that z even fueling more success and growth there. Um, and of course, continuing to to invest in customer success and this Atlas platform story I keep mentioning, we're going to soon have We're gonna soon have four other major PTC brands shipping products on our Atlas Saas platform. And so we're really excited about that. That's good for the other PTC products. It's also good for on shape because now there's there's. There's other interesting products that are on shape customers can use take advantage of very easily using, say, a common log in conventions about user experience there, used to invest of all they're SAS based, so they that makes it easier to begin with. So that's some of the exciting things going on. I think you'll see PTC, um, expanding our lead in SAS based applications for this sector for our our target, uh, sectors not just in, um, in cat and data management, but another area. PTC's Big and his augmented reality with of euphoria, product line leader and industrial uses of a R. That's a whole other story we should do. A whole nother show augmented reality. But these products are amazing. You can you can help factory workers people on, uh, people who are left out of the digital transformation. Sometimes we're standing from machine >>all day. >>They can't be sitting like we are doing Zoom. They can wear a R headset in our tools, let them create great content. This is an area Dana is invested in other companies. But what I wanted to note is the new releases of our authoring software. For this, our content getting released this month, used through the Atlas platform, the SAS components of on shape for things like revision management and collaboration on duh workflow activity. All that those are tools that we're able to share leverage. We get a lot of synergy. It's just really good. It's really fun to have a good time. That's >>awesome. And then we're gonna be talking to John MacLean later about that. Let's do a little deeper Dive on that. And, Dana, what is your involvement today with with on shape? But you're looking for you know, which of their customers air actually adopting. And they're gonna disrupt their industries. And you get good pipeline from that. How do you collaborate today? >>That sounds like a great idea. Um, Aziz, John will tell you I'm constantly just asking him for advice and impressions of other entrepreneurs and picking his brain on ideas. No formal relationship clearly, but continue to count John and and John and other people in on shaping in the circle of experts that I rely on for their opinions. >>All right, so we have some questions from the crowd here. Uh, one of the questions is for the dream team. You know, John and Dana. What's your next next collective venture? I don't think we're there yet, are we? No. >>I just say, as Dana said, we love talking to her about. You know, Dana, you just returned the compliment. We would try and give you advice and the deals you're looking at, and I'm sort of casually mentoring at least one of your portfolio entrepreneurs, and that's been a lot of fun for May on, hopefully a value to them. But also Dana. We uran important pipeline to us in the world of some new things that are happening that we wouldn't see if you know you've shown us some things that you've said. What do you think of this business? And for us, it's like, Wow, it's cool to see that's going on And that's what's supposed to work in an ecosystem like this. So we we deeply value the ongoing relationship. And no, we're not starting something new. I got a lot of work left to do with what I'm doing and really happy. But we can We can collaborate in this way on other ventures. >>I like this question to somebody asking With the cloud options like on shape, Wilmore students have stem opportunities s Oh, that's a great question. Are you because of sass and cloud? Are you able to reach? You know, more students? Much more cost effectively. >>Yeah, Dave, I'm so glad that that that I was asked about this because Yes, and it's extremely gratified us. Yes, we are because of cloud, because on shape is the only full cloud full SAS system or industry were able to reach. Stem education brings able to be part of bringing step education to students who couldn't get it otherwise. And one of most gratifying gratifying things to me is the emails were getting from teachers, um, that that really, um, on the phone calls that were they really pour their heart out and say We're able to get to students in areas that have very limited compute resource is that don't have an I T staff where they don't know what computer that the students can have at home, and they probably don't even have a computer. We're talking about being able to teach them on a phone to have an android phone a low end android phone. You can do three D modeling on there with on shape. Now you can't do it any other system, but with on shape, you could do it. And so the teacher can say to the students, They have to have Internet access, and I know there's a huge community that doesn't even have Internet access, and we're not able, unfortunately to help that. But if you have Internet and you have even an android phone, we can enable the educator to teach them. And so we have case after case of saving a stem program or expanding it into the students that need it most is the ones we're helping here. So really excited about that. And we're also able to let in addition to the run on run on whatever computing devices they have, we also offer them the tools they need for remote teaching with a much richer experience. Could you teach solid works remotely? Well, maybe if the student ran it had a windows workstation. You know, big, big, high end workstation. Maybe it could, but it would be like the difference between collaborating with on shape and collaborate with solid works. Like the difference between a zoom video call and talking on the landline phone. You know, it's a much richer experience, and that's what you need. And stem teaching stem is hard, So yeah, we're super super. Um, I'm excited about bringing stem to more students because of cloud yond >>we're talking about innovation for good, and then the discussion, John, you just had it. Really? There could be a whole another vector here. We could discuss on diversity, and I wanna end with just pointing out. So, Dana, your new firm, it's a woman led firm, too. Two women leaders, you know, going forward. So that's awesome to see, so really? Yeah, thumbs up on that. Congratulations on getting that off the ground. >>Thank you. Thank you. >>Okay, so thank you guys. Really appreciate It was a great discussion. I learned a lot and I'm sure the audience did a swell in a moment. We're gonna talk with on shaped customers to see how they're applying tech for good and some of the products that they're building. So keep it right there. I'm Dave Volonte. You're watching innovation for good on the Cube, the global leader in digital tech event coverage. Stay right there. >>Oh, yeah, it's >>yeah, yeah, around >>the globe. It's the Cube presenting innovation for good. Brought to you by on shape. >>Okay, we're back. This is Dave Volonte and you're watching innovation for good. A program on Cuba 3 65 made possible by on shape of PTC company. We're live today really live tv, which is the heritage of the Cube. And now we're gonna go to the sources and talkto on shape customers to find out how they're applying technology to create real world innovations that are changing the world. So let me introduce our panel members. Rafael Gomez Furberg is with the Chan Zuckerberg bio hub. A very big idea. And collaborative nonprofit was initiative that was funded by Mark Zuckerberg and his wife, Priscilla Chan, and really around diagnosing and curing and better managing infectious diseases. So really timely topic. Philip Tabor is also joining us. He's with silver side detectors, which develops neutron detective detection systems. Yet you want to know if early, if neutrons and radiation or in places where you don't want them, So this should be really interesting. And last but not least, Matthew Shields is with the Charlottesville schools and is gonna educate us on how he and his team are educating students in the use of modern engineering tools and techniques. Gentlemen, welcome to the Cuban to the program. This should be really interesting. Thanks for coming on. >>Hi. Or pleasure >>for having us. >>You're very welcome. Okay, let me ask each of you because you're all doing such interesting and compelling work. Let's start with Rafael. Tell us more about the bio hub and your role there, please. >>Okay. Yeah. So you said that I hope is a nonprofit research institution, um, funded by Mark Zuckerberg and his wife, Priscilla Chan. Um, and our main mission is to develop new technologies to help advance medicine and help, hopefully cure and manage diseases. Um, we also have very close collaborations with Universe California, San Francisco, Stanford University and the University California Berkeley on. We tried to bring those universities together, so they collaborate more of biomedical topics. And I manage a team of engineers. They by joining platform. Um, and we're tasked with creating instruments for the laboratory to help the scientist boats inside the organization and also in the partner universities Do their experiments in better ways in ways that they couldn't do before >>in this edition was launched Well, five years ago, >>it was announced at the end of 2016, and we actually started operation with at the beginning of 2017, which is when I joined, um, So this is our third year. >>And how's how's it going? How does it work? I mean, these things take time. >>It's been a fantastic experience. Uh, the organization works beautifully. Um, it was amazing to see it grow From the beginning, I was employee number 12, I think eso When I came in, it was just a nem P office building and empty labs. And very quickly we had something running about. It's amazing eso I'm very proud of the work that we have done to make that possible. Um And then, of course, that's you mentioned now with co vid, um, we've been able to do a lot of very cool work attire being of the pandemic in March, when there was a deficit of testing, uh, capacity in California, we spun up a testing laboratory in record time in about a week. It was crazy. It was a crazy project, Um, but but incredibly satisfying. And we ended up running all the way until the beginning of November, when the lab was finally shut down. We could process about 3000 samples a day. I think at the end of it all, we were able to test about 100 on the order of 100 and 50,000 samples from all over the state. We were providing free testing toe all of the Department of Public Health Department of Public Health in California, which at the media pandemic, had no way to do testing affordably and fast. So I think that was a great service to the state. Now the state has created that testing system that would serve those departments. So then we decided that it was unnecessary to keep going with testing in the other biopsy that would shut down. >>All right. Thank you for that. Now, Now, Philip, you What you do is mind melting. You basically helped keep the world safe. Maybe describe a little bit more about silver sod detectors and what your role is there and how it all works. >>Tour. So we make a nuclear bomb detectors and we also make water detectors. So we try and do our part thio keep the world from blowing up and make it a better place at the same time. Both of these applications use neutron radiation detectors. That's what we make. Put them out by import border crossing places like that. They can help make sure that people aren't smuggling. Shall we say very bad things. Um, there's also a burgeoning field of research and application where you can use neutrons with some pretty cool physics to find water so you could do things. Like what? A detector up in the mountains and measure snowpack. Put it out in the middle of the field and measure soil moisture content. And as you might imagine, there's some really cool applications in, uh, research and agronomy and public policy for this. >>All right, so it's OK, so it's a It's much more than, you know, whatever fighting terrorism, it's there's a riel edge or I kind of i o t application for what you guys >>do. We do both its's to plowshares. You might >>say a mat. I I look at your role is kind of scaling the brain power for for the future. Maybe tell us more about Charlottesville schools and in the mission that you're pursuing and what you do. >>Thank you. Um, I've been in Charlottesville City schools for about 11 or 12 years. I started their teaching, um, a handful of classes, math and science and things like that. But Thescore board and my administration had the crazy idea of starting an engineering program about seven years ago. My background is an engineering is an engineering. My masters is in mechanical and aerospace engineering and um, I basically spent a summer kind of coming up with what might be a fun engineering curriculum for our students. And it started with just me and 30 students about seven years ago, Um, kind of a home spun from scratch curriculum. One of my goals from the outset was to be a completely project based curriculum, and it's now grown. We probably have about six or 700 students, five or six full time teachers. We now have pre engineering going on at the 5th and 6th grade level. I now have students graduating. Uh, you know, graduating after senior year with, like, seven years of engineering under their belt and heading off to doing some pretty cool stuff. So it's It's been a lot of fun building a program and, um, and learning a lot in the process. >>That's awesome. I mean, you know, Cuba's. We've been passionate about things like women in tech, uh, diversity stem. You know, not only do we need more, more students and stem, we need mawr underrepresented women, minorities, etcetera. We were just talking to John Herstek and integrate gration about this is Do you do you feel is though you're I mean, first of all, the work that you do is awesome, but but I'll go one step further. Do you feel as though it's reaching, um, or diverse base? And how is that going? >>That's a great question. I think research shows that a lot of people get funneled into one kind of track or career path or set of interests really early on in their educational career, and sometimes that that funnel is kind of artificial. And so that's one of the reasons we keep pushing back. Um, so our school systems introducing kindergartners to programming on DSO We're trying to push back how we expose students to engineering and to stem fields as early as possible. And we've definitely seen the first of that in my program. In fact, my engineering program, uh, sprung out of an after school in Extracurricular Science Club that actually three girls started at our school. So I think that actually has helped that three girls started the club that eventually is what led to our engineering programs that sort of baked into the DNA and also our eyes a big public school. And we have about 50% of the students are under the poverty line and we e in Charlottesville, which is a big refugee town. And so I've been adamant from Day one that there are no barriers to entry into the program. There's no test you have to take. You don't have to have be taking a certain level of math or anything like that. That's been a lot of fun. To have a really diverse set of kids enter the program and be successful, >>that's final. That's great to hear. So, Philip, I wanna come back to you. You know, I think about maybe some day we'll be able to go back to a sporting events, and I know when I when I'm in there, there's somebody up on the roof looking out for me, you know, watching the crowd, and they have my back. And I think in many ways, the products that you build, you know, our similar. I may not know they're there, but they're keeping us safe or they're measuring things that that that I don't necessarily see. But I wonder if you could talk about a little bit more detail about the products you build and how they're impacting society. >>Sure, so There are certainly a lot of people who are who are watching, trying to make sure things were going well in keeping you safe that you may or may not be aware of. And we try and support ah lot of them. So we have detectors that are that are deployed in a variety of variety of uses, with a number of agencies and governments that dio like I was saying, ports and border crossing some other interesting applications that are looking for looking for signals that should not be there and working closely to fit into the operations these folks do. Onda. We also have a lot of outreach to researchers and scientists trying to help them support the work they're doing. Um, using neutron detection for soil moisture monitoring is a some really cool opportunities for doing it at large scale and with much less, um, expense or complication than would have been done. Previous technologies. Um, you know, they were talking about collaboration in the previous segment. We've been able to join a number of conferences for that, virtually including one that was supposed to be held in Boston, but another one that was held out of the University of Heidelberg in Germany. And, uh, this is sort of things that in some ways, the pandemic is pushing people towards greater collaboration than they would have been able to do. Had it all but in person. >>Yeah, we did. Uh, the cube did live works a couple years ago in Boston. It was awesome show. And I think, you know, with this whole trend toward digit, I call it the Force march to digital. Thanks to cove it I think that's just gonna continue. Thio grow. Rafael. What if you could describe the process that you use to better understand diseases? And what's your organization's involvement? Been in more detail, addressing the cove in pandemic. >>Um, so so we have the bio be structured in, Um um in a way that foster so the combination of technology and science. So we have to scientific tracks, one about infectious diseases and the other one about understanding just basic human biology, how the human body functions, and especially how the cells in the human body function on how they're organized to create tissues in the body. On Ben, it has this set of platforms. Um, mind is one of them by engineering that are all technology rated. So we have data science platform, all about data analysis, machine learning, things like that. Um, we have a mass spectrometry platform is all about mass spectrometry technologies to, um, exploit those ones in service for the scientist on. We have a genomics platform that it's all about sequencing DNA and are gonna, um and then an advanced microscopy. It's all about developing technologies, uh, to look at things with advanced microscopes and developed technologies to marry computation on microscopy. So, um, the scientists set the agenda and the platforms, we just serve their needs, support their needs, and hopefully develop technologies that help them do their experiments better, faster, or allow them to the experiment that they couldn't do in any other way before. Um And so with cove, it because we have that very strong group of scientists that work on have been working on infectious disease before, and especially in viruses, we've been able to very quickly pivot to working on that s O. For example, my team was able to build pretty quickly a machine to automatically purified proteins on is being used to purify all these different important proteins in the cove. It virus the SARS cov to virus Onda. We're sending some of those purified proteins all over the world. Two scientists that are researching the virus and trying to figure out how to develop vaccines, understand how the virus affects the body and all that. Um, so some of the machines we built are having a very direct impact on this. Um, Also for the copy testing lab, we were able to very quickly develop some very simple machines that allowed the lab to function sort of faster and more efficiently. Sort of had a little bit of automation in places where we couldn't find commercial machines that would do it. >>Um, eso Matt. I mean, you gotta be listening to this and thinking about Okay, So someday your students are gonna be working at organizations like like, like Bio Hub and Silver Side. And you know, a lot of young people they're just don't know about you guys, but like my kids, they're really passionate about changing the world. You know, there's way more important than you know, the financial angles and it z e. I gotta believe you're seeing that you're right in the front lines there. >>Really? Um, in fact, when I started the curriculum six or seven years ago, one of the first bits of feedback I got from my students is they said Okay, this is a lot of fun. So I had my students designing projects and programming microcontrollers raspberry, PiS and order we nose and things like that. The first bit of feedback I got from students was they said Okay, when do we get to impact the world? I've heard engineering >>is about >>making the world a better place, and robots are fun and all, but, you know, where is the real impact? And so um, dude, yeah, thanks to the guidance of my students, I'm baking that Maurin. Now I'm like day one of engineering one. We talk about how the things that the tools they're learning and the skills they're gaining, uh, eventually, you know, very soon could be could be used to make the world a better place. >>You know, we all probably heard that famous line by Jeff Hammer Barker. The greatest minds of my generation are trying to figure out how to get people to click on ads. I think we're really generally generationally, finally, at the point where young students and engineering a really, you know, a passionate about affecting society. I wanna get into the product, you know, side and understand how each of you are using on shape and and the value that that it brings. Maybe Raphael, you could start how long you've been using it. You know, what's your experience with it? Let's let's start there. >>I begin for about two years, and I switched to it with some trepidation. You know, I was used to always using the traditional product that you have to install on your computer, that everybody uses that. So I was kind of locked into that. But I started being very frustrated with the way it worked, um, and decided to give on ship chance. Which reputation? Because any change always, you know, causes anxiety. Um, but very quickly my engineers started loving it, Uh, just because it's it's first of all, the learning curve wasn't very difficult at all. You can transfer from one from the traditional product to entree very quickly and easily. You can learn all the concepts very, very fast. It has all the functionality that we needed and and what's best is that it allows to do things that we couldn't do before or we couldn't do easily. Now we can access the our cat documents from anywhere in the world. Um, so when we're in the lab fabricating something or testing a machine, any computer we have next to us or a tablet or on iPhone, we can pull it up and look at the cad and check things or make changes. That's something that couldn't do before because before you had to pay for every installation off the software for the computer, and I couldn't afford to have 20 installations to have some computers with the cat ready to use them like once every six months would have been very inefficient. So we love that part. And the collaboration features are fantastic, especially now with Kobe, that we have to have all the remote meetings eyes fantastic, that you can have another person drive the cad while the whole team is watching that person change the model and do things and point to things that is absolutely revolutionary. We love it. The fact that you have very, very sophisticated version control before it was always a challenge asking people, please, if you create anniversary and apart, how do we name it so that people find it? And then you end up with all these collection of files with names that nobody ever remembers, what they are, the person left. And now nobody knows which version is the right one. A mess with on shape on the version ING system it has, and the fact that you can go back in history off the document and go back to previous version so easily and then go back to the press and version and explore the history of the part that is truly, um, just world changing for us, that we can do that so easily on for me as a manager to manage this collection of information that is critical for our operations. It makes it so much easier because everything is in one place. I don't have to worry about file servers that go down that I have to administer that have to have I t taken care off that have to figure how to keep access to people to those servers when they're at home, and they need a virtual private network and all of that mess disappears. I just simply give give a person in accounting on shape and then magically, they have access to everything in the way I want. And we can manage the lower documents and everything in a way that is absolutely fantastic. >>Feel what was your what? What were some of the concerns you had mentioned? You had some trepidation. Was it a performance? Was it security? You know some of the traditional cloud stuff, and I'm curious as to how, How, whether any of those act manifested really that you had to manage. What were your concerns? >>Look, the main concern is how long is it going to take for everybody in the team to learn to use the system like it and buy into it? Because I don't want to have my engineers using tools against their will write. I want everybody to be happy because that's how they're productive. They're happy, and they enjoyed the tools they have. That was my main concern. I was a little bit worried about the whole concept of not having the files in a place where I couldn't quote unquote seat in some server and on site, but that That's kind of an outdated concept, right? So that took a little bit of a mind shift, but very quickly. Then I started thinking, Look, I have a lot of documents on Google Drive. Like, I don't worry about that. Why would I worry about my cat on on shape, right? Is the same thing. So I just needed to sort of put things in perspective that way. Um, the other, um, you know, the concern was the learning curve, right? Is like, how is he Will be for everybody to and for me to learn it on whether it had all of the features that we needed. And there were a few features that I actually discussed with, um uh, Cody at on shape on, they were actually awesome about using their scripting language in on shape to sort of mimic some of the features of the old cat, uh, in on, shaped in a way that actually works even better than the old system. So it was It was amazing. Yeah, >>Great. Thank you for that, Philip. What's your experience been? Maybe you could take us through your journey within shape. >>Sure. So we've been we've been using on shaped silver side for coming up on about four years now, and we love it. We're very happy with it. We have a very modular product line, so we make anything from detectors that would go into backpacks. Two vehicles, two very large things that a shipping container would go through and saw. Excuse me. Shape helps us to track and collaborate faster on the design. Have multiple people working a same time on a project. And it also helps us to figure out if somebody else comes to us and say, Hey, I want something new how we congrats modules from things that we already have put them together and then keep track of the design development and the different branches and ideas that we have, how they all fit together. A za design comes together, and it's just been fantastic from a mechanical engineering background. I will also say that having used a number of different systems and solid works was the greatest thing since sliced bread. Before I got using on shape, I went, Wow, this is amazing and I really don't want to design in any other platform. After after getting on Lee, a little bit familiar with it. >>You know, it's funny, right? I'll have the speed of technology progression. I was explaining to some young guns the other day how I used to have a daytime er and that was my life. And if I lost that daytime, er I was dead. And I don't know how we weigh existed without, you know, Google maps eso we get anywhere, I don't know, but, uh but so So, Matt, you know, it's interesting to think about, you know, some of the concerns that Raphael brought up, you hear? For instance, you know, all the time. Wow. You know, I get my Amazon bill at the end of the month that zip through the roof in, But the reality is that Yeah, well, maybe you are doing more, but you're doing things that you couldn't have done before. And I think about your experience in teaching and educating. I mean, you so much more limited in terms of the resource is that you would have had to be able to educate people. So what's your experience been with With on shape and what is it enabled? >>Um, yeah, it was actually talking before we went with on shape. We had a previous CAD program, and I was talking to my vendor about it, and he let me know that we were actually one of the biggest CAD shops in the state. Because if you think about it a really big program, you know, really big company might employ. 5, 10, 15, 20 cad guys, right? I mean, when I worked for a large defense contractor, I think there were probably 20 of us as the cad guys. I now have about 300 students doing cat. So there's probably more students with more hours of cat under their belt in my building than there were when I worked for the big defense contractor. Um, but like you mentioned, uh, probably our biggest hurdle is just re sources. And so we want We want one of things I've always prided myself and trying to do in this. Programs provide students with access two tools and skills that they're going to see either in college or in the real world. So it's one of the reason we went with a big professional cad program. There are, you know, sort of K 12 oriented software and programs and things. But, you know, I want my kids coding and python and using slack and using professional type of tools on DSO when it comes to cat. That's just that That was a really hurt. I mean, you know, you could spend $30,000 on one seat of, you know, professional level cad program, and then you need a $30,000 computer to run it on if you're doing a heavy assemblies, Um and so one of my dreams And it was always just a crazy dream. And I was the way I would always pitcher in my school system and say, someday I'm gonna have a kid on a school issued chromebook in subsidized housing, on public WiFi doing professional level bad and that that was a crazy statement until a couple of years ago. So we're really excited that I literally and you know, March and you said the forced march, the forced march into, you know, modernity, March 13th kids sitting in my engineering lab that we spent a lot of money on doing cad March 14th. Those kids were at home on their school issued chromebooks on public WiFi, uh, keeping their designs going and collaborating. And then, yeah, I could go on and on about some of the things you know, the features that we've learned since then they're even better. So it's not like this is some inferior, diminished version of Academy. There's so much about it. Well, I >>wanna I wanna ask you that I may be over my skis on this, but we're seeing we're starting to see the early days of the democratization of CAD and product design. It is the the citizen engineer, I mean, maybe insulting to the engineers in the room, But but is that we're beginning to see that >>I have to believe that everything moves into the cloud. Part of that is democratization that I don't need. I can whether you know, I think artists, you know, I could have a music studio in my basement with a nice enough software package. And Aiken, I could be a professional for now. My wife's a photographer. I'm not allowed to say that I could be a professional photographer with, you know, some cloud based software, and so, yeah, I do think that's part of what we're seeing is more and more technology is moving to the cloud. >>Philip. Rafael Anything you Dad, >>I think I mean, yeah, that that that combination of cloud based cat and then three d printing that is becoming more and more affordable on ubiquitous It's truly transformative, and I think for education is fantastic. I wish when I was a kid I had the opportunity to play with those kinds of things because I was always the late things. But, you know, the in a very primitive way. So, um, I think this is a dream for kids. Teoh be able to do this. And, um, yeah, there's so many other technologies coming on, like Arduino on all of these electronic things that live kids play at home very cheaply with things that back in my day would have been unthinkable. >>So we know there's a go ahead. Philip, please. >>We had a pandemic and silver site moved to a new manufacturing facility this year. I was just on the shop floor, talking with contractors, standing 6 ft apart, pointing at things. But through it all, our CAD system was completely unruffled. Nothing stopped in our development work. Nothing stopped in our support for existing systems in the field. We didn't have to think about it. We had other server issues, but none with our, you know, engineering cad, platform and product development in support world right ahead, which was cool, but also a in that's point. I think it's just really cool what you're doing with the kids. The most interesting secondary and college level engineering work that I did was project based, taken important problem to the world. Go solve it and that is what we do here. That is what my entire career has been. And I'm super excited to see. See what your students are going to be doing, uh, in there home classrooms on their chromebooks now and what they do building on that. >>Yeah, I'm super excited to see your kids coming out of college with engineering degrees because, yeah, I think that Project based experience is so much better than just sitting in a classroom, taking notes and doing math problems on day. I think it will give the kids a much better flavor. What engineering is really about Think a lot of kids get turned off by engineering because they think it's kind of dry because it's just about the math for some very abstract abstract concept on they are there. But I think the most important thing is just that hands on a building and the creativity off, making things that you can touch that you can see that you can see functioning. >>Great. So, you know, we all know the relentless pace of technology progression. So when you think about when you're sitting down with the folks that on shape and there the customer advisor for one of the things that that you want on shape to do that it doesn't do today >>I could start by saying, I just love some of the things that does do because it's such a modern platform. And I think some of these, uh, some some platforms that have a lot of legacy and a lot of history behind them. I think we're dragging some of that behind them. So it's cool to see a platform that seemed to be developed in the modern era, and so that Z it is the Google docks. And so the fact that collaboration and version ing and link sharing is and like platform agnostic abilities, the fact that that seems to be just built into the nature of the thing so far, That's super exciting. As far as things that, uh, to go from there, Um, I don't know, >>Other than price. >>You can't say >>I >>can't say lower price. >>Yeah, so far on P. D. C. S that work with us. Really? Well, so I'm not complaining. There you there, >>right? Yeah. Yeah. No gaps, guys. Whitespace, Come on. >>We've been really enjoying the three week update. Cadence. You know, there's a new version every three weeks and we don't have to install it. We just get all the latest and greatest goodies. One of the trends that we've been following and enjoying is the the help with a revision management and release work flows. Um, and I know that there's more than on shape is working on that we're very excited for, because that's a big important part about making real hardware and supporting it in the field. Something that was cool. They just integrated Cem markup capability. In the last release that took, we were doing that anyway, but we were doing it outside of on shapes. And now we get to streamline our workflow and put it in the CAD system where We're making those changes anyway when we're reviewing drawings and doing this kind of collaboration. And so I think from our perspective, we continue to look forward. Toa further progress on that. There's a lot of capability in the cloud that I think they're just kind of scratching the surface on you, >>right? I would. I mean, you're you're asking to knit. Pick. I would say one of the things that I would like to see is is faster regeneration speed. There are a few times with convicts, necessities that regenerating the document takes a little longer than I would like. It's not a serious issue, but anyway, I I'm being spoiled, >>you know? That's good. I've been doing this a long time, and I like toe ask that question of practitioners and to me, it It's a signal like when you're nit picking and that's what you're struggling to knit. Pick that to me is a sign of a successful product, and and I wonder, I don't know, uh, have the deep dive into the architecture. But are things like alternative processors. You're seeing them hit the market in a big way. Uh, you know, maybe helping address the challenge, But I'm gonna ask you the big, chewy question now. Then we maybe go to some audience questions when you think about the world's biggest problems. I mean, we're global pandemics, obviously top of mind. You think about nutrition, you know, feeding the global community. We've actually done a pretty good job of that. But it's not necessarily with the greatest nutrition, climate change, alternative energy, the economic divides. You've got geopolitical threats and social unrest. Health care is a continuing problem. What's your vision for changing the world and how product innovation for good and be applied to some of the the problems that that you all are passionate about? Big question. Who wants toe start? >>Not biased. But for years I've been saying that if you want to solve the economy, the environment, uh, global unrest, pandemics, education is the case. If you wanna. If you want to, um, make progress in those in those realms, I think funding funding education is probably gonna pay off pretty well. >>Absolutely. And I think Stam is key to that. I mean, all of the ah lot of the well being that we have today and then industrialized countries. Thanks to science and technology, right improvements in health care, improvements in communication, transportation, air conditioning. Um, every aspect of life is touched by science and technology. So I think having more kids studying and understanding that is absolutely key. Yeah, I agree, >>Philip, you got anything to add? >>I think there's some big technical problems in the world today, Raphael and ourselves there certainly working on a couple of them. Think they're also collaboration problems and getting everybody to be able to pull together instead of pulling separately and to be able to spur the ideas on words. So that's where I think the education side is really exciting. What Matt is doing and it just kind of collaboration in general when we could do provide tools to help people do good work. Uh, that is, I think, valuable. >>Yeah, I think that's a very good point. And along those lines, we have some projects that are about creating very low cost instruments for low research settings, places in Africa, Southeast Asia, South America, so that they can do, um, um, biomedical research that it's difficult to do in those place because they don't have the money to buy the fancy lab machines that cost $30,000 an hour. Um, so we're trying to sort of democratize some of those instruments. And I think thanks to tools like Kahn shape then is easier, for example, to have a conversation with somebody in Africa and show them the design that we have and discuss the details of it with them on. But it's amazing, right to have somebody, you know, 10 time zones away, Um, looking really life in real time with you about your design and discussing the details or teaching them how to build a machine, right? Because, um, you know, they have a three D printer. You can you can just give them the design and say like, you build it yourself, uh, even cheaper than and, you know, also billing and shipping it there. Um, so all that that that aspect of it is also super important. I think for any of these efforts to improve some of the hardest part was in the world for climate change. Do you say, as you say, poverty, nutrition issues? Um, you know, availability of water. You have that project at about finding water. Um, if we can also help deploy technologies that teach people remotely how to create their own technologies or how to build their own systems that will help them solve those forms locally. I think that's very powerful. >>Yeah, the point about education is right on. I think some people in the audience may be familiar with the work of Erik Brynjolfsson and Andrew McAfee, the second machine age where they sort of put forth the premise that, uh, is it laid it out. Look, for the first time in history, machines air replacing humans from a cognitive perspective. Machines have always replaced humans, but that's gonna have an impact on jobs. But the answer is not toe protect the past from the future. The answer is education and public policy that really supports that. So I couldn't agree more. I think it's a really great point. Um, we have We do have some questions from the audience. If if we could If I can ask you guys, um, you know, this one kind of stands out. How do you see artificial intelligence? I was just talking about machine intelligence. Um, how do you see that? Impacting the design space guys trying to infuse a I into your product development. Can you tell me? >>Um, absolutely, like, we're using AI for some things, including some of these very low cost instruments that will hopefully help us diagnose certain diseases, especially this is that are very prevalent in the Third World. Um, and some of those diagnostics are these days done by thes armies of technicians that are trained to look under the microscope. But, um, that's a very slow process. Is very error prone and having machine learning systems that can to the same diagnosis faster, cheaper and also little machines that can be taken to very remote places to these villages that have no access to a fancy microscope. To look at a sample from a patient that's very powerful. And I we don't do this, but I have read quite a bit about how certain places air using a Tribune attorneys to actually help them optimize designs for parts. So you get these very interesting looking parts that you would have never thought off a person would have never thought off, but that are incredibly light ink. Earlier, strong and I have all sort of properties that are interesting thanks to artificial intelligence machine learning in particular >>yet another. The advantage you get when when your work is in the cloud I've seen. I mean, there's just so many applications that so if the radiology scan is in the cloud and the radiologist is goes to bed at night, Radiologist could come in in the morning and and say, Oh, the machine while you were sleeping was using artificial intelligence to scan these 40,000 images. And here's the five that we picked out that we think you should take a closer look at. Or like Raphael said, I can design my part. My, my, my, my, my you know, mount or bracket or whatever and go to sleep. And then I wake up in the morning. The machine has improved. It for me has made it strider strider stronger and lighter. Um And so just when your when your work is in the cloud, that's just that's a really cool advantage that you get that you can have machines doing some of your design work for you. >>Yeah, we've been watching, uh, you know, this week is this month, I guess is AWS re invent and it's just amazing to see how much effort is coming around machine learning machine intelligence. You know Amazon has sage maker Google's got, you know, embedded you no ML and big query. Uh, certainly Microsoft with Azure is doing tons of stuff and machine learning. I think the point there is that that these things will be infused in tow R and D and in tow software product by the vendor community. And you all will apply that to your business and and build value through the unique data that your collecting, you know, in your ecosystems. And and that's how you add value. You don't have to be necessarily, you know, developers of artificial intelligence, but you have to be practitioners to apply that. Does that make sense to you, Philip? >>Yeah, absolutely. And I think your point about value is really well chosen. We see AI involved from the physics simulations all the way up to interpreting radiation data, and that's where the value question, I think, is really important because it's is the output of the AI giving helpful information that the people that need to be looking at it. So if it's curating a serious of radiation alert, saying, Hey, like these air the anomalies. You need to look at eyes it, doing that in a way that's going to help a good response on. In some cases, the II is only as good as the people. That sort of gave it a direction and turn it loose. And you want to make sure that you don't have biases or things like that underlying your AI that they're going to result in less than helpful outcomes coming from it. So we spend quite a lot of time thinking about how do we provide the right outcomes to people who are who are relying on our systems? >>That's a great point, right? Humans air biased and humans build models, so models are inherently biased. But then the software is hitting the market. That's gonna help us identify those biases and help us, you know? Of course. Correct. So we're entering Cem some very exciting times, guys. Great conversation. I can't thank you enough for spending the time with us and sharing with our audience the innovations that you're bringing to help the world. So thanks again. >>Thank you so much. >>Thank you. >>Okay. Welcome. Okay. When we come back, John McElheny is gonna join me. He's on shape. Co founder. And he's currently the VP of strategy at PTC. He's gonna join the program. We're gonna take a look at what's next and product innovation. I'm Dave Volonte and you're watching innovation for good on the Cube, the global leader. Digital technology event coverage. We'll be right back. >>Okay? Okay. Yeah. Okay. >>From around >>the globe, it's the Cube. Presenting innovation for good. Brought to you by on shape. >>Okay, welcome back to innovation. For good. With me is John McElheny, who is one of the co founders of On Shape and is now the VP of strategy at PTC. John, it's good to see you. Thanks for making the time to come on the program. Thanks, Dave. So we heard earlier some of the accomplishments that you've made since the acquisition. How has the acquisition affected your strategy? Maybe you could talk about what resource is PTC brought to the table that allowed you toe sort of rethink or evolve your strategy? What can you share with us? >>Sure. You know, a year ago, when when John and myself met with Jim Pepperman early on is we're we're pondering. Started joining PTC one of things became very clear is that we had a very clear shared vision about how we could take the on shape platform and really extended for, for all of the PTC products, particular sort of their augmented reality as well as their their thing works or the i o. T business and their product. And so from the very beginning there was a clear strategy about taking on shape, extending the platform and really investing, um, pretty significantly in the product development as well as go to market side of things, uh, toe to bring on shape out to not only the PTC based but sort of the broader community at large. So So So PTC has been a terrific, terrific, um, sort of partner as we've we've gonna go on after this market together. Eso We've added a lot of resource and product development side of things. Ah, lot of resource and they go to market and customer success and support. So, really, on many fronts, that's been both. Resource is as well a sort of support at the corporate level from from a strategic standpoint and then in the field, we've had wonderful interactions with many large enterprise customers as well as the PTC channels. So it's been really a great a great year. >>Well, and you think about the challenges of in your business going to SAS, which you guys, you know, took on that journey. You know, 78 years ago. Uh, it's not trivial for a lot of companies to make that transition, especially a company that's been around as long as PTC. So So I'm wondering how much you know, I was just asking you How about what PCP TC brought to the table? E gotta believe you're bringing a lot to the table to in terms of the mindset, uh, even things is, is mundane is not the right word, but things like how you compensate salespeople, how you interact with customers, the notion of a service versus a product. I wonder if you could address >>that. Yeah, it's a it's a really great point. In fact, after we had met Jim last year, John and I one of the things we walked out in the seaport area in Boston, one of things we sort of said is, you know, Jim really gets what we're trying to do here and and part of let me bring you into the thinking early on. Part of what Jim talked about is there's lots of, you know, installed base sort of software that's inside of PTC base. That's helped literally thousands of customers around the world. But the idea of moving to sass and all that it entails both from a technology standpoint but also a cultural standpoint. Like How do you not not just compensate the sales people as an example? But how do you think about customer success? In the past, it might have been that you had professional services that you bring out to a customer, help them deploy your solutions. Well, when you're thinking about a SAS based offering, it's really critical that you get customers successful with it. Otherwise, you may have turned, and you know it will be very expensive in terms of your business long term. So you've got to get customers success with software in the very beginning. So you know, Jim really looked at on shape and he said that John and I, from a cultural standpoint, you know, a lot of times companies get acquired and they've acquired technology in the past that they integrate directly into into PTC and then sort of roll it out through their products, are there just reached channel, he said. In some respects, John John, think about it as we're gonna take PTC and we want to integrate it into on shape because we want you to share with us both on the sales side and customer success on marketing on operations. You know all the things because long term, we believe the world is a SAS world, that the whole industry is gonna move too. So really, it was sort of an inverse in terms of the thought process related to normal transactions >>on That makes a lot of sense to me. You mentioned Sharon turns the silent killer of a SAS company, and you know, there's a lot of discussion, you know, in the entrepreneurial community because you live this, you know what's the best path? I mean today, You see, you know, if you watch Silicon Valley double, double, triple triple, but but there's a lot of people who believe, and I wonder, if you come in there is the best path to, you know, in the X Y axis. If if it's if it's uh, growth on one and retention on the other axis. What's the best way to get to the upper right on? Really? The the best path is probably make sure you've nailed obviously the product market fit, But make sure that you can retain customers and then throw gas on the fire. You see a lot of companies they burn out trying to grow too fast, but they haven't figured out, you know that. But there's too much churn. They haven't figured out those metrics. I mean, obviously on shape. You know, you were sort of a pioneer in here. I gotta believe you've figured out that customer retention before you really, You know, put the pedal to the >>metal. Yeah, and you know, growth growth can mask a lot of things, but getting getting customers, especially the engineering space. Nobody goes and sits there and says, Tomorrow we're gonna go and and, you know, put 100 users on this and and immediately swap out all of our existing tools. These tools are very rich and deep in terms of capability, and they become part of the operational process of how a company designs and builds products. So any time anybody is actually going through the purchasing process. Typically, they will run a try along or they'll run a project where they look at. Kind of What? What is this new solution gonna help them dio. How are we gonna orient ourselves for success? Longer term. So for us, you know, getting new customers and customer acquisition is really critical. But getting those customers to actually deploy the solution to be successful with it. You know, we like to sort of, say, the marketing or the lead generation and even some of the initial sales. That's sort of like the Kindle ing. But the fire really starts when customers deploy it and get successful. The solution because they bring other customers into the fold. And then, of course, if they're successful with it, you know, then in fact, you have negative turn which, ironically, means growth in terms of your inside of your install. Bates. >>Right? And you've seen that with some of the emerging, you know, SAS companies, where you're you're actually you know, when you calculate whatever its net retention or renew ALS, it's actually from a dollar standpoint. It's up in the high nineties or even over 100%. >>So >>and that's a trend we're gonna continue. See, I >>wonder >>if we could sort of go back. Uh, and when you guys were starting on shape, some of the things that you saw that you were trying to strategically leverage and what's changed, you know, today we were talking. I was talking to John earlier about in a way, you kinda you kinda got a blank slate is like doing another startup. >>You're >>not. Obviously you've got installed base and customers to service, but But it's a new beginning for you guys. So one of the things that you saw then you know, cloud and and sas and okay, but that's we've been there, done that. What are you seeing? You know today? >>Well, you know, So So this is a journey, of course, that that on shape on its own has gone through it had I'll sort of say, you know, several iterations, both in terms of of of, you know, how do you How do you get customers? How do you How do you get them successful? How do you grow those customers? And now that we've been part of PTC, the question becomes okay. One, There is certainly a higher level of credibility that helps us in terms of our our megaphone is much bigger than it was when we're standalone company. But on top of that now, figuring out how to work with their channel with their direct sales force, you know, they have, um, for example, you know, very large enterprises. Well, many of those customers are not gonna go in forklift out their existing solution to replace it with with on shape. However, many of them do have challenges in their supply chain and communications with contractors and vendors across the globe. And so, you know, finding our fit inside of those large enterprises as they extend out with their their customers is a very interesting area that we've really been sort of incremental to to PTC. And then, you know, they they have access to lots of other technology, like the i o. T business. And now, of course, the augmented reality business that that we can bring things to bear. For example, in the augmented reality world, they've they've got something called expert capture. And this is essentially imagine, you know, in a are ah, headset that allows you to be ableto to speak to it, but also capture images still images in video. And you could take somebody who's doing their task and capture literally the steps that they're taking its geo location and from their builds steps for new employees to be, we'll learn and understand how todo use that technology to help them do their job better. Well, when they do that, if there is replacement products or variation of of some of the tools that that they built the original design instruction set for they now have another version. Well, they have to manage multiple versions. Well, that's what on shape is really great at doing and so taking our technology and helping their solutions as well. So it's not only expanding our customer footprint, it's expanding the application footprint in terms of how we can help them and help customers. >>So that leads me to the tam discussion and again, as part of your strategist role. How do you think about that? Was just talking to some of your customers earlier about the democratization of cat and engineering? You know, I kind of joked, sort of like citizen engineering, but but so that you know, the demographics are changing the number of users potentially that can access the products because the it's so much more of a facile experience. How are you thinking about the total available market? >>It really is a great question, You know, it used to be when you when you sold boxes of software, it was how many engineers were out there. And that's the size of the market. The fact that matter is now when, When you think about access to that information, that data is simply a pane of glass. Whether it's a computer, whether it's a laptop, UH, a a cell phone or whether it's a tablet, the ability to to use different vehicles, access information and data expands the capabilities and power of a system to allow feedback and iteration. I mean, one of the one of the very interesting things is in technology is when you can take something and really unleash it to a larger audience and builds, you know, purpose built applications. You can start to iterate, get better feedback. You know there's a classic case in the clothing industry where Zara, you know, is a fast sort of turnaround. Agile manufacturer. And there was a great New York Times article written a couple years ago. My wife's a fan of Zara, and I think she justifies any purchases by saying, You know, Zara, you gotta purchase it now. Otherwise it may not be there the next time. Yet you go back to the store. They had some people in a store in New York that had this woman's throw kind of covering Shaw. And they said, Well, it would be great if we could have this little clip here so we can hook it through or something. And they sent a note back toe to the factory in Spain, and literally two weeks later they had, you know, 4000 of these things in store, and they sold out because they had a closed loop and iterative process. And so if we could take information and allow people access in multiple ways through different devices and different screens, that could be very specific information that, you know, we remove a lot of the engineering data book, bring the end user products conceptually to somebody that would have had to wait months to get the actual physical prototype, and we could get feedback well, Weaken have a better chance of making sure whatever product we're building is the right product when it ultimately gets delivered to a customer. So it's really it's a much larger market that has to be thought of rather than just the kind of selling A boxes software to an engineer. >>That's a great story. And again, it's gonna be exciting for you guys to see that with. The added resource is that you have a PTC, Um, so let's talk. I promise people we wanna talk about Atlas. Let's talk about the platform. A little bit of Atlas was announced last year. Atlas. For those who don't know it's a SAS space platform, it purports to go beyond product lifecycle management and you You're talking cloud like agility and scale to CAD and product design. But John, you could do a better job than I. What do >>we need to know about Atlas? Well, I think Atlas is a great description because it really is metaphorically sort of holding up all of the PTC applications themselves. But from the very beginning, when John and I met with Jim, part of what we were intrigued about was that he shared a vision that on shape was more than just going to be a cad authoring tool that, in fact, you know, in the past these engineering tools were very powerful, but they were very narrow in their purpose and focus. And we had specialty applications to manage the versions, etcetera. What we did in on shape is we kind of inverted that thinking. We built this collaboration and sharing engine at the core and then kind of wrap the CAD system around it. But that collaboration sharing and version ING engine is really powerful. And it was that vision that Jim had that he shared that we had from the beginning, which was, how do we take this thing to make a platform that could be used for many other applications inside of inside of any company? And so not only do we have a partner application area that is is much like the APP store or Google play store. Uh, that was sort of our first Stan Shih ation of this. This this platform. But now we're extending out to broader applications and much meatier applications. And internally, that's the thing works in the in the augmented reality. But there'll be other applications that ultimately find its way on top of this platform. And so they'll get all the benefits of of the collaboration, sharing the version ing the multi platform, multi device. And that's an extremely extremely, um, strategic leverage point for the company. >>You know, it's interesting, John, you mentioned the seaport before. So PTC, for those who don't know, built a beautiful facility down at the Seaport in Boston. And, of course, when PTC started, you know, back in the mid 19 eighties, there was nothing at the seaport s. >>So it's >>kind of kind of ironic, you know, we were way seeing the transformation of the seaport. We're seeing the transformation of industry and of course, PTC. And I'm sure someday you'll get back into that beautiful office, you know? Wait. Yeah, I'll bet. And, uh and but I wanna bring this up because I want I want you to talk about the future. How you how you see that our industry and you've observed this has moved from very product centric, uh, plat platform centric with sass and cloud. And now we're seeing ecosystems form around those products and platforms and data flowing through the ecosystem powering, you know, new innovation. I wonder if you could paint a picture for us of what the future looks like to you from your vantage point. >>Yeah, I think one of the key words you said there is data because up until now, data for companies really was sort of trapped in different applications. And it wasn't because people were nefarious and they want to keep it limited. It was just the way in which things were built. And, you know, when people use an application like on shape, what ends up happening is there their day to day interaction and everything that they do is actually captured by the platform. And, you know, we don't have access to that data. Of course it's it's the customer's data. But as as an artifact of them using the system than doing their day to day job, what's happening is they're creating huge amounts of information that can then be accessed and analyzed to help them both improve their design process, improve their efficiencies, improve their actual schedules in terms of making sure they can hit delivery times and be able to understand where there might be roadblocks in the future. So the way I see it is companies now are deploying SAS based tools like on shape and an artifact of them. Using that platform is that they have now analytics and tools to better understand and an instrument and manage their business. And then from there, I think you're going to see, because these systems are all you know extremely well. Architected allow through, you know, very structured AP. I calls to connect other SAS based applications. You're gonna start seeing closed loop sort of system. So, for example, people design using on shape, they end up going and deploying their system or installing it, or people use the end using products. People then may call back into the customers support line and report issues, problems, challenges. They'll be able to do traceability back to the underlying design. They'll be able to do trend analysis and defect analysis from the support lines and tie it back and closed loop the product design, manufacture, deployment in the field sort of cycles. In addition, you can imagine there's many things that air sort of as designed. But then when people go on site and they have to install it. There's some alterations modifications. Think about think about like a large air conditioning units for buildings. You go and you go to train and you get a large air conditioning unit that put up on top of building with a crane. They have to build all kinds of adaptors to make sure that that will fit inside of the particulars of that building. You know, with on shape and tools like this, you'll be able to not only take the design of what the air conditioning system might be, but also the all the adapter plates, but also how they installed it. So it sort of as designed as manufactured as stalled. And all these things can be traced, just like if you think about the transformation of customer service or customer contacts. In the early days, you used to have tools that were PC based tools called contact management solution, you know, kind of act or gold mine. And these were basically glorified Elektronik role in Texas. It had a customer names and they had phone numbers and whatever else. And Salesforce and Siebel, you know, these types of systems really broadened out the perspective of what a customer relationship? Waas. So it wasn't just the contact information it was, you know, How did they come to find out about you as a company? So all of the pre sort of marketing and then kind of what happens after they become a customer and it really was a 3 60 view. I think that 3 60 view gets extended to not just to the customers, but also tools and the products they use. And then, of course, the performance information that could come back to the manufacturer. So, you know, as an engineer, one of the things you learn about with systems is the following. And if you remember, when the CD first came out CDs that used to talk about four times over sampling or eight times over sampling and it was really kind of, you know, the fidelity the system. And we know from systems theory that the best way to improve the performance of a system is to actually have more feedback. The more feedback you have, the better system could be. And so that's why you get 16 60 for example, etcetera. Same thing here. The more feedback we have of different parts of a company that a better performance, The company will be better customer relationships. Better, uh, overall financial performance as well. So that's that's the view I have of how these systems all tied together. >>It's a great vision in your point about the data is I think right on. It used to be so fragmented in silos, and in order to take a system view, you've gotta have a system view of the data. Now, for years, we've optimized maybe on one little component of the system and that sometimes we lose sight of the overall outcome. And so what you just described, I think is, I think sets up. You know very well as we exit. Hopefully soon we exit this this covert era on John. I hope that you and I can sit down face to face at a PTC on shape event in the near term >>in the seaport in the >>seaport would tell you that great facility toe have have an event for sure. It >>z wonderful >>there. So So John McElhinney. Thanks so much for for participating in the program. It was really great to have you on, >>right? Thanks, Dave. >>Okay. And I want to thank everyone for participating. Today we have some great guest speakers. And remember, this is a live program. So give us a little bit of time. We're gonna flip this site over toe on demand mode so you can share it with your colleagues and you, or you can come back and and watch the sessions that you heard today. Uh, this is Dave Volonte for the Cube and on shape PTC. Thank you so much for watching innovation for good. Be well, Have a great holiday. And we'll see you next time. Yeah.

>>from around the globe. It's the Cube presenting innovation for good. Brought to >>you by on shape. Okay, welcome back to innovation. For good. With me is John McElheny, who is one of the co founders of on Shape and is now the VP of strategy at PTC. John, good to see you. Thanks for making the time to come on the program. Thanks, Dave. So we heard earlier some of the accomplishments that you've made since the acquisition. How has the acquisition affected your strategy? Maybe you could talk about what resource is PTC brought to the table that allowed you toe sort of rethink or evolve your strategy? What can you share with us? >>Sure. You know, a year ago when John and myself met with Jim Hempleman early on is we're we're pondering started joining PTC. One of things became very clear is that we had a very clear shared vision about how we could take the on shape platform and really extended for for all of the PTC products, particular sort of their augmented reality as well as their their thing works or the i o. T business and their product. And so from the very beginning, there was a clear strategy about taking on shape, extending the platform and really investing, um, pretty significantly in the product development as well as go to market side of things, uh, toe to bring on shape out to not only the PTC based but sort of the broader community at large. So So So PTC has been terrific. Terrific, um, sort of partner as we've we've gonna go on after this market together. Eso we've added a lot of resource and product development side of things. Ah, lot of resource and to go to market and customer success and support. So really, on many fronts, that's with both resource is, as well a sort of support at the corporate level from from a strategic standpoint and then in the field, we've had wonderful interactions with many large enterprise customers as well as the PTC channels. So it's been really a great a great year. >>Well, and you think about the challenges of your business going to sas what you guys, you know, took on that journey, you know, 78 years ago. Uh, it's not trivial for a lot of companies to make that transition, especially company. That's been around as long as PTC. So So I'm wondering how much you know, I was just asking you what PC PTC brought the table. E gotta believe you're bringing a lot to the table to in terms of the mindset, uh, even things is, is mundane is not the right word. But things like how you compensate sales people, how you interact with customers, the notion of a service versus a product. I wonder if you could address >>that. Yeah, it's a It's a really great point. In fact, after we had met Jim last year, John and I one of the things we walked out in the seaport area in Boston one of things we sort of said is you know, Jim really gets what we're trying to do here and and part of let me bring you into the thinking early on. Part of what Jim talked about is there's lots of, you know, installed base sort of software that's inside of PTC base. That helped literally thousands of customers around the world. But the idea of moving to sass and all that it entails both from a technology standpoint, but also a cultural standpoint, like how do you not not just compensate the sales people as an example? But how do you think about customers? Success? In the past, it might have been that you had professional services that you bring out to a customer, help them deploy your solutions. Well, when you're thinking about a SAS based offering, it's really critical that you get customers successful with it. Otherwise, you may have turned, and you know it will be very expensive in terms of your business long term. So you've got to get customers success with software in the very beginning. So you know, Jim really looked at on shape and he said that John and I from a cultural standpoint, you know, a lot of times companies get acquired and they've acquired technology in the past that they integrate directly into into PTC and then sort of roll it out through their products or their distribution channels, he said. In some respects, John John, think about it as we're gonna take PTC and we want to integrate it into on shape because we want you to share with us both on the sales side and customer success on marketing on operations, you know, all the things because long term, we believe the world is a SAS world, that the whole industry is gonna move too. So, really, it was sort of an inverse in terms of the thought process related to normal transactions >>on that makes a lot of sense to me. You mentioned Sharon turns the silent killer of a SAS company. And you know, there's a lot of discussion, you know, in the entrepreneurial community because you live this, you know, what's the best path? I mean, today, you see, you know, you you watch Silicon Valley double, double, triple triple. But but there's a lot of people who believe, and I wonder, if you come in there is the best path to, you know, in the X Y axis. If if it's if it's, uh, growth on one and retention on the other axis, what's the best way to get to the upper right on? Really, the the best path is probably make sure you've nailed obviously the product market fit, but make sure that you can retain customers and then throw gas on the fire. You see a lot of companies they burn out trying to grow too fast, but they haven't figured out, you know that. But there's too much churn. They haven't figured out those metrics. I mean, obviously on shape. You know, you were sort of a pioneer in here. I gotta believe you've figured out that customer retention before you really? You know, put the pedal to the >>metal. Yeah. And you know, growth growth can mask a lot of things, but getting getting customers, especially the engineering space. Nobody goes and sits there and says, Tomorrow we're gonna go and and, you know, put 100 users on this and and immediately swap out all of our existing tools. These tools are very rich and deep in terms of capability, and they become part of the operational process of how a company designs and builds products. So any time anybody is actually going through the purchasing process, typically they will run a try along or they'll run a project where they look at Kind of What? What is this new solution gonna help them dio. How are we gonna orient ourselves for success? Longer term. So for us, you know, getting new customers and customer acquisition is really critical. But getting those customers to actually deploy the solution to be successful with it. You know, we like to sort of, say, the marketing or the lead generation and even some of the initial sales. That's sort of like the Kindle ing. But the fire really starts when customers deploy it and get successful with the solution because they bring other customers into the fold. And then, of course, if they're successful with it, you know, then in fact, you have negative turn which, ironically, means growth in terms of your inside of your install Bates. >>Right? And you've seen that with some of the emerging, you know, SAS companies, where you're you're actually you know, when you calculate whatever its net retention or renew ALS, it's actually from a dollar standpoint that's up in the high nineties or even over 100% >>so and >>that's a trend we're gonna continue. See, I wonder if we could sort of go back. Uh, and when you guys were starting on shape, some of the things that you saw that you were trying to strategically leverage and what's changed, you know, today we were talking. I was talking to John earlier about in a way, you kinda you kinda got a blank slate is like doing another startup. You're not. Obviously you've got installed base and customers to service, but but it's a new beginning for you guys. So one of the things that you saw then you know, cloud and and sas and okay, but that's we've been there, done that. What are you seeing? You know, today? >>Well, you know, So So this is a journey, of course, that that on shape on its own has gone through. And had, I'll sort of say, you know, several iterations, both in terms of of of, you know, how do you How do you get customers? How do you How do you get them successful? How do you grow those customers? And now that we've been part of PTC, the question becomes okay, One, there is certainly a higher level of credibility that helps us in terms of our our megaphone is much bigger than it was when we're standalone company. But on top of that now, figuring out how to work with their channel with their direct sales force, you know, they have, um, for example, you know, very large enterprises. Well, many of those customers are not gonna go in forklift out their existing solution to replace it with with on shape. However, many of them do have challenges in their supply chain and communications with contractors and vendors across the globe. And so, you know, finding our fit inside of those large enterprises as they extend out with their their customers is a very interesting area that we've really been sort of incremental to to PTC. And then, you know, they they have access to lots of other technology, like the i O. T business. And now, of course, the augmented reality business that that we can bring things to bear. For example, in the augmented reality world they've they've got something called expert capture. And this is essentially imagined, you know, in a are, ah, headset that allows you to be ableto to speak to it but also capture images, still images in video, and you could take somebody who's doing their task and capture literally the steps that they're taking its geo location and from their builds steps for new employees. We'll learn and understand how todo use that technology to help them do their job better. Well, when they do that if there is replacement products or variation of of some of the tools that that they built the original design instruction set for they now have another version. Well, they have to manage multiple versions. Well, that's what on shape is really great at doing and so taking our technology and helping their solutions as well. So it's not only expanding our customer footprint, it's expanding the application footprint in terms of how we can help them and help customers. >>So that leads me to the tam discussion. And again, it was part of your strategist role. How do you think about that? Was just talking to some of your customers earlier about the democratization of cat and engineering. You know, I kind of joked, sort of like citizen engineering, but but so that, you know, the demographics are changing the number of users potentially that can access the products because the it's so much more of a facile experience. How are you thinking about the total available market? >>It really is a great question, you know, It used to be when you when you sold boxes of software, it was how many engineers were out there, and that's the size of the market. The fact that matter is now when, When you think about access to that information, that data is simply a pane of glass. Whether it's a computer, whether it's a laptop, uh, a cell phone or whether it's a tablet, the ability to to use different vehicles, access information and data expands the capabilities and power of a system to allow feedback and iteration. I mean, one of the one of the very interesting things is in technology is when you can take something and really unleash it to a larger audience and builds, you know, purpose built applications. You can start to iterate, get better feedback. You know, there's a classic case in the clothing industry where Zara, you know, is a fast, sort of turnaround agile manufacturer. And there was a great New York Times article written a couple years ago. My wife's a fan of Zara, and I think she justifies any purchases by saying, you know, was Are you gotta purchase it now. Otherwise it may not be there the next time. Yet you go back to the store. They had some people in the store in New York that had this woman's throw kind of covering Shaw, and they said, Well, it would be great if we could have this little clip here so we could hook it through or something. And they sent a note back toe to the factory in Spain and literally two weeks later they had, you know, 4000 of these things in store, and they sold out because they had a closed loop and iterative process. And so if we could take information and allow people access in multiple ways through different devices and different screens, that could be very specific information that, you know, we remove a lot of the engineering data book, bring the end user products conceptually to somebody that would have had to wait months to get the actual physical prototype, and we could get feedback. Well, Weaken have a better chance of making sure whatever product we're building is the right product when it ultimately gets delivered to a customer. So it's really it's a much larger market that has to be thought of rather than just the kind of selling a boxes off where to an engineer, >>that's a great story, and and again, it's gotta be exciting for you guys to see that on day with the added resource is that you have a PTC eso. Let's talk. I promise people we want to talk about Atlas. Let's talk about the platform. A little bit of Atlas was announced last year. Atlas. For those who don't know it's a SAS space platform, it purports to go beyond product lifecycle management and you you're talking cloudlike agility and scale to CAD and product design. But, John, you could do a better job than I. What do >>we need to know about Atlas? Well, I think Atlas is a great description because it really is metaphorically, sort of holding up all of the PTC applications themselves. But from the very beginning, when John and I met with Jim, part of what we were intrigued about was that he shared a vision that on shape was more than just going to be a cad authoring tool that, in fact, you know, in the past, these engineering tools were very powerful, but they were very narrow in their purpose and focus, and we had specialty applications to manage diversions, etcetera. What we did in on shape is we kind of inverted that thinking we built this collaboration and sharing engine at the core and then kind of wrap the CAD system around it. But that collaboration sharing and version ING engine is really powerful. And it was that vision that Jim had that he shared that we had from the beginning, which was, how do we take this thing to make a platform that could be used for many other applications inside of inside of any company? And so not only do we have a partner application area that is is much like the APP store or Google play store. Uh, that was sort of our first misty initiation of this this this platform. But now we're extending out to broader applications and much meatier applications. And internally, that's the thing works in the in the augmented reality. But there'll be other applications that ultimately find its way on top of this platform, and so they'll get all the benefits of of the collaboration, sharing the version ing the multi platform multi device. And that's an extremely extremely, um, strategic leverage point for the company. >>You know, it's interesting, John, you mentioned the seaport before, So PTC For those who don't know built a beautiful facility down at the seaport in Boston. And of course, when PTC started back in the mid 19 eighties, this there was nothing at the seaport s. >>So it's >>kind of kind of ironic, you know, we were way seeing the transformation of the seaport. We're seeing the transformation of industry and of course, PTC. And I'm sure someday you'll get back into that beautiful office, you know? Wait. Yeah, I'll Bet. And, uh and but I wanna bring this up because I want I want you to talk about the future. How you how you see that our industry and you've observed this has moved from very product centric, uh, plat platform centric with sass and cloud. And now we're seeing ecosystems form around those products and platforms and in data flowing through the ecosystem, powering you new innovation. I wonder if you could paint a picture for us of what the future looks like to you from your vantage point. >>Yeah, I think one of the key words you said there is data because up until now, data for companies really was sort of trapped in different applications. And it wasn't because people with nefarious and they want to keep it limited. It was just the way in which things were built, and you know, when people use an application like on shape, what ends up happening is there their day to day interactions and everything that they dio is actually captured by the platform. And you know, we don't have access to that data. Of course it's it's the customer's data. But as as an artifact of them using the system than doing their day to day job, what's happening is they're creating huge amounts of information that can then be accessed and analyzed to help them both improve their design process, improve their efficiencies, improve their actual schedules in terms of making sure they can hit delivery times and be able to understand where there might be roadblocks in the future. So the way I see it is, companies now are deploying SAS based tools like an shape and an artifact of them. Using that platform is that they have now analytics and tools to better understand and an instrument and manage their business. And then from there, I think you're going to see, because these systems are all you know extremely well. architected allow through, you know, very structured AP. I calls to connect other SAS based applications. You're gonna start seeing closed loop sort of system. So, for example, people design using on shape. They end up going and deploying their system or installing it, or people use the end using products. People then may call back into the customers support line and report issues problems, challenges. They'll be able to do traceability back to the underlying design. They'll be able to do trend analysis and defect analysis from the support lines and tie it back and closed loop the product design, manufacture, deployment in the field sort of cycles. In addition, you can imagine there's many things that air sort of as designed. But then when people go on site and they have to install it, there's some alterations modifications. Think about think about like a large air conditioning units for buildings. You go and you go to train and you get a large air conditioning unit that put up on the top of building with a crane. They have to build all kinds of adaptors to make sure that that will fit inside of of of the particulars of that building. You know, with on shape and tools like this, you'll be able to not only take the design of what the air conditioning system might be, but also the all the adapter plates, but also how they installed it. So it sort of as designed as manufactured as stalled. And all these things can be traced just like if you think about the transformation of customer service or customer contacts. In the early days, you used to have tools that were PC based tools called contact management solution, you know, kind of act or gold mine. And these were basically glorified Elektronik role in Texas. It had a customer names, and they had phone numbers and whatever else. And Salesforce and Siebel, these types of systems really broadened out the perspective of what a customer relationship waas. So it wasn't just the contact information it was, you know, How did they come to find out about you as a company? So all the pre sort of marketing and then kind of what happens after they become a customer and it really was a 3 60 view. I think that 3 60 view gets extended to not just to the customers, but also tools and the products they use. And then, of course, the performance information that could come back to the manufacturer. So, you know, as an engineer, one of the things you learn about with systems is the following. And if you remember, when the 501st came out CDs that used to talk about four times over sampling or eight times over sampling and it was really kind of, you know, the fidelity the system. And we know from systems theory that the best way to improve the performance of a system is to actually have more feedback. The more feedback you have, the better system could be. And so that's why you got 16 60 for example, etcetera. Same thing here. The more feedback we have of different parts of a company that a better performance. The company will be better customer relationships, better overall financial performance as well. So that's that's the view I have of how these systems all tied together. >>The great vision in your point about the data is, I think, right on. It used to be so fragmented in silos, and in order to take a system view, you've gotta have a system view of the data. Uh, for years we've optimized maybe on one little component of the system and that sometimes we lose sight of the overall outcome. And so what you just described, I think is, I think sets up. You know very well as we exit. Hopefully soon we exit this this covert era on John. I hope that you and I can sit down face to face at a PTC on shape event in the near term. Who's >>in the seaport in the >>seaport Would tell you that great facility toe have have an event for sure. It >>z wonderful >>there. So So, John McElhinney. Thanks so much for for participating in the program. It was really great to have you on. >>Right. Thanks, Dave. >>Okay. And I want to thank everyone for participating. Today. We have some great guest speakers. And remember, this is a live program, so give us a little bit of time. We're gonna flip this site over to on demand mode so you can share it with your colleagues and you, or you can come back and and watch the sessions that you heard today. Uh, this is Dave Volonte for the Cube and on shape PTC. Thank you so much for watching innovation for good. Be well, have a great holiday and we'll see you next time.

>>Hi, I'm Peter Burress. And welcome back to know the Cube conversation. This one from B M sees Helix Immersion Day at Santa Clara Marriott in Santa Clara, California. Once again, we've got a great set of topics for today Today, Right now we're gonna talk about is the everybody talks about the explosion in the amount of data, but nobody talks about the resulting or associated explosion in software. And that may in fact, be that an even bigger issue than the explosion and data. Because ultimately, we want to apply that data and get work done. That's gonna require that we rethink service's rethink service management, rethink operations and rethink operations management in the context of how all this new software is gonna create new work but also can perform new classes of work. Soto have that conversation. We've got a couple of great guests. New York. And here is the BMC president of Digital Service is in operations management division to BMC. Welcome back to the Cube. >>Thank you. >>And me Here shoot Close the CEO of Automation anywhere here. Welcome to the Cube. So Naoki, I want to start with you. A year ago, we started on this journey of how this new digital service is is going to evolve to do Maur types of work for people. How has be emcees? Helix Platform evolved in that time. >>So if you remember last time, it's almost a year. Back when we launched Helix, which was all around taking the service management capability that we had on Prem Minute available in cloud continue rise so customers can run and cut of their choice and provided experience through various channels bought as channel off that customer experience. This is what we had released last time. We call it the three C's for Helix, Everything in cloud containerized with cognitive capabilities so customers can transform that experience in this version. What we are extending helix is with the operation side. So although I Tom capabilities that we have in our platform are now a part off Felix, so we have one entering platform so that customers can discover every asset that they have on prominent loud monitor those assets detected anomalies service bought four lines of business and for i t. For immediate issues that happen, vulnerabilities that are there in the system and automatically optimized capacity and cost on holistic. This whole closed loop off operations and service coming together is what this next day off innovations that were launching BMC Helix >>Soma here New York He's talked about very successfully, and Felix has been a very successful platform for improving user experience. But up front, I noted that we're not just talking about human beings as users anymore. We're talking about software is users R p a robotic process. Automation is a central feature of some of these new trends. Tell us a little bit about how robotic process automation is driving an increased need for this kind of digital service in operations management capability? >>Sure think it a high level you have to think of. The new organization has augmented organization that are human and what's working side by side, each doing what they're best at. And so, in a specific example of a service organization, uh, the the BMC hell ex ist Licht Alexis Taking this is Think of this as a utility where the way you plug it into an electricity outlet and switch on the light and you get the electricity, you plug into the BMC helix, and behind it, you have augmented workforce of chat boards are pia bots, human beings each doing what they're best at and giving a far superior customer experience and like any other that is happening now. And that's the future off service industry. >>But when you point a human, so to speak metaphorically into that system, there's a certain amount of time there's a certain amount of training. There's a certain, and as a consequence, you can have a little bit more predictable scale. That doesn't mean that you don't end up with a lot of complexity, but our p A seems that the potential of our P A seems that you're going to increase the rate at which these users, in this case, digital users are going to enter into the system. You don't have a training regimen you can attach to them. They have to be tested. They have to be discovered. You have to be put in operation with reliability. How is that ultimately driving the need for some of these new capabilities? >>I think you if you think of this, if you think of this box as a digital workers, you almost have to go through the same process that you would go through human beings. You onboard them in terms of you, configure them. You trained them with cognitive capabilities and the and then in. The one difference is the monitor themselves. Without any bias they give, they can give you. They can give their own performance rating performance rating card. Um, but the beauty off this is when human and what's work together because there are some functions that the bots can do well. And then at some point they can hand off to the human beings and human beings. Do some of the more interesting work that is based on judgment. Call customer service. All of that, um, so that the combination is is the end goal for everybody >>and to add would be here said right, that customer experience, whether you're providing experience to employees, are consumers and customers. That is the ultimate goal. That's ultimate result of what you want to get and the speed at which you provided experiences, the accuracy of which you provide experience of the cause, that which you provided experience becomes a competitive sensation, which is where all this automation, this augmentation that they're doing with humans and bots is what enables us to do that right for or large enterprise customers May major service organizations trying to transform into that beautiful. >>But increasingly, it seems as though the, uh, the things that we have to do to orchestrate in ministry Maur users digital and human undertaking Maur complex tasks where each is best applied is really driving a lot of new data mentioned upfront, an enormous amount of software and you said new experiences. But those experiences have to be reliable, have to be secure. They have to be predictable. So that suggests this overwhelming impact of all of these capabilities. You talk about a digital tsunami? What are some of the key things? Do you think Enterprise is gonna have to do to start engaging that? >>Yeah, I'm incredibly college 40 nursery revolution. Whether we call our initial transformation, I think what we all are experiencing is the tsunami Texan ami, right, Tsunami of clouds, where you have corruption clouds, private clouds have a close marriage clouds, tsunami of devices, not just more valid visors, but also has everything alone, as is getting connected devices, tsunami of channels. I mean, as an end user, I wantto experience that in the channel of my preference lack as a journalism as a channel tsunami of bots, off conversation, bullets in our Peabody. So in this tsunami, I think what everyone is trying to figure out is, how do they manage this explosion? It's humanly impossible to do it all manually. You have toe augment it. But of course, intelligence, I'm all. But then, of course, boss, become a big part of that augmentation toe. Orchestrate all of them back to back cross. >>I would say that the this is no longer nice to have, because if you look it from over consumer's perspective, last 20 years of digital technologies off from my Amazons and Google's of the World, Netflix and others they have created this mind set off instant customer gratification, and we all been trained for it. So what was acceptable five years ago is no longer acceptable in our own lives, I e. And so this new standard off instant result instant outcome. Instant respond. Instant delivery V. Just expected. Right. Once you're end, consumer begins to do that. We as a business is no longer have a choice that's writing on the wall. And so what? This new platform Zehr doing like you'd be emcee. Hellickson automation anywhere is delivering their instant gratification. And when you think about it, more and more of the new customers that are millennials, they don't know any other way. So for them, this is the only experience they will relate. Oh, so again, this is not nice to see Oh, it is. But it is the only way only the world will operate, right? >>Well, what we're trying to do is take on new classes of customer experience, new operational opportunities to improve our profitability, innovate and find new value propositions. But you mentioned time arrival rate of transaction is no longer predictable. It's gonna be defined by the market, not by your employees. We could go on and on and on with that. What is taught us a little bit about automation anywhere and what automation anywhere is doing to try to ensure that as businesses go off to attend to the complexity creates new value at the same time can introduce simplicity where they could get scale and more automation. >>Sure, you earlier mentioned that with explosion of data came the explosion off applications And what? Let me focus on what problem or permission anywhere solves. If you look at large organizations, they have vast amount of applications, sometimes 408 100 few 1000 what we have seen. What we've been doing historically is using people as a human bridges between this applications. And we have a prettier that way for too long. And that's the world today. >>So humans are the interface >>humans at the bridges between applications and often called the salty air operations. That's the easiest way to describe it. So the what are two mission ever does is it offers this technology platform robotic process automation area in an Arctic split form that integrates all off it together into a seamless automation bought that can go across and with the eye it can make intelligent, intelligent choices. Um, and so now take that Combined with the BMC, Alex, and you have a seamless service platform that can deliver superior experience. >>So we've got now these swivel chair users now being software, which means that we could discover them more easily. We can monitor them more easily, and that feeds. He looks >>absolutely so you know, in our consumer wall, in a day to day life We are used to a certain experience of how we consume data or consume experiences with our TVs and all the channels that experience that we have an identity. Life is what people expect when they walk into the company, right walking to the Enterprise, which every IittIe organization is trying to figure out. How do they get to that level of maturity? So this is what the combination of what we're doing with Felix and automation anywhere brewing's that consumer great experiences into an enterprise >>world. Some here when we think about our p A. We're applying it in interesting and innovative ways, no question about it. But there are certain patterns of success. Give us some visibility into what you are seeing leads to success. And then what's the future of our P? A. How's that gonna involve over the next few years? >>Sure. Um, R P has been deployed across virtually every industry and virtually every department, so there are many ways to get started in All of them are right. But often we find is that you can either start in a central organization where in terror organization is doing everything centrally. It is a great way to get started. But eventually we learned that the Federated Way is the best way to end where hundreds of offices all over the world, if you are especially large organization, each business unit is doing it with I t providing governments and central security and policies and an actual bots running and being implemented all over the world eventually for a large gilt transformation. That is a common pattern we have seen among successful customers. >>And where do you think this is? Houses pattern going to evolve as enterprises gained more familiarity with it, innovating new and interesting ways and his automation anywhere, and others advance the state of the art. Where do you think it's gonna end up? >>The read is going is is I define it as an app store experience or a Google play experience. So if you think about how we operate over mobile devices today, if you want something on your device, you would look for a nap that does that. We're getting to a point where there is bought for everything in a digital worker for everything. So if you need certain job done, you first go to a what store? Uh that is an automation anywhere website. Look for about that. Does something higher or download that Bart. Get the work done and it comes pre built. Like many. There are works with BMC Felix on many of those, So s. So that is your 1st 1st way you will look, look for getting your work done in a new body economy. And if it if there's no but available, then you look for other options. It will transform how we work and how we think of >>work. In many respects, it's the gig economy with perfect contractor, and it's that leads to some very in string challenges. Ultimately, we start thinking about service Is so Ni aki based on what me here just talked about. Where does digital service is go as our P A joins other classes of users in creating those new experiences at new Prophet points and new value propositions, >>it becomes a competitive. How you provide that service can become a big competitive sensation for financial institutions. For telcos, which is a service industry, right, you're providing that service and, like two meters point, then the user hits that switch. They expect the light to come on If I'm an end user, that consumer warning a service from my telco provider, all from my, um, financial institution. I expect that service to be instantaneous at the highest accuracy accuracy at which super wide is gonna start driving competitor, official for financial institutions of financial institution Telco two Telco and that So I C companies, differentiating and really surviving are thriving in the long term. >>It's no longer becoming something that's nice to have its jacks or better in business, too. >>That's right. And the demo of the live demo that we saw today was really impressive because it sure that what would have taken a few days to happen now happens in three minutes. Right? It is, which is, which is almost the time it takes to call an uber. You know, when interpreters begin to do work at a pace that what you call an uber that's that's that's the future. Yes, it's here. >>Yes, so do I mean the demo that we do the entire enter and demo to request additional storage and being able to provisional remediating issues that we see predict cost and make it available to the end user develop whoever it is is asking for it in minutes. Alright, which used to take days and days. No, no, no, not to mention sometimes in pixels. >>It's typically done faster at scale, with greater reliability. Greater greater security, Certainly greater predictability, et cetera. All right. Here. Shukla, CEO of automation Anywhere. Yeah. Kenny, our president off the dental Service is and operations management division at BMC. Thanks both of you for being on the Cube. >>Thank you. >>Thank you. >>Once again, I'm Peter Burress and I want to thank you for participating in this cube conversation from Santa Clara Marriott at B M sees helix immersion days until next time.

(funky music) >> From our studios in the heart of Silicon Valley, Palo Alto, California, this is a Cube Conversation. >> Hi, welcome to another Wikibon digital community event, this one sponsored by BMC Software. Every organization faces the challenge of how to do service management and operations management better. The ideal is to start bringing them together, but traditionally, they've been undertaken by different groups, often utilizing different tools. And that's what we're going to talk about today in today's digital community event. What can we do to improve our digital business operations, competitiveness, and customer experience, by doing a better job of bringing together those core resources that handle service management and operations management activities. As with all digital community events, this one's going to feature some upfront conversations with a number of thought leaders in this crucial space, and then we're going to run a crowd chat, which will be your opportunity to share your insights, ask your questions, and ultimately, communicate with others like you in the community that focuses on this important issue. So stay through to the end and help us participate in that digital community event. Now, recently, I had an opportunity to attend BMC Helix's Immersion Day, and while there, theCUBE was able to conduct a number of different interviews. One of the best ones we had was a great conversation with Nayaki Nayyar, who is the president of service management and operations management at the BMC Helix division, and Mihir Shukla, who is the CEO of Automation Anywhere. Let's hear what they had to say about the potential of bringing service management and operations management together. >> So, Nayaki, I want to start with you. A year ago, we started on this journey of how this new digital services platform is going to evolve to do more types of work for people. How has BMC's Helix platform evolved in that time? >> So, if you remember last time, it was almost a year back when we launched Helix, which was all around taking the service management capability that we had on prem, made it available in Cloud, containerized, so customers can run in cloud of their choice, and provided experience through various channels, bought as a channel of that customer experience. This is what we had released last time, we call it the three C's for Helix, everything in cloud, containerized, with cognitive capabilities, so customers can transform their experience. In this version, what we are extending Helix is with the operations side, so all the ITOM capabilities that we have in our platform are now a part of Helix, so we have one end-to-end platform, so that customers can discover every asset that they have on prem and cloud, monitor those assets, detect any anomalies, service both for lines of business and for IT, remediate any issues that happen, vulnerabilities that are there in the system, and automatically optimize capacity and cost and holistically, this whole closed loop of operations and service coming together is what this next wave of innovations that we are launching with BMC Helix. >> So, Mihir, Nayaki's talked about, very successfully, and Helix has been a very successful platform for improving user experience, but up front I noted that we're not just talking about human beings as users anymore, we're now talking about software as users. RPA, robotic process automation, is a central feature of some of these new trends. Tell us a little bit about how robotic process automation is driving an increased need for this kind of digital service in operations management capability. >> Sure, think in a high level, you have to think of the new organization as augmented organization that are human and bots working side by side, each doing what they're best at. And so in a specific example of a service organization, where BMC Helix is taking this is, think of this as a utility, where the way you plug it into an electricity outlet and switch on the light and you get the electricity, you plug into the BMC Helix, and behind it you have augmented workflows of chart bots, RPA bots, human beings, each doing what they're best at, and giving a far superior customer experience, unlike any other. That is happening now, and that's the future of service industry. >> But when you plug a human, so to speak, metaphorically, into that system, there's a certain amount of time, there's a certain amount of training, and as a consequence you can have a little bit more predictable scale. That doesn't mean that you don't end up with a lot of complexity, but RPA seems, the potential of RPA seems that you're going to increase the rate at which these users, in this case, digital users, are going to enter into the system, you don't have a training regimen you can attach to them, they have to be tested, they have to be discovered, they have to be put in operation with reliability, how is that ultimately driving the need for some of these new capabilities? >> I think if you think of these bots as digital workers, you almost have to go through the same process that you would go through human beings. You onboard them, in terms of, you configure them, you train them with cognitive capabilities, and then the one difference is they monitor themselves, without any bias, they can give their own performance rating card. But the beauty of this is when human and bots work together, because there are some functions that the bots can do well and then at some point they can hand off to the human beings, and human beings do some of the more interesting work that is based on judgment call, customer service, all of that. So that the combination is the end goal for everybody. >> And to add to what Mihir said, right, that customer experience, whether you're providing an experience to employees or consumers or end customers, that is the ultimate goal, that's the ultimate result of what you want to get, and the speed at which you provide that experience is the accuracy at which you provide experience, the cost at which you provide that experience becomes a comparative differentiation, which is where all this automation, this augmentation that they're doing with humans and bots, is what enables us to do that, right? For all large enterprise customers, major service organizations trying to transform into that future goal. >> But increasingly it seems as though the things that we have to do, to orchestrate and administrate, more users, digital and human, undertaking more complex tasks where each is best applied, is really driving a lot of new data, as I mentioned upfront, an enormous amount of new software, and you said new experiences, but those experiences have to be reliable, have to be secure, they have to be predictable. So that suggests this overwhelming impact of all of these capabilities. You talk about a digital tsunami. What are some of the key things that you think enterprises are going to have to do to start engaging that? >> Yeah, and whether we call it revolution, whether we call it digital transformation, I think what we all are experiencing is a tsunami, tech tsunami, right, tsunami of clouds where you have professional clouds, private clouds, hybrid clouds, managed clouds. Tsunami of devices, not just the mobile devices, but also as everything is getting connected, IoT devices. Tsunami of channels, as an end user, I want to experience that in the channel of my preference, Slack as a channel, SM as a channel. A tsunami of bots, of conversation bots and RPA bots, so in this tsunami, I think what everyone is trying to figure out is, how do they manage this explosion? It's humanly impossible to do it all manually you have to augment it, with of course, intelligence AIML, but then of course bots become a big part of that augmentation to orchestrate all of that back to back process. >> I would say that this is no longer nice to have, because if you look at it from a more consumer's perspective, last 20 years of digital technologies from Amazons and Googles of the world, Netflix and others, they have created this mindset of instant customer gratification. And we all been trained for it, so what was acceptable five years ago is no longer acceptable in our own lives. And so this new standard of instant result, instant outcome, instant respond, instant delivery, we just expect it, right? Once your end consumer begins to do that, we as a business no longer have a choice, that's writing on the wall. And so what these new platforms are doing, like with BMC Helix and Automation Anywhere, is delivering that instant gratification, right? And when you think about it more and more of the new customers that are millennials, they don't know any other way. So for them, this is the only experience they will relate to, so again, this is not nice to have. It is the only way world will operate, right? >> We're going to turn back to the conversation that I had with Nayaki and Mihir shortly, but first, let's see what BMC's actually doing as they try to bring together service management and operations management, by watching a quick demo that they've prepared. (techno music) (music continues) >> Great demonstration of how these technologies are coming together in a real world sense. Now let's hear more of the conversation I had with Nayaki and Mihir about bringing together service management and operations management, but specifically focusing on how this class of technology is going to be extended, and made even more powerful for business as they think about not just IT, but other classes of automation. Let's hear what they had to say. >> So if you look at large organizations, they have vast amount of applications. Sometimes 400, 800, few thousand. And what we have been doing historically is using people as a human bridges between these applications, and we have operated that way for too long, and that's the world today. >> So humans are the interface, they're the system interfaces. >> Humans are the bridges between applications, and we often call it a swivel chair operations, that's an easiest way to describe it. So what Automation Anywhere does, is it offers this technology platform, robotic process automation, AI in an RTX platform, that integrates all of it together into a seamless automation bot that can go across, and with AI it can make intelligent choices. And so now we can take that, combined with the BMC Helix, and you have a seamless service platform that can deliver a superior experience. >> So we've got now the swivel chair users, now being software, which means that we can discover them more easily, we can monitor them more easily, and that feeds Helix. >> Absolutely, so you know in our consumer world, in our day to day life, we are used to a certain experience of how we consume data or consume experiences with our TVs and all the channels. That experience that we have in our day to day life is what people expect when they walk into the company, right, walk into the enterprise, which every IT organization is trying to figure out how do they get to that level of maturity. So this is what the combination of what we are doing with Helix and Automation Anywhere, brings that consumer grid experiences into an enterprise world. >> So Mihir, when we think about RPA, we're applying it in interesting and innovative ways, no question about it. But there are certain patterns of success, give us some visibility into what you are seeing leads to success, and then what's the future of RPA, how's that going to evolve over the next few years? >> Sure, so RPA has been deployed across virtually every industry and virtually every department. So there are many ways to get started and all of them are right. But often we find is that you can either start in a central organization wherein that organization is doing everything centrally. It is a great way to get started, but eventually we learn that the federated way's the best way to end. Where hundreds of offices all over the world, if you're especially a large organization, each business unit is doing it with IT providing governance and central security and policies, and actual bots running and being implemented all over the world. Eventually for a large-scale transformation, there is a common pattern we have seen among successful customers. >> And where do you think this pattern going to evolve, as enterprises gain more familiarity with it, innovate in new and interesting ways, and as Automation Anywhere and others advance the state of the art, where do you think it's going to end up? >> The rate it's going is, is I define it as an app store experience or a Google Play experience. So if you think about how we operate our mobile devices today, if you want something on your device, you will look for an app that does that. We are getting to a point where there is bot for everything, and a digital worker for everything, so if you need certain job done, you first go to a bot store, that is an Automation Anywhere website, look for a bot that does something, hire or download that bot, get the work done, and it comes prebuilt like many there are works with BMC Helix, and many others. So that is your first way you will look for getting your work done in a new bot economy, and if there's no bot available, then you look for other options. It will transform how we work and how we think of work. >> In many respects, it's the gig economy with perfect contractor, right? And it leads to some very interesting challenges, ultimately, when we start thinking about services. So Nayaki, based on what Mihir just talked about, where does digital services go as RPA joins other classes of users in creating those new experiences at new profit points and new value propositions? >> It becomes a compare of how you provide that service, can become a big competitive differentiation for financial institutions, for Telcos, which is a service industry, right, you provide that service, and like to Mihir's point, when the user hits that switch, they expect the light to come on, so if I'm an end user, the consumer, wanting a service from my Telco provider or from my financial institution, I expect that service to be instantaneous, and the highest accuracy, accuracy at which you provide is going to start driving competitive differentiation from financial institution to financial institution, Telco to Telco, and that's how I see companies differentiating and really surviving or thriving in the long term. >> Now let's hear from a really important partner, a CDO, someone who's thinking about how these technologies are going to be applied to the front lines of business change. Sanjay Srivastava is the CDO at Genpact, and he and I had a great conversation at BMC Immersion Days about what this means to digital business transformation. How will service management and operations management in combination accelerate and make more successful businesses' efforts to transform digitally. Let's hear what Sanjay had to say. >> So tell us a little bit about, what is a digital service outcome and why is it so important? >> Yeah, well I think the reality is that what technology is doing is it's disintermediating the ecosystem, so many of the industries are clients-operated, and they have to go back and reimagine their value proposition at the core of what they do with the use of new, innovative technologies, and it's that intersection of new capabilities, of new innovative business models that really use emerging technologies, but intersect them with their business models, with their business processes, and the requirements of their clients, and help them rethink, reimagine, and deliver their new value proposition. That's really what it's all about. >> So a digital service outcome would then be the things that the business must do and must do well, but ideally, with a different experience or with a different degree of flexibility and agility, or with a different cost profile, have I got that right? >> Correct. >> So when we think about that, what are some of the key elements of a digital service success? >> We like to think about three critical success factors in driving any digital transformation. The first one is the notion of experience, and what I mean by that is not user interface for a piece of software, but the journey of a customer, an employee, a provider, a partner, in engaging with you and your business model. When we think about journey mapping that scientifically, we think about design, thinking on the back of that, and we think about re-imagining what the new experience looks like. One of the largest things we've got in the industry is digital transformation on the back of cost take out of productivity or efficiency is insufficient drive and optimize the value that digital can bring. And using experience as the compass, as sort of the north star in that journey is a meaningful differentiator and driver of business benefit, so that's number one. I think the second area that's become increasingly apparent is the intersection of domain with digital. And the thinking there is that to materialize the benefit of digital in an enterprise, you have to intersect it with the specifics of that business, how users interact, what clients seek, how does business actually happen? We talk about artificial intelligence a lot, we do a lot of work in AI as an example, and the key thing about machine learning is goal orientation, and what is goal orientation? It's about understanding the specifics of the environments, you can actually orient the goal of the machine learning algorithm to deliver high accuracy results. And it's something that can often easily get overlooked, so indexing on the two halves of the whole, the yin and the yang, the piece around digital, and the innovative technologies, and being able to leverage and take advantage of them, but equally, be founded in domain, understand the environment, and use that knowledge to drive the right materialization of the end outcome. And that's the second critical success factor, I think, to get it right. I think the third one is the notion of how do you build a framework for innovation? You know, it's not the sort of thing where a large fortune company, Fortune 500 companies can necessarily experiment and it's a little bit of a go happy go lucky strategy, doesn't really work, you have to innovate at scale, you have to do it in a fundamental fashion, you have to do it as a critical success factor. And so one of the biggest things we focus on is how do you innovate at the edge? Innovation must be at the edge, this is where the rubber meets the road. But governance has to be at the core. >> Well let me build on that for a second, 'cause you said innovation's at the edge, so basically that means where the brand promise is being enacted for the customer, and that could be at an industrial automation setting or it could be in just making a recommendation, it could be any number of things, but it's where the value proposition is realized for the customer. >> Correct, that's exactly right, and that's where innovation must happen. So as a large corporation, you must be able, it's important to set up a framework that allows you to do innovation at the edge, otherwise it's not meaningful innovation if you, "Well, it's just a lot of busy work." And yet as you do that, and as you change your business model, as you bring new components to the equation, how do you drive governance, and it's increasingly becoming more important, you think about, we're going to be in a AI first world increasingly, more and more that's the reality of the world we're going in, and in that AI first world, I work here in Palo Alto, walk into my office, a couple of hundred people any given day. If tomorrow morning I walked in and 100 people didn't show up for work, I would know right away, because I can see them. Now fast forward to an environment where we have digital workers, we have automation bots, we have conversational AI Chatbots. And in that world, understanding which of my AI components are on, which ones are off, which ones showed up for work today, which ones fell sick, and really being able to understand that governance, and that's just the productivity piece of it. Then you think about data and security, AI changes complete dimensions on that. And you think about bias and explainability, it just become increasingly important, a notion of a digital ethics board, and thinking about ethics more pervasively. So I think that companies and clients we serve that do really well in digital transformation are those that key in on those three things, the notion of experience is the true compass for how you drive transformation. The ability to intermix domain and digital in a meaningfully intersecting fashion. And to be thoughtful, proactive, and get governance right up front in the journey to come. >> So let me again build on that a little bit, 'cause people are increasingly recognizing that we're not going to centralize with cloud, we're going to greater distribute. We're going to distribute data more, we're going to distribute function more, but you just added another dimension, that some of us have been thinking about for a long time, and that's this notion of distributing authorities so that an individual at the edge can make the decision based on the data and the resources that are available, with the appropriate set of authorities, and that has to be handled at a central, in a overall coherent governant way. So that leads to the next question. >> And just before you go there, I mean I think the best example of that, is we do that, most corporations do that really well in the financial scheme of things. Businesses at the edge make decisions on a day to day basis on pricing and relationships and so on and so forth, and yet there's a central other committee that looks through the financials and makes sure it meets the right requirements and has the right framework, and much in the same way, we're going to start seeing digital ethics committees that become part of these large corporations as they think about digitizing the business. >> Governance at the end of the day is how do you orchestrate multiple divergent claims against a common set of assets, and being able to do that is absolutely essential, and it leads to this notion of we've got these ideas of digital business, digital services and operations management. How are we going to weave them together utilizing some of these new technologies, new fabrics that are now possible to both achieve the outcomes we're talking about at scale and at speed? >> Yeah, well the technology capabilities are improving really well in that area, and so the good news is they're the set of tools that are now available that give you the ingredients, the components of the recipe that's required to make dinner, if you will. The work that needs to happen is actually how to orchestrate that, to figure out which components need to come in, and how do you pull together a vertical stack that has the right components to meet your needs today, and more importantly, to address the needs of the future, because this is changing like no other time in history. >> You want options with everything you do now, you want to make sure that you have a string of options for the future, and it's especially important here. >> That's right, that's exactly right. And the quick framework we've established there is sort of the three-legged stool of, how do you integrate quickly, how do you modularize your investments and then how do you govern them into one integrated whole, and those become really important. I'll give you examples, much of the work we do, we'll work with a consumer bank for instance, and they'll want to do a robotic process automation engagement, we'll run them for nine months, they'll get 1800 robots up and running. And the next question becomes, well now we have all this data that we didn't really have, because now we have an RPA running, how do I learn some machine learning insights from there, and so we then work with them to actually derive some insights and get these questions answered. And then the engagement changes to, well now that we have this pattern recognition then we understand more questions are going to be asked, how do I respond to those questions, A, automatically, and before they get asked, this notion of next best action. And so you think about that journey of a traditional client, the requirements change from robotics to machine learning to conversational AI to something else, and keeping that string of investments, that innovative sort of streak true, and yet being able to manage, govern, and protect the investments, that's the key role. >> We want to thank all the thought leaders that participated in preparing their thoughts for this digital community event, especially the folks at BMC Software. But now here's your opportunity to weigh in on how you see service management and operations management coming together in your business. How's it going to affect your IT organization, your IT organization's ability to serve your business, and your business overall? This is your opportunity to participate in a crowd chat where the community comes together and shares insights, asks each other questions, and engages with these thought leaders to try to get the answers that you need to move forward on the journey to bring together service management and operations management in your shop. Let's crowd chat!

>> Is and who we are today as as a country, as a universe. >> Narrator: Congratulations Reggie Jackson, (inspirational music) you are a CUBE alumni. (upbeat music) >> Announcer: Live from Las Vegas it's theCUBE covering Splunk.Conf19. Brought to you by Splunk. >> Okay, welcome back everyone it's theCUBE's live coverage here in Las Vegas for Splunk.Conf19. I am John Furrier host of theCUBE. It's the 10th Anniversary of Splunk's .Conf user conference. Our 7th year covering it. It's been quite a ride, what a wave. Splunk keeps getting stronger and better, adding more features, and has really become a powerhouse from a third party security standpoint. We got a C-SO in theCUBE on theCUBE today. Chief Information Security, John Frushour Deputy Chief (mumbles) New York-Presbyterian The Award Winner from the Data to Everywhere Award winner, welcome by theCube. >> Thank you, thank you. >> So first of all, what is the award that you won? I missed the keynotes, I was working on a story this morning. >> Frushour: Sure, sure. >> What's the award? >> Yeah, the Data Everything award is really celebrating using Splunk kind of outside its traditional use case, you know I'm a security professional. We use Splunk. We're a Splunk Enterprise Security customer. That's kind of our daily duty. That's our primary use case for Splunk, but you know, New York Presbyterian developed the system to track narcotic diversion. We call it our medication analytics platform and we're using Splunk to track opioid diversion, slash narcotic diversions, same term, across our enterprise. So, looking for improper prescription usage, over prescription, under prescription, prescribing for deceased patients, prescribing for patients that you've never seen before, superman problems like taking one pill out of the drawer every time for the last thirty times to build up a stash. You know, not resupplying a cabinet when you should have thirty pills and you only see fifteen. What happened there? Everything's data. It's data everything. And so we use this data to try to solve this problem. >> So that's (mumbles) that's great usage we'll find the drugs, I'm going to work hard for it. But that's just an insider threat kind of concept. >> Frushour: Absolutely. >> As a C-SO, you know, security's obviously paramount. What's changed the most? 'Cause look at, I mean, just looking at Splunk over the past seven years, log files, now you got cloud native tracing, all the KPI's, >> Frushour: Sure. >> You now have massive volumes of data coming in. You got core business operations with IOT things all instrumental. >> Sure, sure. >> As a security offer, that's a pretty big surface area. >> Yeah. >> How do you look at that? What's your philosophy on that? >> You know, a lot of what we do, and my boss, the C-SO (mumbles) we look at is endpoint protection and really driving down to that smaller element of what we complete and control. I mean, ten, fifteen years ago information security was all about perimeter control, so you've got firewalls, defense and depth models. I have a firewall, I have a proxy, I have an endpoint solution, I have an AV, I have some type of data redaction capability, data masking, data labeling capability, and I think we've seen.. I don't think security's changed. I hear a lot of people say, "Oh, well, information security's so much different nowadays." No, you know, I'm a military guy. I don't think anything's changed, I think the target changed. And I think the target moved from the perimeter to the endpoint. And so we're very focused on user behavior. We're very focused on endpoint agents and what people are doing on their individual machines that could cause a risk. We're entitling and providing privilege to end users today that twenty years ago we would've never granted. You know, there was a few people with the keys to the kingdom, and inside the castle keep. Nowadays everybody's got an admin account and everybody's got some level of privilege. And it's the endpoint, it's the individual that we're most focused on, making sure that they're safe and they can operate effectively in hospitals. >> Interviewer: What are some of the tactical things that have changed? Obviously, the endpoint obviously shifted, so some tactics have to change probably again. Operationally, you still got to solve the same problem: attacks, insider threats, etc. >> Frushour: Yeah. >> What are the tactics? What new tactics have emerged that are critical to you guys? >> Yeah, that's a tough question, I mean has really anything changed? Is the game really the game? Is the con really the same con? You look at, you know, titans of security and think about guys like Kevin Mitnick that pioneered, you know, social engineering and this sort of stuff, and really... It's really just convincing a human to do something that they shouldn't do, right? >> Interviewer: Yeah. >> I mean you can read all these books about phone freaking and going in and convincing the administrative assistant that you're just late for meeting and you need to get in through that special door to get in that special room, and bingo. Then you're in a Telco closet, and you know, you've got access. Nowadays, you don't have to walk into that same administrative assistant's desk and convince 'em that you're just late for the meeting. You can send a phishing email. So the tactics, I think, have changed to be more personal and more direct. The phishing emails, the spear phishing emails, I mean, we're a large healthcare institution. We get hit with those types of target attacks every day. They come via mobile device, They come via the phishing emails. Look at the Google Play store. Just, I think, in the last month has had two apps that have had some type of backdoor or malicious content in them that got through the app store and got onto people's phones. We had to pull that off people's phones, which wasn't pretty. >> Interviewer: Yeah. >> But I think it's the same game. It's the same kind to convince humans to do stuff that they're not supposed to do. But the delivery mechanism, the tactical delivery's changed. >> Interviewer: How is Splunk involved? Cause I've always been a big fan of Splunk. People who know me know that I've pretty much been a fan boy. The way they handle large amounts of data, log files, (mumbles) >> Frushour: Sure. >> and then expand out into other areas. People love to use Splunk to bring in their data, and to bring it into, I hate to use the word data leg but I mean, Just getting... >> Yeah >> the control of the data. How is data used now in your world? Because you got a lot of things going on. You got healthcare, IOT, people. >> Frushour: Sure, sure. >> I mean lives are on the line. >> Frushour: Lives are on the line, yeah. >> And there's things you got to be aware of and data's key. What is your approach? >> Well first I'm going to shamelessly plug a quote I heard from (mumbles) this week, who leads the security practice. She said that data is the oxygen of AI, and I just, I love that quote. I think that's just a fantastic line. Data's the oxygen of AI. I wish I'd come up with it myself, but now I owe her a royalty fee. I think you could probably extend that and say data is the lifeline of Splunk. So, if you think about a use case like our medication analytics platform, we're bringing in data sources from our time clock system, our multi-factor authentication system, our remote access desktop system. Logs from our electronic medical records system, Logs from the cabinets that hold the narcotics that every time you open the door, you know, a log then is created. So, we're bringing in kind of everything that you would need to see. Aside from doing something with actual video cameras and tracking people in some augmented reality matrix whatever, we've got all the data sources to really pin down all the data that we need to pin down, "Okay, Nurse Sally, you know, you opened that cabinet on that day on your shift after you authenticated and pulled out this much Oxy and distributed it to this patient." I mean, we have a full picture and chain of everything. >> Full supply chain of everything. >> We can see everything that happens and with every new data source that's out there, the beauty of Splunk is you just add it to Splunk. I mean, the Splunk handles structured and unstructured data. Splunk handles cis log fees and JSON fees, and there's, I mean there's just, it doesn't matter You can just add that stream to Splunk, enrich those events that were reported today. We have another solution which we call the privacy platform. Really built for our privacy team. And in that scenario, kind of the same data sets. We're looking at time cards, we're looking at authentication, we're looking at access and you visited this website via this proxy on this day, but the information from the EMR is very critical because we're watching for people that open patient records when they're not supposed to. We're the number five hospital in the country. We're the number one hospital in the state of New York. We have a large (mumbles) of very important people that are our patients and people want to see those records. And so the privacy platform is designed to get audit trails for looking at all that stuff and saying, "Hey, Nurse Sally, we just saw that you looked at patient Billy's record. That's not good. Let's investigate." We have about thirty use cases for privacy. >> Interviewer: So it's not in context of what she's doing, that's where the data come in? >> That's where the data come in, I mean, it's advanced. Nurse Sally opens up the EMR and looks at patient Billy's record, maybe patient Billy wasn't on the chart, or patient Billy is a VIP, or patient Billy is, for whatever reason, not supposed to be on that docket for that nurse, on that schedule for that nurse, we're going to get an alarm. The privacy team's going to go, "Oh, well, were they supposed to look at that record?" I'm just giving you, kind of, like two or three uses cases, but there's about thirty of them. >> Yeah, sure, I mean, celebrities whether it's Donald Trump who probably went there at some point. Everyone wants to get his taxes and records to just general patient care. >> Just general patient care. Yeah, exactly, and the privacy of our patients is paramount. I mean, especially in this digital age where, like we talked about earlier, everyone's going after making a human do something silly, right? We want to ensure that our humans, our nurses, our best in class patient care professionals are not doing something with your record that they're not supposed to. >> Interviewer: Well John, I want to hear your thoughts on this story I did a couple weeks ago called the Industrial IOT Apocalypse: Now or Later? And the provocative story was simply trying to raise awareness that malware and spear phishing is just tactics for that. Endpoint is critical, obviously. >> Sure. >> You pointed that out, everyone kind of knows that . >> Sure. >> But until someone dies, until there's a catastrophe where you can take over physical equipment, whether it's a self-driving bus, >> Frushour: Yeah. >> Or go into a hospital and not just do ransom ware, >> Frushour: Absolutely. >> Actually using industrial equipment to kill people. >> Sure. >> Interviewer: To cause a lot of harm. >> Right. >> This is an industrial, kind of the hacking kind of mindset. There's a lot of conversations going on, not enough mainstream conversations, but some of the top people are talking about this. This is kind of a concern. What's your view on this? Is it something that needs to be talked about more of? Is it just BS? Should it be... Is there any signal there that's worth talking about around protecting the physical things that are attached to them? >> Oh, absolutely, I mean this is a huge, huge area of interest for us. Medical device security at New York Presbyterian, we have anywhere from about eighty to ninety thousand endpoints across the enterprise. Every ICU room in our organization has about seven to ten connected devices in the ICU room. From infusion pumps to intubation machines to heart rate monitors and SPO2 monitors, all this stuff. >> Interviewer: All IP and connected. >> All connected, right. The policy or the medium in which they're connected changes. Some are ZP and Bluetooth and hard line and WiFi, and we've got all these different protocols that they use to connect. We buy biomedical devices at volume, right? And biomedical devices have a long path towards FDA certification, so a lot of the time they're designed years before they're fielded. And when they're fielded, they come out and the device manufacturer says, "Alright, we've got this new widget. It's going to, you know, save lives, it's a great widget. It uses this protocol called TLS 1.0." And as a security professional I'm sitting there going, "Really?" Like, I'm not buying that but that's kind of the only game, that's the only widget that I can buy because that's the only widget that does that particular function and, you know, it was made. So, this is a huge problem for us is endpoint device security, ensuring there's no vulnerabilities, ensuring we're not increasing our risk profile by adding these devices to our network and endangering our patients. So it's a huge area. >> And also compatible to what you guys are thinking. Like I could imagine, like, why would you want a multi-threaded processor on a light bulb? >> Frushour: Yeah. >> I mean, scope it down, turn it on, turn it off. >> Frushour: Scope it down for its intended purpose, yeah, I mean, FDA certification is all about if the device performs its intended function. But, so we've, you know, we really leaned forward, our CSO has really leaned forward with initiatives like the S bomb. He's working closely with the FDA to develop kind of a set of baseline standards. Ports and protocols, software and services. It uses these libraries, It talks to these servers in this country. And then we have this portfolio that a security professional would say, "Okay, I accept that risk. That's okay, I'll put that on my network moving on." But this is absolutely a huge area of concern for us, and as we get more connected we are very, very leaning forward on telehealth and delivering a great patient experience from a mobile device, a phone, a tablet. That type of delivery mechanism spawns all kinds of privacy concerns, and inter-operability concerns with protocol. >> What's protected. >> Exactly. >> That's good, I love to follow up with you on that. Something we can double down on. But while we're here this morning I want to get back to data. >> Frushour: Sure. >> Thank you, by the way, for sharing that insight. Something I think's really important, industrial IOT protection. Diverse data is really feeds a lot of great machine learning. You're only as good as your next blind spot, right? And when you're doing pattern recognition by using data. >> Frushour: Absolutely. >> So data is data, right? You know, telecraft, other data. Mixing data could actually be a good thing. >> Frushour: Sure, sure. >> Most professionals would agree to that. How do you look at diverse data? Because in healthcare there's two schools of thought. There's the old, HIPAA. "We don't share anything." That client privacy, you mentioned that, to full sharing to get the maximum out of the AI or machine learning. >> Sure. >> How are you guys looking at that data, diverse data, the sharing? Cause in security sharing's good too, right? >> Sure, sure, sure. >> What's your thoughts on sharing data? >> I mean sharing data across our institutions, which we have great relationships with, in New York is very fluid at New York Presbyterian. We're a large healthcare conglomerate with a lot of disparate hospitals that came as a result of partnership and acquisition. They don't all use the same electronic health record system. I think right now we have seven in play and we're converging down to one. But that's a lot of data sharing that we have to focus on between seven different HR's. A patient could move from one institution to the next for a specialty procedure, and you got to make sure that their data goes with them. >> Yeah. >> So I think we're pretty, we're pretty decent at sharing the data when it needs to be shared. It's the other part of your question about artificial intelligence, really I go back to like dedication analytics. A large part of the medication analytics platform that we designed does a lot of anomaly detections, anomaly detection on diversion. So if we see that, let's say you're, you know, a physician and you do knee surgeries. I'm just making this up. I am not a clinician, so we're going to hear a lot of stupidity here, but bare with me. So you do knee surgeries, and you do knee surgeries once a day, every day, Monday through Friday, right? And after that knee surgery, which you do every day in cyclical form, you prescribe two thousand milligrams of Vicodin. That's your standard. And doctors, you know, they're humans. Humans are built on patterns. That's your pattern. Two thousand milligrams. That's worked for you; that's what you prescribe. But all of the sudden on Saturday, a day that you've never done a knee surgery in your life for the last twenty years, you all of a sudden perform a very invasive knee surgery procedure that apparently had a lot of complications because the duration of the procedure was way outside the bounds of all the other procedures. And if you're kind of a math geek right now you're probably thinking, "I see where he's going with this." >> Interviewer: Yeah. >> Because you just become an anomaly. And then maybe you prescribe ten thousand milligrams of Vicodin on that day. A procedure outside of your schedule with a prescription history that we've never seen before, that's the beauty of funneling this data into Splunk's ML Toolkit. And then visualizing that. I love the 3D visualization, right? Because anybody can see like, "Okay, all this stuff, the school of phish here is safe, but these I've got to focus on." >> Interviewer: Yeah. >> Right? And so we put that into the ML Toolkit and then we can see, "Okay, Dr. X.." We have ten thousand, a little over ten thousand physicians across New York Presbyterian. Doctor X right over here, that does not look like a normal prescriptive scenario as the rest of their baseline. And we can tweak this and we can change precision and we can change accuracy. We can move all this stuff around and say, "Well, let's just look on medical record number, Let's just focus on procedure type, Let's focus on campus location. What did they prescribe from a different campus?" That's anomalous. So that is huge for us, using the ML Toolkit to look at those anomalies and then drive the privacy team, the risk teams, the pharmacy analytics teams to say, "Oh, I need to go investigate." >> So, that's a lot of heavy lifting for ya? Let you guys look at data that you need to look at. >> Absolutely. >> Give ya a (mumbles). Final question, Splunk, in general, you're happy with these guys? Obviously, they do a big part of your data. What should people know about Splunk 2019, this year? And are you happy with them? >> Oh, I mean Splunk has been a great partner to New York Presbyterian. We've done so much incredible development work with them, and really, what I like to talk about is Splunk for healthcare. You know, we've created, we saw some really important problems in our space, in this article. But, we're looking, we're leaning really far forward into things like risk based analysis, peri-op services. We've got a microbial stewardship program, that we're looking at developing into Splunk, so we can watch that. That's a huge, I wouldn't say as big of a crisis as the opioid epidemic, but an equally important crisis to medical professionals across this country. And, these are all solvable problems, this is just data. Right? These are just events that happen in different systems. If we can get that into Splunk, we can cease the archaic practice of looking at spreadsheets, and look up tables and people spending days to find one thing to investigate. Splunk's been a great partner to us. The tool it has been fantastic in helping us in our journey to provide best in-class patient care. >> Well, congratulations, John Frushour, Deputy Chief Information Security Officer, New York Presbyterian. Thanks for that insight. >> You're welcome. >> Great (mumbles) healthcare and your challenge and your opportunity. >> Congratulations for the award winner Data to Everything award winner, got to get that slogan. Get used to that, it's two everything. Getting things done, he's a doer. I'm John Furrier, here on theCube doing the Cube action all day for three days. We're on day two, we'll be back with more coverage, after this short break. (upbeat music)

>> Announcer: From Burlingame, California, it's theCUBE, covering Sumo Logic Illuminate 2019. Brought to you by Sumo Logic. >> Hey, welcome back, everybody. Jeff Frick here, with theCUBE. We're at Sumo Logic Illuminate at the Hyatt Regency San Francisco Airport. About 800 people, 900 people, packed house in the keynote earlier this afternoon, really interesting space. And we're excited to have our next guest, kind of on the cutting edge of the IoT space on the consumer side. And he's Robert Parker, the CTO of Samsung SmartThings. Robert, great to see you. >> Hi, great to be here. >> Absolutely, so, before we get into the depth of the conversation, a little bit of a background on SmartThings. I was doing some research, getting ready for this, and the fact that it started as a Kickstarter a long time ago, not that long ago, and now is part of Samsung, a global electronics giant, what a fun adventure. >> Absolutely, I think it's been one of these things where it's great to be something where it's community-driven to begin with. So, Kickstarter was a big part of our launch, and we were one of the biggest Kickstarter launches at the time, really powered by our community around the website and early users. We got a lot of interest in IoT, and then moved on to the next stage of the vision, which is sort of encompassing all devices. And so, that meant we have more than 2,000 different Samsung devices on the platform now, which really allowed devices to talk to each other in ways that are really exciting, and that breadth has been a really great thing to be part of. >> Right, it's really funny, we went to the Samsung Developer Conference a couple years ago, and it was funny to see the living room guys fighting with the kitchen guys as to, what was the center? Is it the TV, or is it the refrigerator? Or is the the washing machine, for that bit? And Samsung's really got a foot in all those places. >> Absolutely, this is one of the things that the SmartThing platform has really enabled Samsung to transition across, as then it's no longer a conversation with the washing machine person or the dryer. All the devices are part of the SmartThings cloud. The SmartThings cloud is a one way that you can talk to Samsung devices, and it's an open ecosystem. So, it's not just Samsung devices, we're equally comfortable with manufacturers, any manufacturer, bringing those devices because home is a multi-vendor environment. You are not going to have all of your home from any one vendor. >> Right. >> And that's been one of the exciting parts of the vision, is that's been part, the open ecosystem has been something that's been part of the SmartThings story forever. To really immortalize that in a platform for Samsung has been a great transition. >> Right, so we're here at Sumo Logic Illuminate, and in preparing for this, I saw an interview with you, you made a really interesting comment. You said that we are a pervasive user of Sumo Logic, and then you said 90% of the team are using Sumo Logic. It's fascinating to me, because I think a lot of companies are chasing innovation, and I think one of the ways to get innovation is you enable more people to have more access to more data, and the tools to actually operate that data so that they can do their jobs and find cool ways to make improvements that aren't necessarily coming from the top down. It sounds like you guys have addressed that philosophy wholeheartedly. >> So, we absolutely have addressed it wholeheartedly, I think there was a lot of luck involved, and I wanted to sort of describe it, is that one of the things that worked well for us is people were excited to use Sumo more and more. They were more excited to see what they could do with the tool, what insights they could get, and so, you'd see your neighbor looking at it, and they'd look at a dashboard and they'd say, hey, can I do a little bit of that? And so much so, in the last year, we've seen a lot of unplanned value come out. So, a third of the value we got out of the Sumo in the past year was unplanned. It was things people didn't, processes they didn't know they would improve that really just came from this groundswell, from what I would call the community. And I think that's where you get, that unlocks a lot of the potential, because you really can't do things from sort of the planned high level. You really need people actively engaged and doing stuff you wouldn't expect. >> That's great. So, I want to talk a little bit about security. Security's a big topic here, it's a topic everywhere we go. And now, with connected devices, and connected keys, and connected doorbells, it seems like, oh, here we go again, and there's this constant talk that security's got to be baked in throughout the entire process. How are you guys dealing with security? It's obviously got to be right at the top of mind in terms of priorities while you're still connecting the sprinklers-- >> No, absolutely. >> And the thermostat and everything else. >> Security and privacy are both critical. I link in privacy even though you didn't ask about it, because, as you think about devices like cameras and things like this, privacy is top of mind. Also, in terms of regulation like GDPR. And so, because of that, we're really looking at both cases, the challenge for both security and privacy is, it really cuts through your whole organization and every process, and by the way, every process that every partner at the organization has, because we can have something that could be exploited from an attack through a customer service representative, that could be a person in the customer service organization, it could be how someone social engineered that. And so, what we've really needed is this kind of continuous intelligence that can span all of these processes, because in something like security, you're as good as your weakest process. And that doesn't mean that we don't focus on all the things that you talked about. We're industry-leading from a device perspective to have hardware baked-in keys and do things in the manufacturing process that lead to something that could be as secure as anything, but that's really the secret of using a lot of the continuous intelligence tools like Sumo, is that all of these could-bes aren't enough. You have to bring it together by having the intelligence that spans those processes to make sure that all of them are elevated, because at the end of the day, a security attack is going to attack your weakest thing, not your strongest thing. >> Right, so one of the other topics here that's talked about is this exponential growth of data, and you guys are part of the problem, 'cause now we got sensors, and light switches, and all these other things that are kickin' off data that, before, we weren't monitoring. And so, from an execution point of view at the company, when you've got so much data that you need to turn into information, and then actionable insight, you said Sumo's got some unique characteristics that allow you guys to get more leverage out of that platform. I wonder if you could dig into that a little bit more. >> And I'd like to reframe the data discussion a little bit, because a lot of people look at it as a problem, and I want to really talk about the opportunity side. So, part of that goes to our story, where we started off at Kickstarter with a few thousand users. We have over 50 million active users now. >> Jeff: 50 million? >> 50 million, our Android application in the Google Play Store had been been downloaded around 200 million times, so it gives you some idea of that size and scope. So, the data is an opportunity. There's an opportunity to build a customer base, to excite people, and to manage the processes that do that. And what's great now is that the availability of this data means that you can do it in more ways than you ever could before. The problem is, you need a tool that brings this together to be able to do that, and doing that well is difficult. Difficult both on the teams, and difficult because of the size, scope, and complexity of the systems because of the data that you mentioned. But the reason you want to do it is so that you can cross the chasm in terms of this opportunity. And more and more companies have this opportunity out in front of them. One of the things that's been really exciting about the cloud is it sort of democratized the entry point, but that wasn't good enough. Just because you could get in the game with three people, it's like making a, you can make a application in a mobile application store, either on Google's or on Apple's, really easily, that gets you in there. What you really need to do is manage the intelligence that goes from that, and for us, it's been really exciting to be able to take our decisions and make them data-driven. And we can do that by this explosion of data because it is there. >> Right, and the data is good, and I think we see data as an asset, it hasn't really hit balance sheets officially yet, but I think you see it in the valuations of companies like Google, and Facebook, and Amazon, right, who obviously have these crazy, giant multiples of their revenue, one, because they're growing, but two, because they have so much data. So, the market's kind of valuing that data without explicitly calling it out as a line item on the balance sheet. That said, not all data has the same value, not all data needs to be treated the same. And so, it really opens up an opportunity to say how do you tier it? So, you don't want to get, y'know, spend a ton of money on a piece of data and a big, fat stream that somebody leaves open on Amazon accidentally, suddenly have a big bill, and that maybe wasn't the most valuable, so. >> I'd actually double down on what you said, because for a typical company, one of the things that's also been true of the mega-scale companies that you pointed out with, is there's a lot of uniformity in their data. So, a company like Amazon, they have customer orders and they've got orders at this massive scale. A typical company doesn't look like that. Their data spread is more fragmented, smaller scale, and so, because of that, they want to make different decisions. And this is the same thing that has already happened in the storage area. People are really comfortable with storage that they're going to have in either disaster recovery, or long-term storage, and they want a very low-cost footprint around that. They've got their hot data, and they're much more willing to have that data managed differently, and at a higher cost rate, because it's much more valuable. We're looking for tools that span that, not just in storage, but in the ingestion, and the management, and the querying of that data, because, like you said, for most businesses, a lot of data is infrequently looked at, or looked at in response to a situation, so I'll never know which 10% of the data will be looked at. It'll be based on, oh, I got audited, or some other business event that happens. And so, this is one of the keys things that businesses are now struggling with. One of them is that, hey, they want to adopt these practices to become modern, or more modernized, but the second one is, to really be able to tier the data because they couldn't treat all the data as if it's hot data, just like they already figured that out for storage. >> Right, it's pretty interesting, 'cause it's been going on for storage forever, and we really saw it, I think, with the rise of Flash, which was super-high quality but super-expensive in the early days, that's coming down. And then, at the other end, we have the Glacier Storage and the cold storage just put it away. I want to get your last thoughts, last answer, Robert. As you look forward, I can't believe we're already in middle of September of 2019, it's fascinating to me that time flies so fast, but as you look forward, what are some of your priorities over the next year or so? How are you guys moving the ball down the field? >> One of the things that we're looking at was the data problem that you were talking about, if, really looking at our infrequent data, and being able to manage that effectively, both from the types of insights that we can get from that, so a lot of this starts to be better usage of machine learning, pattern recognition, AI, and so that we can, the ideal situation for us in that type of data is it got touched once, it got looked at once, and then we could understand how to action it later, that deferred action. And then, how to trigger that deferred action, as well as the tiering that we sort of talked about, that all data's not-- >> Created equal. >> Created equally, and so both those things are happening. Just to put some numbers on this, as why, is that we have 150 terabytes or so of data that is somewhat interesting to our business generated on a daily basis. >> 150 terabytes a day? >> 150 terabytes a day. >> That's interesting, that's the good stuff. >> And out of that, I'd say 10 terabytes is really actionable. And so, that gives you an idea. The other part is how that's growing, where a year ago, we would've been at maybe 60 terabytes of what I would've called this interesting data, and maybe five terabytes of immediately actionable. And so, this is following that, where that's exponentially growing, and it's a big number, so that's what we really think about. >> So, you scared? Because those curves, those curves get steep. >> It's the same way, we look at it as a huge opportunity, so what will happen is, either people will create value out of that for customers, in which case, actually, the opportunity, because it's at such a scale, it will be great for everyone, or, number two, it just becomes noise. And so, it isn't really something to get scared of, because worst case is, it became noise to you. We really want to be one of those people who are getting value out of it, and see the business growth and the consumer value growth out of that. I'm pretty optimistic that we'll be able to do it, because we really, if I look back three, four, years, we've just been able to figure out a way, and I think it will continue to do that. >> All right, well, Robert, thanks for taking a few minutes of your time and sharing the story, it's a great story. >> Thank you, appreciate being here. >> All right, he's Robert, I'm Jeff, you're watching theCUBE. We're at Sumo Logic Illuminate 2019. Thanks for watching, we'll see you next time.

>> from Burlingame, California It's the Cube covering Suma logic Illuminate 2019. Brought to you by Sumer Logic >> Hey, welcome back already, Jeffrey Here with the Cube Worth Suma >> logic illuminated the higher Regency San Francisco airport. About 800 people, 900 people packed house in the keynote earlier this afternoon. Really interesting space, and we're excited to have our next guest >> kind of on the cutting edge >> of the I o T space on the consumer side. And he's Robert Parker, the CTO of Sand Samsung. Smart things, Robert. Great to see you. >> Great to be here. >> Absolutely so before we get into >> the kind of the depth of the conversation, a little bit of a background on smart things. I was doing some research getting ready for this and the fact that it started as a kickstarter a long time ago, not that long ago, and now is part of Samsung, a global electronics giants. What a fun adventure. >> Absolutely. I think it's been one of these things where it's great to be something where it's community driven to begin with, so kick start. It was a big part of our launch, and we were one of the biggest kicks are launches at the time. Uh, really powered by our community around the website and early users. We got a lot of interest in I O. T. And then moved on to the next stage of the vision, which is sort of encompassing all devices. And so that meant we have more than 2000 different Samsung devices on the platform now, which really allow devices to talk to each other in ways that are really exciting. And that breath has been really great thing to be part of >> right. It's really funny. We went to the Samsung Developer conference a couple of years ago. It was funny to see the the living room guys fighting with the kitchen guys, you know, What was >> the centers that the TV or is it >> the fridge aerator? Or is it the washing machine for that bit? And Samsung's got really got a foot in all those places? >> Absolutely. This is one of the things that the smart thing platform is really enabled Samsung to transition across is then it's no longer a conversation with the washing machine person or the dryer. All the devices are part of the smart things. Cloud. Martin Claude is a one way that you could talk to Samsung Devices, and it's an open ecosystem. So it's not just Samsung. Devices were equally comfortable with manufacturers. Any manufacturer bringing those devices because home is a multi vendor environment you are not. We're gonna have all of your home from anyone, vendor, right? And that's been one of the exciting parts of visions that's been part The open ecosystem is something that's been part of smart things. Story forever to really immortalize that in a platform for Samsung has been great transit, >> right? So we're here. It's Uma Logic, eliminate and preparing for this. I saw an interview with you. You made a really interesting comment. >> You said that we are a pervasive >> user of suma logic, and he said 90% of the team are using similar logic. It's fascinating to me because I think a lot of companies air chasing innovation. I think one of the ways to get innovation is you enable more people to have more access to more data and the tools to actually operate that data so that they can do their jobs and find cool ways to make improvements that aren't necessarily coming from the top down. It sounds like you guys have addressed that philosophy wholeheartedly, >> so we absolutely have addressed it wholeheartedly. I think there's a lot of luck involved, and I want to sort of describe it Is that one of the things that worked well for us is people were excited to use sumo more and more. They're more excited to see what they could do with the tool, what insights they could get. And so you see your neighbor looking at it and they look a dashboard and they say, Can I do a little bit of that? And so much So you know, in the last year we've seen ah lot of unplanned value come out. So 1/3 of the value we gotta assume of, um, um in the past year was unplanned. These things people didn't process, they didn't know they would improve. That really just came from this groundswell from what I would call the community. And I think that's where you get that. That unlocks a lot of the potential because you really can't do things from sort of the planned high level. You really need. People actively engaged right and doing stuff you wouldn't expect. >> That's great. So I >> want to talk about >> a little bit about security. Security is a big topic here. It's topic everywhere we go on and now, with connected devices and connected keys and connect doorbells, it seems like, Oh, here we go again And there's this constant talk that security's got to be baked in throughout the entire process. How are you guys dealing with security? Obviously got to be right at the top of mind in terms of priorities. While you're still connecting the sprinklers in the thermostat and everything else. Security >> and privacy are both critical link in privacy, even though you didn't ask about it. Because as you think about devices like cameras and things like this, privacy is top of mind. Also, in terms of regulation like GDP, are so because of that, we're really looking at both cases that the challenge for both security and privacy is it really cuts through your whole organization and every process, and by the way, every process that every partner, if the organization has because we can have something that could be exploited from sort of a an attack through a customer service representative. That could be a person in the customer service organization. It could be how some of social engineered that. And so what we've really needed is this kind of continuous intelligence that can span all of these processes because in something I security, you're as good as your weakest process. And that doesn't mean that we don't focus on all things that you talked about. Were industry leading from device perspective tohave hardware baked in keys and, you know, do things the manufacturing process that lead to something that could be as secure as anything. But that's really that the secret of using a lot of the continuous intelligence tools like sumo is that all of these could bees aren't enough. You have to bring it together by having the intelligence that spans those processes to make sure that all of them are elevated. Because at the end of the day, a security attack is gonna attack your weakest thing, not your strongest right. >> So one of the other >> topics here that talked about is this exponential growth of data, and you guys were part of the problem because now we got sensors and light switches and all these other things that are kicking off data that before we weren't monitoring. And so from from an execution point of view at the company, when you've got so much data that you need to turn into information and then actionable insight, you said Sumo's got some unique characteristics that allow you guys to get more leverage of that platform. I wonder if you could dig into that little bit more >> and I'd like to reframe the data discussion a little bit. A lot of people look at it. It's a problem. I want to really talk about the opportunity side. So part of that goes to our story where we started off at KICKSTARTER with a few 1000 users, we have over 50 million active users now. >> 50 million >> 50 million. Our Android application, the Google Play store, had been downloaded around 200 million times, so it gives you some idea of that size and scope. So the data is an opportunity. There's an opportunity to build a customer base, too, excite people and to manage the processes that do that. And you know what's great now is that the availability of this data means that you can do it in more ways than you ever could before. The problem is, you need a tool that brings us together. To be able to do that in doing that well is difficult, difficult both on the teams and difficult because the size, scope and complexity of the systems because of the data that you mentioned. But the >> reason you want to >> do it is so that you can cross the chasm in terms of this opportunity, and more and more companies are enough. You have this opportunity on the front of them. One of the things that's been really exciting, but the cloud is a sort of democratized the entry point. But that wasn't good enough just because you could get in the game with three people. It's like making a you can make us application in Mobile Applications store, either on Google's on Apple's really easily that gets you in there. What you really need to do is manage the intelligence that goes from that, and for us, it's been really exciting to be able to take our decisions and make them data driven, and we can do that by this explosion of data because it is their >> right in the date is good. And I think we see, you know, kind of date of it as an asset. It hasn't really hit balance sheets officially yet, but I think you see it in the valuations of of companies like Google and Facebook and Amazon, right, who obviously have these crazy giant multiples of the revenue one because they're growing but too because they have so much data. So the markets kind of valuing that data without explicitly calling it out as a line on the balance sheet. That said, not all data has the same value, not all day. Not all data needs to be treated the same and so really opens up an opportunity. How do you tear it so you don't want to get? You know, it's been a ton of money on a piece of data and a big fat stream that somebody leaves open and accidentally suddenly have a big building that maybe wasn't the most valuable. So >> it actually double down on what you said because for a typical company, one of things has also been true. Of the mega scale companies that you pointed out with is there's a lot of uniformity in their data coming the cost of the Amazon. They have customer orders, and they've got orders at this massive scale. A typical company doesn't look like that. They have their data spread is more fragmented, smaller scale on so >> because they want to make different decisions. And this is the >> same thing that has already happened in the storage area. People are really comfortable with storage that they're gonna have in either just disaster recovery or long term storage. And they want a very low cost footprint around that they've got their hot data and they're much more willing, tohave that data managed differently and at a higher cost rate because it's it's much more valuable. We're looking for tools that span that not just in storage, but in the ingestion in the management in the querying of that data. Because, like you said for most businesses, a lot of data's infrequently looked at or looked at in response to a situation, so I'll never know which 10% of the data will be looked at. It will be based on Oh, I got audited or, you know, some other business event that happened on, so this is one of the key things that business is struggling with. One of them is that they they want to adopt these practices to become modern or boring, modernized. But the 2nd 1 is to really be able to tear the data because they couldn't treat all the data's if it's hot data, just like they already figured that out for storage, >> right? It's pretty interesting. It's been going on for storage forever. We really saw it, I think, with the rise of Flash, which was super high quality but super expensive in the early days that's coming down and then at the other. And we have the end of the glacier storage in the cold, cold, cold store. Just put it away by what your last thought's that last. Answer, Robert. As you look forward, I can't believe you're already in middle of September of 2019. It's fascinating to me that time flies so fast. But as >> you look >> forward, what are some of your priorities over the next year or so? How are you guys kind of moving the ball down the field? >> So we're one of the things that we're looking at? Was the data problem that you were talking about, if really looking at are infrequent data and be able to manage that effectively both from the types of insights that we can get from that. So a lot of this starts to be better usage of machine learning pattern recognition a eye on so that we can, you know, the ideal situation for us and not type of data is it got touched once it got looked at once, and then we could understand how to action it later that deferred action. And then how do you know trigger that deferred action as well as the tearing that we sort of talked about that all day? It is not created, equal, created equally, and so both those things are happening just to put some numbers on this. And why is that? We have 150 terabytes or so of data that is somewhat interesting to our business generated on a daily basis. 150. Terrible, terrible. That's interesting. And then on that's out of that, I'd say 10 terabytes is kind of really actionable. It's that gives you an idea. The other part is how that's growing. Where a year ago, we would have been at maybe 60 terabytes of what I would have called this interesting data and maybe five terabytes of, of of, you know, immediately actionable. And And so that's where you know this is following that where that's exponentially growing and it's a big number. So that's what we really think about. >> So you scared those curves. Curves get state, we look. It >> is a huge opportunity. What will happen is either people will create value out of that for customers, in which case, actually the opportunity, because is that such a scale? It will be great for everyone or number two, you know, it just becomes noise, right? And so it isn't really something that scared of, because worst case is it became noise to you. We really want to be one of those people were getting value out of it and see sort of the business growth and the consumer value growth. Out of that, I I'm pretty optimistic that we'll be able to do it because we really if I look back 34 years, we've just been able to figure out a way, and I think it will continue to do that >> All right. Well, Robert, thanks for taking a few minutes of your time and ensuring the story. It's a great story. Thank you. Appreciate being here. All right. >> He's Robert. I'm Jeff. You're watching the Q word. Suma logic illuminate 2019. >> Thanks for watching. We'll see you next time.

live from Stanford University it's the cube covering global women and data science conference brought to you by Silicon angle media good morning and welcome to the cube I'm Lisa Martin and we are live at the global fourth annual women in data science conference at the Arriaga Alumni Center at Stanford I'm very pleased to be joined by one of the Wits ambassadors this year Regina cut of our math data science senior manager Accenture at Google and as I mentioned you are an ambassador for wits in Bangla Road the event is Saturday so Janelle welcome to the cube thank you pleasure it is - this is the fourth annual women in data science conference this year over 150 regional events of which you are hosting Bengaluru on Saturday March 9th 50-plus countries they're expecting a hundred thousand people to engage tell us a little bit about how you got to be involved in wins yeah so I care about data science but also what accurate representation of women in gender minority in the space and I think it's global initiative is doing amazing job in creating a significant impact globally and that kind of excited me to get involved with its initiative so you have which I can't believe you're an SME with ten plus years experience and data analytics focusing on marketing and customer analytics you've had senior analytics leadership positions at Accenture Hewlett Packard now Google tell me a little bit about before we get into some of the things that you're doing specifically the data--the on your experience as a female in technology the last ten plus years it's been exciting I started my career as an engineer I wanted to be a doctor fortunately unfortunately it couldn't happen and I ended up being an engineer and it has been an exciting ride since then I felt that had a passion for doing personal management and I posted management and specialization of operational research and project management and I started my career as a data scientist worked my way up through different leadership positions and currently leading a portfolio for Accenture at Google yeah in the read of science domain yeah it's exciting absolutely so one of the things that is happening this year wins 2019 the second annual data thon that's right really looking at predictive analytics challenge for social impact tell us a little bit about why Woods is doing this data thon and what you're doing in not respectively in Bengaluru okay so well you see data science in itself is a highly interdisciplinary domain and it requires people from different disciplines to come together look at the problem from different perspectives to be able to come up with the most amicable and optimal solution at any given point of time and Gareth on is one such avenue that fosters this collaboration and data thon is also an interesting Avenue because it helps young data science enthusiasts whom the require design skill sets and also helps the data science practitioners enhance and sustain their skill sets and that's the reason which Bangalore was keen on supporting what's global data thon initiative so this skill set so I'd like to kind of dig into that a bit because we're very familiar with those required data analytics skill sets from a subject matter expertise perspective but there's other skill sets that we talk about more and more with respect to data science and analytics and that's empathy it's communication negotiation can you talk to us a little bit about how some of those other skills help these data thon participants not just in the actual event but to further their careers absolutely so really into the real world so there are a lot of these challenges wherein you would require a domain expert you require someone who has a coding experience someone who has experience to handle multiple data sites programmatically and also you need someone who has a background of statistics and mathematics so you would need different people to come together I look at the problem and then be able to solve the challenges right so collaboration is extremely pivotal it's extremely important for us to put ourselves in other shoes and see a look at the problem and look at the problem from different perspective and collaboration or the key to be able to be successful in data science domain as such okay so let's get into the specifics about this year's data sets and the teams that were involved in the data thon all right so this year's marathon was focused on using satellite imagery to analyze the scenario of deforestation cost of oil palm plantations so what we did at which Bangalore is we conducted a community workshop because our research indicated that men dominated the Kegel leaderboard not just in Bangla but for India in general despite that region having amazing female leader scientists who are innovators in their space with multiple patents publications and innovations to the credit so we asked few questions to certain female data scientists to understand what could be the potential reason for their lower participation and the Kegel as a platform and their responses led us to these three reasons firstly they may not have the awareness about Kegel as a platform may be a little bit more about that platform so reviewers can understand that right so Kegel is a platform where in a lot of these data sets have been posted if anybody is interested to hold the required a design skill says they can definitely try explore build some codes and submit those schools and the teams that are submitting the codes which are very effective having greater accuracy he would get scored and the jiggle-ator build and you know that which is the most effective solution that can be implemented in the real world so we connected this data Sun workshop and one of the challenges that most of the female leader scientists face is having an environment to network collaborate and come up with a team to be able to attempt a specific data on challenge that is in hand so we connected data from workshop to help participants overcome this challenge and to encourage them to participate into its global hit a fun challenge so what we did as a part of this workshop was we give them on how to navigate Kegel as a platform and we connected an event specifically focused on networking so that participants could network form teams we also conducted a deep in-depth technical session focusing on deep neural nets and specifically on convolutional neural nets the understanding of which was pivotal to be able to solve this year's marathon challenge and the most interesting part of this telethon workshop was a mentorship guidance we were able to line up some amazing mentors and assign these minders to the concern or the interested participating teams and these matters work with respective teams for the next three weeks and for them terms with the required guidance coaching and mentorship held them for the VidCon showed me that's fantastic so over a three-week period how many participants did you have there 110 plus people for the key right yeah for the event and there are multiple teams that have formed and we assigned those mentors we identified seven different mentors and assigned these mentors to the interested participating teams we got a great response in terms of amazing turnout for the event new teams got formed new relationships got initiated new relationships new collaborations all right tell us about those achievements so they were there was one team from engineering branch or engineering division who were really near to the killer's platform they have their engineering exams coming up but despite that they learned a lot of these new concepts they form the team they work together as a team and we were able to submit the code on the Kegel leader board they were not the top scoring team but this entire experience of being able to collaborate look at the problem from different perspective and be able to submit the code despite one of these challenges and also navigate the platforming itself was a decent achievement from my perspective a huge achievement yeah so who you are at Stanford today you're gonna be flying back to go host the event there tell us about from your perspective if we look at the future line of sight for data science let's just take a peek at the momentum this that this Woods movement is generating this is our fourth year covering this fourth annual event fourth year on the cube and we see tremendous tremendous momentum mm-hmm with not just females participating and the woods leaders providing this sustained education throughout the year the podcast for example that they released a few months ago on Google Play on iTunes but also the number of participants worldwide as you look where we are today what in your perspective is the future for data science all right so data science is a domain is evolving at a lightning speed and may possibly hold the solution to almost all the challenges faced by humanity in the near future but to be able to come up with the most amicable and sustainable solution that's more relevant to the domain achieving diversity in this field is most and initiatives like wits help achieve that diversity and foster a real impact absolutely what's original thank you so much for joining me on the cube this morning live from wins 2019 we appreciate that wish you the best of luck kids a local event in Bengaluru over the weekend thank you it was a pleasure likewise thank you we want to thank you you're watching the cube live from Stanford University at the fourth annual woods conference I'm Lisa Martin stick around my next guest will join me in just a moment

>> From Santa Clara, California in the heart of Silicon Valley, it's theCUBE, covering Technovation's World Pitch 2018. Now here's Sonia Tagare. >> Hi, welcome back, I'm Sonia Tagare, here with theCUBE in Santa Clara, California, covering Technovation's World Pitch Summit 2018, a pitch competition for girls who develop mobile apps in order to create positive change in the world. This week, 12 finalists are competing for their chance to win the gold or silver scholarships. With us right now, we have, from Delhi, India Team Cantavits. So we have Sneha Agarwal, Aditi Jain, Shriya Shukla. Then we have Kritika Sharma, and then we have Shraddha Chugh. With them is their coach, Archana Jain. So congratulations, and welcome to theCUBE. >> Thank you. >> So your app, Eedo, tell us more about that. >> So Eedo is a late Latin word for electronic waste. our app is all about electronic waste. Electronic waste is electronic equipment which are not in a working condition right now. So what we do is connect people who generate e-waste to people who recycle it in an eco-friendly manner without harming the environment, and health problems. Because, generally people, what they do is, they dispose their e-waste as regular trash, or they just throw it in the dustbins, or maybe sell it to the local scrap dealers which harm the environment illegally, and harms all the human health. So our app is just about connecting e-waste generators and e-waste recyclers, to not harm environment and human health from e-waste dispos&al. >> It sounds like it could have quite the social impact. What inspired you all to create this app? >> Actually, it was one of the potential ideas when we had a brainstorming session to choose an idea for an app for Technovation challenge, but then we read a grave article about e-waste in a national daily, and that motivated us further, and we decided to make an app to solve this issue. >> What inspired you to join Technovation? >> Actually, Technovation always gave us inspiration, and that spirit to just go into the field of information and technology and create cool apps to solve community issues. I think we were, in 2016, we came to know about Technovation, and just reading about an overview of Technovation, it just gave us that spirit and that enthusiasm to participate in this competition. >> And how did you all create your team? How did you meet? >> She's our teacher at school, and she's the one who introduced us all. I, Aditi, and Shraddha, we have been participating for three years in this competition. This is the third year, and Shriya has been participating for two years. This is her second year, and Sneha is the new one, and she introduced us all. She came up, and we went to her once or twice, then she introduced us to this competition. >> Actually, she appointed all the students, that we should come as a team, >> Yeah >> and go into this competition. >> That's wonderful. So how do you think, being a part of this competition, how has it helped you? Has it made you more interested in technology? >> Yeah, definitely. >> Actually, Technovation gave us the opportunity to go in a world of endless opportunities. Actually, Technovation helped us to actually identify ourselves, identify inner talent so that we solve community issues, and create coding, actually go into coding, and that high tech opportunities. >> Yeah? >> Yeah. >> Just take the microphone. >> You want to add anything? >> I want to add. We also got to learn many things that we'll not learn if we didn't get to know about Technovation. We learned coding, and marketing strategies, which we'll not be able to learn if we not create an app for Technovation. >> Well that's wonderful. >> For me, earlier, coding was a very difficult task. I'm talking three years back, but now, after participating in this event in three years, it has been very easy and it it is very helpful to develop a new career in our life so we can go in the field of software engineering, or many other fields that will be very wonderful for our life. >> That's very inspiring. What are you most excited about this week at the Technovation competition? >> For this week, we're most excited about pitching our app in front of the people so that we can generate awareness about the e-waste problem and our solution to it. >> That's great. Can you tell us a little bit more about how a user can use this app? >> Actually, if I'm a common user, and I have to use my app to dispose of the e-waste, so what will I do? I download the app from the Google Play Store, just post an ad of the e-waste, like, I have a Mumbai phone that's broken now. I just enter the device name, the quantity, and the date and time for collection, and I'll just post the ad. Only that's much work from the generator of e-waste, and then comes in all of recyclers of the e-waste. He'll just see the list of ads which have been posted by the generators of e-waste. He'll click the ad, view it's details, and accept that for pick up. After picking that e-waste from user's doorstep, he'll be given a reasonable amount for the same to the user. Wow, so what advice would you give to other girls who want to join Technovation? >> I want to say that Technovation gave us wings, as I mentioned earlier to fly in a world of endless opportunities, and I would say that if you have that will to do something good for society, technology is the best option you can go for, and you can implement to solve community issues. So, go girls, I would say, go girls in the field of information technology, and do whatever you want. >> Well, that's a great note to end on. Thank you all so much for being here, and congratulations, and good luck on your pitch tomorrow. >> Thank you. >> We are here at Technovation's World Pitch Summit 2018 in Santa Clara, California, stay tuned for more. (electronic music)

(electronic music) - Welcome to theCube Insights. A podcast that is typically taken from Siliconangle media's theCube interviews, where we share the best of our teams insights from all events we go to and from time to time we want to be able to extract some of our learnings when we're back at the ranch. Joining me for this segment is co-founder, co-CEO, benevolent dictator of a community, my boss, Dave Vellante. - Hey Stu. - Dave. Good to see you dressed down. - Yeah, well. Podcast, right? We got toys, props and no tie. - Yeah, I love seeing this ... we were just talking, John Furrier, who we could really make a claim to say we wouldn't have the state of podcasting today, definitely in tech, if it wasn't for what John had done back in the day with PodTech and it's one of those things, we've talked about podcasts for years but I'd gotten feedback from the community that said, "Wow, you guys have grown and go to so many shows that we want to listen to you guys as to: what was interesting at this show, what did you guys take out of it, what cool people did you interview?" We said, "Well, of course all over youtube, our website thecube.net but it made a lot of sense to put them in podcast form because podcasts have had a great renaissance over the last couple of years. - Yeah, and it's pretty straight forward, as Stu, for us to do this because virtually every show we do, even if it's a sponsor show, we do our own independent analysis upfront and at the tail end, a lot of our people in our community said, "We listen to that, to get the low down on the show and get your unfiltered opinion." And so, why not? - Yeah, Dave. Great point. I love, from when I first came on board, you always said, "Stu, speak your mind. Say what the community; what are the users saying? What does everybody talk about?" As I always say, if there is an elephant in the room we want to put it on the table and take a bite out it. And even, yes, we get sponsored by the companies to be there. We're fully transparent as to who pays us. But from the first Cube event, at the end of the day, where after keynote, we're gonna tell you exactly what we think and we're always welcome for debate. For people to come back, push on what we're saying and help bring us more data because at the end of the day, data and what's actually happening in the world will help shape our opinions and help us move in the direction where we think things should go. - I think the other thing is too, is a lot of folks ask us to come in and talk to them about what we've learned over the past year, the past six months. This is a great way for us to just hit the podcast and just go through, and this is what I do, just go through some of the shows that I wasn't able to attend and see what the other hosts were saying. So, how do you find these things? - Yeah, so first of all, great. theCube insights is the branding we have on it. We're on iTunes, We're on Spotify, We're on Google Play, Buzzsprout's what we use to be able to get it out there. It's an RSS on wikibon.com. I will embed them every once in a while or link to them. We plan to put them out, on average, it's once a week. We wanna have that regular cadence Typically on Thursday from a show that we've been out the spring season is really busy, so we've often been doing two a week at this point, but regular cadence, just podcasts are often a little tough to Google for so if you go into your favorite player and look at thecube insights and if you can't find it just hit you, me, somebody on the team up. - So you just searched thecube insights in one of those players? - Yeah absolutely, I've been sitting with a lot of people and right now it's been word of mouth, this is the first time we're actually really explaining what we're doing but thecube one word, insights is the second word I found it real quick in iTunes I find it in Google Play, Spotify is great for that and or your favorite podcast player Let us know if we're not there. - So maybe talk about some of the things we're seeing. - Yeah absolutely - The last few months. - So, right when we're here, what are our key learning? So for the last year or two Dave, I've really been helping look at the companies that are in this space, How are they dealing with multi cloud? And the refinement I've had in 2018 right now is that multi cloud or hybrid cloud seems to be, where everyone's Landing up and part of it is that everything in IT is heterogeneous but when I talk about a software company, really, where is their strength? are they an infrastructure company that really is trying to modernize what's happening in the data center are they born with cloud are they helping there? or are they really a software that can live in SAAS, in private cloud and public cloud? I kinda picture a company and where's their center of gravity? Do they lean very heavily towards private cloud, and they say public cloud it's too expensive and it's hard and You're gonna lose your job over it or are they somebody that's in the public cloud saying: there's nothing that should live in the data center and you should be a 100% public cloud, go adopt severless and it's great and the reality is that customers use a lot of these tools, lots of SAAS, multiple public Cloud for what they're doing and absolutely their stuff that's living in the data center And will continue for a long time. what do you see in it Dave? - My sort of takeaway in the last several months, half a year, a year is we used to talk about cloud big data, mobile and social as the forward drivers. I feel like it's kinda been there done that, That's getting a little bit long in the tooth and I think there's like the 3DS now, it's digital transformation, it's data first, is sort of the second D and disruption is the 3rd D And I think if you check on one of the podcast we did on scene digital, with David Michella. I think he did a really of laying out how the industry is changing there's a whole new set of words coming in, we're moving beyond that cloud big data, social mobile era into an era that's really defined by this matrix that he talks about. So check that out I won't go into it in detail here but at the top of that matrix is machine intelligence or what people call AI. And it's powering virtually everything and it's been embedded in all types of different applications and you clearly see that to the extent that organizations are able to Leverage the services, those digital services in that matrix, which are all about data, they're driving change. So it's digital transformation actually is real, data first really means You gotta put data at the core of your enterprise and if you look at the top five companies in terms of market cap the Googles, the Facebooks, the Amazons, the Microsofts Etc. Those top five companies are really data first. But People sometimes call data-driven, and then disruption everywhere, one of my favorite disruptions scenarios is of course crypto and blockchain And of course I have my book "The Enigma war" which is all about crypto, cryptography and we're seeing just massive Innovation going on as a result of both blockchain and crypto economics, so we've been really excited to cover, I think we've done eight or nine shows this year on crypto and blockchain. - Yeah it's an interesting one Dave because absolutely when you mention cryptocurrency and Bitcoin, there's still a lot of people in the room that look at you, Come on, there's crazy folks and it's money, it's speculation and it's ridiculous. What does that have to do with technology? But we've been covering for a couple of years now, the hyper ledger and some of these underlying pieces. You and I both watch Silicon Valley and I thought they actually did a really good job this year talking about the new distributed internet and how we're gonna build these things and that's really underneath one of the things that these technologies are building towards. - Well the internet was originally conceived as this decentralized network and well it physically is a decentralized network, it's owned essentially controlled by an oligopoly of behemoths and so what I've learned about cryptocurrency is that internet was built on protocols that were funded by the government and university collaboration so for instance SMTP Gmail's built on SMTP (mumbles) TCPIP, DNS Etc. Are all protocols that were funded essentially by the government, Linux itself came out of universities early developers didn't get paid for developing the technologies there and what happened after the big giants co-opted those protocols and basically now run the internet, development in those protocol stopped. Well Bitcoin and Ethereum and all these other protocols that are been developed around tokens, are driving innovation and building out really a new decentralized internet. So there's tons of innovation and funding going on, that I think people overlook the mainstream media talks all about fraud and these ICO's that are BS Etc. And there's certainly a lot of that it's the Wild West right now. But there's really a lot of high quality innovation going on, hard to tell what's gonna last and what's gonna fizzle but I guarantee there's some tech that's being developed that will stay the course. - Yeah I love....I believe you've read the Nick Carr book "The Shallows", Dave. He really talked about when we built the internet, there's two things one is like a push information, And that easy but building community and being able to share is really tough. I actually saw at an innovation conference I went to, the guy that created the pop-up ad like comes and he apologizes greatly, he said "I did a horrible horrible thing to the internet". - Yeah he did - Because I helped make it easier to have ads be how we monetize things, and the idea around the internet originally was how do I do micropayments? how do I really incent people to share? and that's one of the things we're looking at. - Ad base business models have an inherent incentive for large organizations that are centralized to basically co-opt our data and do onerous things with them And that's clearly what's happened. users wanna take back control of their data and so you're seeing this, they call it a Matrix. Silicon Valley I think you're right did a good job of laying that out, the show was actually sometimes half amazingly accurate and so a lot of development going on there. Anywhere you see a centralized, so called trusted third-party where they're a gatekeeper and they're adjudicating essentially. That's where crypto and token economics is really attacking, it's the confluence of software engineering, Cryptography and game theory. This is the other beautiful thing about crypto is that there is alignment of incentives between the investor, the entrepreneur, the customer and the product community. and so right now everybody is winning, maybe it's a bubble but usually when these bubbles burst something lives on, i got some beautiful tulips in my front yard. - Yeah so I love getting Insight into the things that you've been thinking of, John Furrier, the team, Peter Borus, our whole analyst team. Let's bring it back to thecube for a second Dave, we've done a ton of interviews I'm almost up to 200 views this year we did 1600 as a team last year. I'll mention two because one, I was absolutely giddy and you helped me get this interview, Walter isaacson at The Dell Show, One of my favorite authors I'm working through his DaVinci book right now which is amazing he talks about how a humanities and technology, the Marrying of that. Of course a lot of people read the Steve Jobs interview, I love the Einstein book that he did, the innovators. But if you listen to the Michael Dell interview that I did and then the Walter isaacson I think he might be working on a biography of Michael Dell, which i've talk to a lot of people, and they're like i'd love to read that. He's brilliant, amazing guy I can't tell you how many people have stopped me and said I listened to that Michael Dell interview. The other one, Customers. Love talking about customers especially people that they're chewing glass, they're breaking down new barriers. Key Toms and I interviewed It was Vijay Luthra from Northern trust. Kissed a chicago guy And he's like "this is one of the oldest and most conservative financial institutions out there". And they're actually gonna be on the stage at DockerCon talking about containers they're playing with severless technology, how the financial institutions get involved in the data economy, Leverage this kind of environment while still maintaining security so it was one that I really enjoyed. How about...... what's jumped out of you in all your years? - (Mumbles) reminds me of the quote (mumbles) software is eating the world, well data is eating software so every company is.... it reminds me of the NASDAQ interview that I did Recently and all we talked about, we didn't talk about their IT, we talked about how they're pointing their technology to help other exchanges get launched around the world and so it's a classic case of procurer of technology now becoming a seller of technology, and we've seen that everywhere. I think what's gonna be interesting Stu is AI, I think that more AI is gonna be bought, than built by these companies and that's how they will close the gap, I don't think the average everyday global 2000 company is gonna be an AI innovator in terms of what they develop, I think how they apply it is where the Innovation is gonna be. - Yeah Dave we had this discussion when it was (mumbles) It was the practitioners that will Leverage this will make a whole lot more money than the people that made it. - We're certainly seeing that. - Yeah I saw.....I said like Linux became pervasive, it took RedHat a long time to become a billion dollar company, because the open stack go along way there. Any final thoughts you wanna go on Dave? - Well so yeah, check out thecube.net, check out thecube insights, find that on whatever your favorite podcast player is, we're gonna be all over the place thecube.net will tell you where we're gonna be obviously, siliconangle.com, wikibon.com for all the research. - Alright and be sure to hit us up on Twitter if you have questions. He's D Villante on twitter, Angus stu S-T-U, Furrier is @Furrier, Peter Borus is PL Borus on twitter, Our whole team. wikibon.com for the research, siliconangle.com for the news and of course thecube.net for all the video. - And @ TheCube - And @TheCube of course on Twitter for our main feed And we're also up on Instagram now, so check out thecube signal on one word, give you a little bit of behind the scenes fun our phenomenal production team help to bring the buzz and the energy for all the things we do so for Dave Vellante, I'm Stu Miniman, thanks so much for listening to this special episode of thecube insights. 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>> Announcer: Live from Las Vegas, it's theCUBE, covering AWS Reinvent 2017, presented by AWS, intel, and our ecosystem of partners. >> Welcome back everyone, live here in Las Vegas. We're at AWS Reinvent. Day one coverage of three days of theCUBE, I'm John Furrier, the host this week. >> We've got two sets, our fifth year covering Reinvent. It's been great to watch. Every year we try to get in the VC panels. We just had Jerry Chen on from Greylock. We've got two more awesome friends of theCUBE in the community here. We've got Sunil Dhaliwal who is the founder of Amplify Ventures and Nick Sturiale with Ignition Partners. Guys, great to see you. >> Great to see you, John. >> Good to see you, John. >> Boy what a lineup it's been over the past three years, four years with Amazon, just watching them tear. Now it's all steamed ahead. Microsoft is totally gearing up. You can see them playing, what they're doing, they're pedaling as fast as they can. Google Play and the (mumbles) we're gonna compete on TensorFlow and other, little goodness, a lot more to go. You got Alibaba Cloud. Intel behind us is making (mumbles) chips. Good market on paper. >> Yeah. >> But we're seeing startups kind of get bought, not for what they wanted. Didn't go public. Skyhigh from Greylock. You see Barracuda going private. A lot of money to be made. Maybe the investment thesis of 200 million dollar fundings, that's over, is it over? Get a little bit of cash and get the critical mass and... >> Well, here's a question. Do you invest in these companies thinking every one of them is going to go public? Or do you think that a good number of them are gonna get acquired? And I think the investors that have done this for a while, and Nick's done this for what, like 45 years? >> I started when I was two, so. >> I've done this like two years less than you have, so I don't pretend I'm dramatically younger. But the reality is, these companies get acquired. And pretending that you're gonna pile into a company late and expect every single thing to go public I think is kind of crazy. And the people that are getting caught in that trap, I think they're gonna be in for a rude awakening. But look, you've got a billion six outcome for Barracuda, right? >> John: That was pretty damn good. >> And you know Skyhigh number hasn't been printed, but it wasn't a small one. Like, those are good outcomes. Those are good venture returns, if you were smart about where you got in. >> So I have a slightly different perspective, which is the real issue is that so much money moved into the late stage, and these companies thought that growth would always be linear even asymptotic. And so what happens is that their growth rate slows down and the cost of growth goes up, and suddenly the company's not quite as hot as it was a year ago, and so now the options for what they do have shrunk dramatically, and so you get exits like you just mentioned. And so part of the problem is is that entrepreneurs and investors really have to have a sober view of what is a business model that's durable over time and which ones really are gonna start to leak in their later phases. >> Well it's kind of a planted question for you guys, because you're early stage in Amplify. I've been following you guys, do a great job. You guys do a range of early, end growth. >> Mostly early though. >> The days of just laying back and kicking your feet up and throwing cash at stuff is over. You actually gotta do the work. It sounds like old school VCs. Greg Sands and I talk about this all the time. You gotta go in and be venturing. You gotta actually make it work. >> And that sucks, I was just told I put my feet up, I put some money in and then I get a distribution check at the end of it. >> That's what everyone thinks you guys do. What do you guys do every day? Take us through your day. >> It looks a lot like that except... >> It's so easy to be a VC, all you do is okay, yes, no, okay that's good. >> We got a dartboard. >> All you gotta do is bet on the good ones. >> Yeah. >> That's so easy. >> So there are what, 14,000 startups in the bay area, how many of them are worthwhile you think? >> It's a lot of work. Well old school, let's go back to the old school tactics, because you're seeing a couple things going on. You guys essentially pointing it out, you gotta do the work and pick the winners. But now that the business models are changing, right? You're seeing Amazon just ignoring conventional wisdom, and they're winning. The game is changing a bit in the business model side. How are you guys looking at that as you make investments? So you got the classic venture, bet on a good team, do all that stuff. What do you guys look at now in the marketplace for fit, scale, longevity, durability? >> I mean the stuff we care about the most is are you going after a big problem? Because I think a lot of the stuff we see, even with your great teams and great technologies, but you step back and you actually think, you know, that isn't a company, that's a product, or that's not even a product, that's a feature. And I think that's the natural outgrowth of what happens when you got 14,000 startups in the bay area, is there aren't 14,000 products that are companies worth having. What you have is, probably 12,000 features, 1500 products, and then like 500 real companies. And that's probably the biggest filter that you gotta apply on the way in, and it's maybe the hardest one to solve for, which is, roll this out seven years, nine years, because that's really what you're talking about when you're talking about building a public durable company is, what does this market look like way down the road? And is that a thing that can stand alone? And that's really, I think, the difference between the companies and the investors that do really well and the ones that can kind of squeeze by, knocking out a couple interesting outcomes. >> My favorite thing is that when you say we just pick the winners, is that nobody knows who the winner is a priori. If you knew that, that market would be gone already. And most successful companies that you read about, and they talk about the (mumbles) investors that were in it early, that's all BS. It's a million good things happen along the way, serendipity, a ton of hard work on the management team and the employees. So this idea that things are preordained is just silly. And I would tell you that you look at most really successful companies today, their business model is completely different than the one that the venture person backed. >> I mean it's always the classic, because I remember when I first started an entrepreneur in the 90s, the question was what's your exit strategy? It was a legitimate question at that time, and it was kind of a peg mark, okay, when I build a growing company and have an exit. Now the exits are, as you mentioned, buyers. And that's not necessarily a bad thing. If Microsoft's in a race to fill in their white spaces, man, I would crop up and get the crops growing, right? So you can say, okay, Microsoft. So you guys gotta kind of do a little bit of homework there, do some relationship work, and you guys are close to Microsoft, so. >> Yes. >> I mean, is that kind of the new playbook? >> Yes. >> How should entrepreneurs posture to this? I mean obviously they're gonna try to build a durable venture, but they don't want to be zig-zagging too much or pivoting. >> No. >> I mean Nick made the point earlier, which I think is absolutely the one to focus on, which is when you raise a ton of capital your options start to shrink. The more money you raise at the higher and higher price, there's somebody you gotta serve who's thinking about the even bigger pot of gold at the end of the rainbow. And honestly, when we look at, I'll take one company in our portfolio for example, and I think the Splunk story is right up there with it, If you look at Datadog, Datadog's huge here at this show. There's purple shirts everywhere and a massive booth, and they've been here for five years running or four years running. That business has barely touched the last round of capital they raised, let alone the round of capital before that. The capital efficiency of that business, not only is it gonna make it a great outcome, but it's gonna give them tons of options of things that they can do. And, you know, they'll get to make every single decision they make, whether it's going to new product or whatever, position of strength. And not a lot of companies do that. >> So Splunk started in 2004. Guess how much total the company raised before it went public? >> How much? >> Forty million. Guess how much it spent up to the time it went public? >> John: How much? >> John: Twenty five. >> So it went public... >> So very capital efficient? >> John: Think about that. >> Yes, and it's worth 9 billion now. So you had several hundred millionaires created out of Splunk, and I would submit to you if Splunk was started today, the investor community would have killed it. >> John: Why? >> Because 18 Brinks trucks would have backed up and dumped a billion dollars on top of it, and buried it in too much money without allowing the company to get the time to become a fully viable system. >> Sunil: Yeah. >> So the too much cash can create toxicity for the startup? >> Money rarely makes the company. Money rarely makes the company. >> Lew Cirne was on earlier, founder of New Relic. Another capital efficient company. >> Great company. >> Went public all time high. Love that guy. He's such a strong, he wrote some code last week. He said, if you can help your partners be successful, in referring to Amazon. >> Man: Amazon. >> Then you can be a great ecosystem partner. So the question now is that's not a bad deal for a company to jump into the Cloud game and be a really good partner and build a kick-ass product. >> Yes. >> And look like a feature maybe on paper, and then sequence to an opportunity. Thoughts on that? It's certainly lucrative if you can get the flywheel going. Right? >> So you don't want to build a company whose basic thesis is helping Amazon or Azure or Google. That is a dead company. If, however, you pull revenue for one of those three in a way that's interesting to them, they will support you all day long. We have two companies in particular, Icertis and KenSci that are pulling a lot of revenue for Azure right now. And Microsoft gives them extraordinary support. >> That's the nuance right there. That's the nuance. Pulling revenue, value, creation. >> Yes. >> Well, they've created Amazon and Microsoft and Google, to a degree, as they get going. They've created a really interesting model, which is unlike your traditional ecosystem, hub-and-spoke model, where someone's gonna capture (mumbles) control of the sale, etc., etc. The smart thing that Amazon's done is they say, you use whatever you want, we're gonna bill you for the primitives until the cows come home, and as long as you're not standing in between Amazon and their primitives revenue, you're gonna do great. >> All right, final question for you guys. First of all, great conversation on the capital markets, certainly it's crazy. We always try to cover it, but here's a thought exercise. Last night we were at the analyst summit. We were talking to some analysts, and the question was, the airplane's going down, and you're in a board meeting, I gotta pick a parachute. There are only three parachutes, Amazon, Microsoft, and Google, which one do you grab? You got 10 seconds. >> To sell to or? >> No, just grab a parachute, and you hope that it opens and you live. Pick a parachute. >> Amazon, >> I'm going with Amazon. This one isn't hard. >> Microsoft and Google. The only person who's gonna grab the Microsoft parachute is the guy who's been with Microsoft for 30 years and knows they're not gonna let him down. If you're a forward-facing company you're going with Amazon, and if you're nuts, you're gonna grab Google right now. No offense to my friends at Google. >> So we're sitting here at Reinvent, so I feel like that's a trick question. (laughing) >> Well, that's good. If you're in the Microsoft ecosystem, they do take care of their own. >> They do. >> Their DNA is tuned to ISVs, they're very good at it. >> and that's their track record. Well, the one guys says, well it depends. By the time you argue with the parachute the planes (mumbles). But it does depend on your business. >> Sunil: Yes. >> Nick: Yes. >> But it is hard not to look at this show and say this is what electricity was in 1920. >> Final question, obviously Amazon is looking at all steam ahead, business models are changing, you're starting to see the top of the stack develop nicely, moving up the stacks seems to be the trend. You got this decentralized market up there. Bitcoin hit 10,000. A lot of smart alpha geeks, including some of the guys here at theCUBE team, is looking at ways to kind of leverage this decentralization trend in a way that's productive. Yet there's a lot of scams out there with these ICOs. Decentralization good or just another infrastructure dynamic? Thoughts on this whole decentralized token economics wave? Also the FCC has regulations now in it. Is it disrupting VC? Your thoughts, Nick. >> Do remember what H.L. Mencken said? "A fool and his money are soon parted." so I think anyone who sits there and says I understand completely what an ICO is and what I'm buying and doesn't view it as something that'll be a tax deduction for next year, I think is gonna be in for a bumpy ride. >> Get out your Gartner Hype Cycle. And if you don't know what it is, go look it up, and there's a spot right now of where we are in the hype cycle, and I think the movement my finger tells you where we are, but this is coming, but this comes afterwards. >> I heard this argument, the web is just for kids. No one will ever use the web. Browsers is a toy. >> A K memory is all you'll ever need. >> Yeah, but guess what, guess what, 2001 happened before we got to 2017, so let's never forget where we are at that kind of hype. >> ICOs are like subprime mortgages, and I speak Spanish and I can't even read the thing. That is what an ICO is. >> So certainly hyped up. Winter's coming, we'll see. All right, we got the VCs here, Nick and Sunil. We got Amplify and Ignition Partners here in theCUBE. More live coverage day one after this short break.

>> Announcer: Live, from Orlando, Florida, it's the Cube covering Grace Hopper's celebration of women in computing brought to you by Silicon Angle Media >> Welcome back to the Cube's coverage of the Grace Hopper conference here in Orlando, Florida I'm your host Rebecca Knight, along with my co host Jeff Frick. We're joined by Megan Smith. We're very excited to have you on the show. >> It's good to be here >> She is the third US CTO and also the CEO of a new company, Shift7.co, so thanks so much for joining us. >> Thanks for having me, it's great to be here. It's so fun to be at Hopper, >> Rebecca: It is, it is! >> It's cool, it's the Grace Hopper celebration, because we're trying to celebrate women in computing, and we're what, at 18 thousand people now, >> The biggest ever, >> Plus I think, 6 thousand people joining on the livestream, which is great. >> Before the cameras were rolling, we were talking about your role as the 3rd US CTO, and just talking about getting more technology into government to help leaders work together, and move faster. Tell us a little about this initiative. >> What's so great, is it's not partisan, fixing the government and making it work better, so all the work that we were doing continues. What we were able to put in place, during the Obama administration, and continues to Trump, were things like, the CT office. Having technical people, so I worked at Google, people work at Amazon, Facebook, Twitter, these companies who have that background, to join in on policy conversations, one, to join in on capacity building the government, so data sciences and tech and, let's have our services be as great as Amazon, or as Twitter, or Oracle, and not be sort of retro, really serve the American people. And then also, helping the American people in general, with capacity building, things like computer science for all. So that was an initiative that continues to get all of our children to have coding at school. That all children, you couldn't graduate from high school without having had some experience on learning of coding Coding is a 21st century fluency, it's a skill we all need, Like freshman biology. You want to know some biology, you want to know some coding, you want to know how to write, so making sure they have is tech-up, which was a program we started to help train Americans, there's six hundred thousand jobs open, in the United States, and they pay 50% more than the average American salary. The companies are starving. How do we rapidly get more Americans into these jobs? It turns out that people have, of course, created these fabulous code boot camps, you can train in three months for these jobs, some of them are paid, some times they pay you, all different kinds, some are online, some are offline, they're all over the country. So we're able to get more people to consider, a job like that, culturally they think, Well I don't, why would I, I don't know how to do that. Well you can, this is a fun and interesting and exciting career, you can do digital marketing, you can do user interface design. You can get involved in front end or back end coding, product management, all those things, sales. And so, how do you pull lots more Americans in, get our companies fueled so we have really the economic opportunity, and they're all over the country. Location wise, and topic wise. So we did tech hour now, and a tech jobs tour, which is not what we did in government, but we continue some of that work. >> This weird dichotomy, because on one end, people are worried about tech taking jobs, on the other hand, there's a ton of open tech jobs. And there's this transition period, that's difficult, obviously for people that didn't grow up, but one of the keynote speakers today, told a really heartening story, that she didn't get into it until the day she had to leave her abusive husband, and now she is a coder >> That's Doctor Sue Black, who was just given the Order of the British Empire, I mean, she is an incredible computer scientist. Yes, she escaped an abusive marriage with three small children, in her early 20s, I think. Ended up moving into public housing, and dealing with three children only being the school from 9 until 3, and eventually getting her PhD in computer science, and really, she started Techmoms now, she continues to do research in other things, but she's really trying to use her story, and her organizing capacity, to have more people realize this isn't hard like figuring out gravity waves that won the Nobel prize. This is hard like writing a hard essay, so we all can learn to write an essay. It takes some mastery work, you don't learn it in kindergarten but by the time you're in 7th, 8th, 9th, 10th, 12th grade, you can do it. >> It's not rocket science. >> Right, so coding is like that. >> The other piece you said that's very interesting, is the consumerization of IT. We've seen it at enterprise, a huge trend. But, now I expect everything that's on my phone, when I interact with Facebook or Amazon, or whatever, to be in all the applications, so, as you said, that's influencing government, and the way they have to deliver services, and I would imagine, too, with kind of the next wave of kids coming in, graduating, going into public service, they certainly have that expectation, right? They've been working on their phone forever of course it should be on the phone. >> And so we want everybody in our country fluent in computer science and coding at a basic level, like again, like freshman biology or takin' chemistry in high school, or taking writing. So that everyone could realize this is not rocket science we could have these kinds of capabilities as part of our services, from Housing and Urban Development, from the Department of Education. You know, a lot of us use our phones to get places, you know, on our maps, and so that's actually data coming from the US Geological survey, if you're looking at the weather, you're looking at NOAA's satellites, this is open government data. We were able to open over two hundred thousand data sets, from all over government, not private data, but public data, that you could make an entire app store, or Google play set of products on top of that. Government wouldn't have to pay for that, it just packages up the API as well. A really good example of that, is the US census team. There's nothing more big data than census, they have all of our information from a data perspective, and so they did opportunity.census.gov, and they said to various agencies, let us help you bridge these data sets into something that someone could build on top of, like we're seeing from the courses sector, we saw wonderful things like, Housing and Urban Development said, okay, our challenges are housing affordability, mobility, these are the challenges instead of having HUD make an app for Americans to come to, they just can explain what their problem is, what data sets, and then engage extraordinary companies, like airbnb, Redfins, Zillow, these fabulous tech companies, who can make instead a product for 100% of the Americans, rather than only wealthy or middle class Americans, and so they did things like, opportunity score, and airbnb helping you figuring out, if I rent a room in my house I can make my rent more affordable, very creative apps, that we can see, same thing for the Department of Ed or Department of Labor, and as the data gets out there, and as apps come, also the opportunity for data science and machine learning. What if, as much as we serve ads to ourselves, in these algorithms, what if we use the algorithms to help Americans find a job that they would love? You know, job matching, and these kinds of opportunities. of the problems in the world, and helping government get more fluent at that. And the way to do that is not so much, jam the government You have to do this, but find terrific talent like we see at Hopper, and have them cycle into the government, to be co-leaders just like a surgeon general would come. >> Are you facing recruitment challenges in that same way though? In the sense that technology is having a hard enough time recruiting and retaining women, but the government, too, is that seen as enough of an employer of choice for young talented, bright ambitious, young women? >> I'm not in government now, but when we were in there, we found a very interesting thing. Alex Mcgovern, who had been the general counsel of Twitter who was Stephanie's CTO with me and led a lot of our tech quals we called TQ like tech IQ in policy, together with economists and lawyers and others have if we're going to decide net neutrality, let's include everyone, including computer scientists, and we're going to sue bridge and open source, So we talked about that, and on the way going in Mcgovern, he said, wouldn't it be cool if, just like when you look at a lawyer's resume, you might see that they clerk and they served their county through clerking and through the judicial system, as well as being a private lawyer, they were a public defender, that's a pretty normal thing to see on a legal resume. If you looked at medical, you might see them going into NIH or doing some research, if you looked at a scientist, they might have gone to, done some NSF work or others. But for the tech crew, there is of course amazing technical people in NASA, NAH and the Department of Energy, and there's great IT teams, but there's not this thing that the Silicon Valley crew resume would say, oh, yeah, I served my country. So that's why, under President Obama, we were able to create these incredible programs. The Presidential Innovation Fellows, which was a one year term of service, The United States Digital Service, which is a three months to a two year term of service in the VA. What's more amazing if you build Amazon, than to go as a second act and help our veterans? It's an incredible honor, to the point of, will they come? Yes, that's what we were hoping, could we have that be a normal thing, and yes it's become a normal thing. And the Trump administration continues it. The 18F team is in the general services administration, they're on 18th and F so they have a code name. But that particular team is located around the country, not only in DC but in San Francisco, in Chicago, and others. So you see this tech sector flowing now into the government on a regular basis, and we welcome more peoples. The government is who shows up to help, so we need the tech sector to show up cause we've got a lot of money as a country, but if we're not effectively using it we're not serving the American people and foster children, veterans, elders, others need the services that they deserve and we have the money, so let's make it happen the way the tech sector is delivering Amazon packages or searches. >> What is your feeling, this is not your first Grace Hopper obviously, but what is your feeling about this conference, and advice that you would give to young women who are here, maybe for their first or second time, in terms of getting the most their time here? >> You know, I think the main thing is, it's a celebration, that's fun and you can walk up to anyone, so just talk to everyone. I've been talking to a million people on the floor, fabulous. Students are here, more senior technical leaders are here. We've been running speed mentoring, we're running a program called the Tech Jobs Tour, it's at Techjobstour.com, it's a #Americanshiring, and we've been going to 50 different cities and so we're running a version of that, and we do speed mentoring, so come to the speed mentoring sessions, it's a five minute pop, talk to someone about what you're tryin' to do. Lot's of programs like that, get into the sessions, come to the keynotes which are so inspiring, and Melinda Gates was amazing today, Dr. Fefe Lee was incredible, just across aboard, Dr Sue Black was here, I thought it was great today, actually, just to reflect on Melinda's keynote, I think this might have been the first time, I was talking to her, that she's really talked about her own technical experience >> That struck me, too! As a coder, starting in computer science. I didn't really understand that she had really started very early, with Apple 3 and the story of her dad >> And her love of her Apple 3, right! and really high school coding, which is so important for young people in high school and middle school, even younger. The Muscogee Creek Tribe, in Oklahoma, is teaching robotics in head start, so we can start in preschool. Just make it fun, and interesting. They're funny, they don't do battle bots, because you don't really want to teach 3 and 4 year olds to fight, so instead they have collaborative robots. >> Robots who work together Age appropriate. >> Well Megan Smith, this has been so fun talking to you, thanks so much for coming on our show. >> Thanks for having me. >> We will have more from the Grace Hopper Conference just after this, I'm Rebecca Knight for Jeff Frick (music)