>> Narrator: From Sand Hill Road, in the heart of Silicon Valley, it's the CUBE. Presenting, The People First Network, insights from entrepreneurs and tech leaders. >> Hello everyone welcome to this special CUBE conversation, I'm John Furrier, host of theCUBE. We're here at Mayfield Fund, on Sand Hill Road and Menlo Park. As part of Mayfield's People First Network, co-creation with SiliconANGLE and theCUBE and Mayfield. Next guest, Beth Devin, Managing Director of Innovation Network and Emerging Technologies at Citi Ventures. Thanks for coming on. >> Thanks for having me. >> Hey, thanks for coming in. We're here for the Mayfield fiftieth anniversary, where they're featuring luminaries like yourself, and we're talking about conversations around how the world's changing and the opportunities and the challenges can be met, and how you can share some of your best practices. Talk about what your role is at Citi Ventures and what your focus is. >> Sure, sure, and boy howdy, has it been changing. It's hard to keep up with. I've been at Citi Ventures about two years and one of the reasons I joined was to stand up an Emerging Technology practice. Citi Ventures does a lot of work in corporate venture investing. We tend to be strategic investors, for start up companies that are aligned with the strategy of Citi, as well as our client. We serve probably, eighty percent of the Fortune Five Hundred companies in the world. But we also are a really important part of the innovation ecosystem at Citi. Which is looking at how to drive culture change, broaden mindset, and really, enlist our employees to be part of the innovation process. So, we have an internal incubator, we have a Shark Tank-like process we call Discover Ten X. And what I really bring to the table with my team is monitoring, and learning about, and digesting technology that's not quite ready for commercialization but we think it might be disruptive in a good or challenging way for the bank or our clients. We try to educate and provide content that's helpful to our executives, and just the employee body at large. >> I want to get into a LinkedIn post you wrote, called the Tech Whisperer, which I love. >> Thank you. >> You're there to identify new things to help people understand what that is. But that's not what you've done. You've actually implemented technology. So, on the other side of the coin, in your career. Tell us about some of the things you've done in your career, because you've been a practitioner. >> Beth: Yeah. >> and now you're identifying trends and technologies, before you were on the other side of the table. >> That's right, and sometimes I'll tell you, I have that itch. I miss the operator role, sometimes. Yeah, you know, I feel so fortunate I sort of stumbled on computer science early when I was going to school. And, the first, I'd say twenty years of my career, were working in enterprise I.T, which at that time I couldn't even have made that distinction, like why do you have to say enterprise I.T. I was a software developer, and I was then a DBA, and I even did assembler language programing. So way back when, I think I was so fortunate to fall in to software engineering. It's like problem solving, or puzzle making, and you with your own brain and sort of typing can figure out these problems. Then over the years I became more of a manager and a leader, and sort of about a reputation for being somebody you could put on any hard problem and I'd figure a way out. You know tell me where we're trying to go it looks knotty, like not a fun project, and I would tackle that. And then I'd say, I had some experience working in lots of different industries. Which really gave me an appreciation, for you know, at the end of the day, we can all debate the role that technology plays in companies. But industries, whether it's health care or media, or financial services. There's a lot of the same challenges that we have. So I worked at Turner Broadcasting before it was acquired, you know by Time Warner and AOL. And I learned about media. And then I had a fantastic time working at Charles Schwab. That was my first big Financial Services role when it came back to the bay area. I worked at Art.Com, it was a need converse company, the first company I worked at where I was in charge of all the technology. We had no brick and mortar, and if the technology wasn't working, we weren't earning revenue, in fact, not only that, we were really making customers angry. I also had a role at a start up, where I was the third person to join the company, and we had a great CEO who had a vision, but it was on paper. And we hadn't really figured out how to build this. I was very proud to assemble a team, get an office, and have a product launch in a year. >> So you're a builder, you're a doer, an assembler, key coding, hexadecimal cord dumps back in the day. >> Way back when. We didn't even have monitors. I'll tell ya, it was a long time ago. >> Glory days, huh? Back when we didn't have shoes on. You know, technology. But what a change. >> Huge change. >> The variety of backgrounds you have, The LinkedIn, the Charles Schwab, I think was during the growth years. >> And the downturn, so we got both sides. >> Both sides of that coin, but again, the technologies were evolving. >> Yes. >> To serve that kind of high frequency customer base. >> Beth: That's right. >> With databases changing, internet getting faster. >> It has. >> Jeff: More people getting online. >> We were early adopters, I'll tell you. I still will tell people, Charles Schwab is one of the best experiences I have, even though at the end I was part of the layoff process. I was there almost seven years, and I watched, we had crazy times in the internet boom. Going in 98, 99, 2000, I can't even tell you some of the experiences we had. And we weren't a digital native. But we were one of the first companies to put trading online, and to build APIs so our customers could self service, and they could do that all online. We did mobile trading. I remember we had to test our software on like twenty different phone sets. Today, it's actually, so much easier. >> It's only three. Or two. Or one. Depending on how you look at it. >> That's right. We couldn't even test on all the phone sets that were out then. But that was such a great experience, and I still, that Schwab network, is still people I'm in touch with today. And we all sort of sprinkled out to different places. I think, I dunno, there's just something special about that company in terms of what we learned, and what we were able to accomplish. >> You have a fantastic background. Again the waves of innovation you have lived through, been apart of, tackling hard problems, taking it head on. Great ethos, great management discipline. Now more than ever, it seems to be needed, because we're living in an age of massive change. Cause you have the databases are changing, the networks changing, the coding paradigms changing. Dev ops, you've got the role of data. Obviously, mobile clearly is proliferated. And now the business models are evolving. Now you got business model action, technical changes, cultural people changes. All of those theaters are exploding with opportunity, but also challenges. What's your take on that as you look at that world? >> You know, I'm a change junkie, I think. I love when things are changing, when organizations are changing, when companies are coming apart and coming together. So for me, I feel like, I've been again, so fortunate I'm in the perfect place. But, one of the things that I really prided myself on early in my career, is being what I call the bridge, or the, the translator between the different lines of business folks that I work with. Whether it was head of marketing, or somebody in a sales or customer relationship, or service organization, and the technology teams I built and led. And I think I've had a natural curiosity about what makes a business tick, and not so much over indexing on the technology itself. So technology is going to come and go, there's going to be different flavors. But actually, how to really take advantage of that technology, to better engage your customers, which as you said, their needs and their demands are changing, their expectations are so high. They really set the pace now. Who would have though that ten years ago we'd live in an environment where industries and businesses are changing because consumers have sort of set the bar on the way we all want to interact, engage, communicate, buy, pay. So there's this huge impact on organizations, and you know, I have a lot of empathy for large established enterprises that are challenged to make it through this transformation, this change, that somehow, they have to make. And I always try to pay attention on which companies have done it. And I call out Microsoft as an example. I can still remember several years ago, being at a conference. I think it was Jeffrey Moore who was speaking, and he had on one slide... Here's all the companies in technology that have had really large success. Leading up to the internet boom days, there would be a recipe for the four companies that would come together. I think it was Sun, Oracle, and Microsoft. And then he said, and now here's the companies of today. And most young people coming out of college, or getting computer science degrees won't use any of these old technology companies. But Microsoft proved us all wrong, but they did it, focused on people, culture, being willing to say where they screwed up, and where they're not going to focus anymore, and part ways with those parts of their business. And really focus on who are their customers, what are their customer needs. I think there's something to be learned from those changes they made. And I think back to the Tech Whisperer, there's no excuse for an executive today, not to at least understand the fundamentals of technology. So many decisions have to be made around investment, capital, hiring, investment in your people. That without that understanding, you're sort of operating blind. >> And this is the thing that I think I love, and was impressed by that Tech Whisperer article. You know, a play on the Horse Whisperer, the movie. You're kind of whispering in the ears of leaders who won't admit that they're scared. But they're all scared! They're all scared. And so they need to get, maybe it's cognitive dissonance around decision making, or they might not trust their lead. Or they don't know what they're talking about So this certainly is there, I would agree with that. But there's dynamics at play, and I want to get your thoughts on this. I think this plays into the Tech Whisperer. The trend we're seeing is the old days was the engineers are out coding away, hey they're out there coding away, look at them coding away. Now with Cloud they're in the front lines. They're getting closer to the customer, the apps are in charge. They're dictating to the infrastructure what can be done. With data almost every solution can be customized. There's no more general purpose. These are the things we talk about, but this changes the personnel equation. Now you got engineering and product people talking to sales and marketing people, business people. >> And customers. >> They tend not to, they traditionally weren't going well. Now they have to work well, engineers want to work with the customers. This is kind of a new business practice, and now I'm a scared executive. Beth, what do I do? What's your thoughts on that dynamic? >> You know, I'm not sure I would have had insight in that if I hadn't had the oppurtunity to work at this little start up, which we were a digital native. And it was the first time I worked in an environment where we did true extreme programming, pair programming, we had really strong product leads, and engineers. So we didn't have project managers, business analysts, a lot of things that I think enterprise I.T tends to have. Because the folks, historically, at an enterprise, the folks that are specifying the need, the business need, are folks in the lines of business. And they're not product managers, and even product managers, I say in banking for example, they aren't software product managers. And so that change, if you really do want to embrace these new methods and dev ops, and a lot of the automation that's available to engineering and software development organizations today, you really do have to make that change. Otherwise it's just going to be a clumsy version of what you use to do, with a new name on it. The other thing though that I would say, is I don't want to discount for large enterprises is partnerships with start up companies or other tech partners. You don't need to build everything. There's so much great technology out there. You brought up the Cloud. Look at how rich these Cloud stacks are getting. You know, it's not just now, can you provision me some compute, and some storage, and help me connect to the internet. There's some pretty sophisticated capabilities in there around A.I and machine learning, and data management, and analysis. So, I think overtime, we'll see richer and richer Cloud stacks, that enables you know, every company to benefit from the technology and innovation that's going on right now. >> Andy Jassy, the CEO of Amazon Web Search, has always said whenever I've interviewed him, he always talks publicly now about it is, two pizza teams, and automate the undifferentiated heavy lifting. In tech we all know what that is, the boring, mundane, patching, provisioning, ugh. And deploying more creative research. Okay so, I believe that. I'm a big believer of that philosophy. But it opens up the role, the question of the roles of the people. That lonely DBA, that you once were, I did some DBA work myself. System admins, storage administrator, these were roles, network administrator, the sacred God of the network, they ran everything. They're evolving to be much more coding oriented, software driven changes. >> It's a huge change. And you know, one thing that I think is sad, is I run into folks often that are, I'll just say, technology professionals, just say, you know, we're at large. Who are out of work. You know, who sort of hang their head, they're not valued, or maybe there's some ageism involved, or they get marked as, oh that's old school, they're not going to change. So, I really do believe we're at a point, where there's not enough resources out there. And so how we invest in talent that's available today, and help people through this change, not everybody is going to make it. It starts with you, knowing yourself, and how open-minded you are. Are you willing to learn, are you willing to put some effort forth, and sort of figuring out some of these new operating models. Because that's just essential if you want to be part of the future. And I'll tell you, it's hard, and it's exhausting. So I don't say this lightly, I just think. You know about my career, how many changes and twists and turns their have been. Sometimes you're just like, okay I'm ready, I'm ready to just go hiking. (Beth laughs) >> It can be, there's a lot of institutional baggage, associated with the role you had, I've heard that before. Old guard, old school, we don't do that, you're way too old for that, we need more women so lets get women in. So there's like a big dynamic around that. And I want to get your thoughts on it because you mentioned ageism, and also women in tech has also grown. There's a need for that. So there's more opportunities now than ever. I mean you go to the cyber security job boards, there are more jobs for cyber security experts than any. >> Oh, I'll tell you, yesterday, we held an event at our office, in partnership with some different start ups. Because that's one of the things you do when you're in a corporate venture group, and it was all on the future of authentication. So it was really targeted at an audience of information security professionals and chief information security officers. And it was twenty men and one woman. And I thought, wow, you know I'm use to that from having been a CIO that a lot of the infrastructure roles in particular, like as you were saying, the rack and stack, the storage management, the network folks, just tend to be more male dominant, than I think the product managers, designers, even software engineers to some extent. But here you know, how many times can you go online and see how many openings there are for that type of role. So I personally, am not pursuing that type of role, so I don't know what all the steps would need to be, to get educated, to get certified, but boy is there a need. And that needs not going to go away. As more, if everything is digitized and everything is online. Then security is going to be a constant concern and sort of dynamic space. >> Well, we interview a lot of women in tech, great to have you on, you're a great leader. We also interview a lot of people that are older. I totally believe that there's an ageism issue out there. I've seen it first hand, maybe because I'm over fifty. And also women in tech, there's more coming but not enough. The numbers speak for themselves. There's also an opportunity, if you look at the leveling up. I talked to a person who was a network engineer, kind of the same thing as him, hanging his head down. And I said, do you realize that networking paradigm is very similar to how cyber works. So a lot of the old is coming back. So if you look at what was in the computer science programs in the eighties. It was a systems thinking. The systems thinking is coming back. So I see that as a great opportunity. But also the aperture of the field of computer science is changing. So it's not, there are some areas that frankly, women are better than men at in my opinion. In my opinion, might get some crap for that. But the point, I do believe that. And there are different roles. So I think it's not just, there's so much more here. >> Oh, that's what I try to tell people. It's not just coding, right. There's so many different types of roles. And unfortunately I think we don't market ourselves well. So I encourage everyone out there that knows somebody. (Beth laughs) Who's looking-- >> If someone was provisioned Sun micro-systems, or mini computers, or workstations, probably has a systems background that could be a Cloud administrator or a Cloud architect. Same concepts. So I want to get your thoughts on women in tech since you're here. What's your thoughts on the industry, how's it going, things you advise, other folks, men and women, that they could do differently. Any good signs? What's your thoughts in general? >> Yeah so, first of all, I'm just a big advocate for women in general. Young girls, and, young women, just getting into the work force, and always have been. Have to say again, very fortunate early in my career working for companies like a phone company, and Schwab, we had so many amazing female leaders. And I don't even think we had a program, it was just sort of part of the DNA of the company. And it's really only in the last couple of years I really seen we have a big problem. Whether it's reading about some of the cultures of some of the big tech companies, or even spending more time in the valley. I think there's no one answer, it's multifaceted. It's education, it's families, it's you know, each one of us could make a difference in how we hire, sort of checking in what our unintended biases are, I know at Citi right now, there's a huge program around diversity and inclusion. Gender, and otherwise. And one of the ways I think it's going to be impactful. They've set targets that I know are controversial, but it holds people accountable, to make decisions and invest in developing people, and making sure there's a pipeline of talent that can step up into even bigger roles with a more diverse leadership team. It will take time though, it will take time. >> But mind shares are critical. >> It absolutely is. Self-awareness, community awareness, very much so. >> What can men do differently, it's always about women in tech, but what can we, what can men do? >> I think it's a great question. I would say, women can do this too. I hate when I see a group together, and it's all women working on the women issue. Shame on us, for not inviting men into the organization. And then I think it's similar to the Tech Whisperer. Don't be nervous, don't be worried, just step in. Because, you know, men are fathers, men are leaders, men are colleagues. They're brothers, they're uncles. We have to work on this together. >> I had a great guest, and friend, I was interviewing. And she was amazing, and she said, John, it's not diversity and inclusion, it's inclusion and diversity. It's I-N-D not D-I. First of all, I've never heard of it, what's D-N-I? My point exactly. Inclusion is not just the diversity piece, inclusion first is inclusive in general, diversity is different. So people tend to blend them. >> Yes they do. >> Or even forget the inclusion part. >> Final question, since you're a change junkie, which I love that phrase, I'm kind of one myself. Change junkies are always chasing that next wave, and you love waves. Pat Gelsinger at VMWare, wave junkie, always love talking with him. And he's a great wave spotter, he sees them early. There's a big set of waves coming in now, pretty clear. Cloud has done it's thing. It's only going to change and get bigger, hybrid, private, multi Cloud. Data, AI, twenty year cycle coming. What waves are you most excited about? What's out there? What waves are obvious, what waves aren't, that you see? >> Yeah, oh, that's a tough one. Cause we try to track what those waves are. I think one of the things that I'm seeing is that as we all get, and I don't just mean people, I mean things. Everything is connected, and everything has some kind of smarts, some kind of small CPU senser. There's no way that our existing, sort of network, infrastructure and the way we connect and talk can support all of that. So I think we're going to see some kind of discontinuous change, where new models are going to, are going to absolutely be required cause we'll sort of hit the limit of how much traffic can go over the internet, and how many devices can we manage. How much automation can the people and an enterprise sort of oversee and monitor, and secure and protect. That's the thing that I feel like it's a tsunami about to hit us. And it's going to be one of these perfect storms. And luckily, I think there is innovation going on around 5G and edge computing, and different ways to think about securing the enterprise. That will help. But it couldn't come soon enough. >> And model also meaning not just technical business. >> Absolutely. Machine the machine. Like who's identity is on there that's taken an action on your behalf, or the companies behalf. You know, we see that already with RPA, these software robots. Who's making sure that they're doing what they're suppose to do. And they're so easy to create, now you have thousands of them. In my mind, it's just more software to manage. >> And a great contrary to Carl Eschenbach, former VMware CEO now at Sequoia, he's on the board of UIPath, they're on the front page of Forbes today, talking about bots. >> Yes, yes, yes, I've heard them speak. >> This is an issue, like is there a verification. Is there a fake bots coming. If there's fake news, fake bots are probably going to come too. >> Absolutely they will. >> This is a reality. >> And we're putting them in the hands of non-engineers to build these bots. Which there's good and bad, right. >> Regulation and policy are two different things, and they could work together. This is going to be a seminal issue for our industry. Is understanding the societal impact, tech for good. Shaping the technologies. This is what a Tech Whisperer has to do. You have a tough job ahead of you. >> But I love it. >> Jeff: Beth thank you for coming on. >> Thank you for having me. >> I'm Jeff Furrier for the People First Network here at Sand Hill Road at Mayfield as part of theCUBE and SiliconANGLE's co-creation with Mayfield Fund, thans for watching.

>> Narrator: From Sand Hill Road, in the heart of Silicon Valley, it's theCUBE, presenting the People First Network, insights from entrepreneurs and tech leaders. >> Hello and welcome to a special Cube conversation, I'm John Furrier with theCUBE. We're here at Mayfield Fund on Sand Hill Road, Venture Cap for investing here for the People First co-created production by theCube and Mayfield. Next to us, Phil Finucane who's the former CTO of Express Scripts as well as a variety of other roles. Went to Stanford, Stanford alum. >> Mm hmm. >> Good to see you, thanks for joining me for this interview. >> Thank you, thank you for having me. >> So, before we get into some of the specifics, talk about your career, you're a former CTO of Express Scripts >> Yep. >> What are some of the other journeys that you've had? Talk about your roles. >> Yeah, I've had sort of a varied career. I started off as just a computer coder for a contract coder in the mid-90s. I sort of stumbled into it, not because I had a computer science background, but because when you start coding, sort of for fun in Silicon Valley in the mid-90s, there are just lots of jobs and I was lucky to have great mentors along the way. In 2003, I joined Yahoo and came in as the lead engineer, sort of the ops guy and the build and release guy for the log in and registration team at Yahoo, so I learned how to, went from being just a coder to being somebody who know how to run and build big systems and manage them all around the world. That was in the day when everything was bare metal and I could go to a data center and actually look at my machine and say, "Wow, that one's mine," right? And you know, sort of progressed from there to being the architect by the time that I left for some of the big social initiatives at Yahoo. On my way out, the YOS, the initiative to try to build Facebook in I think 2007, 2008 to try to take them on. That didn't work out too well, but it was definitely a formative experience in my career. From there I went to Zynga, where I was the CTO for Farmville. Was really, really good at getting middle-aged women in the Midwest to come play our game, and you know, was there for >> And it was highly, >> About three years >> high growth, Farmville >> Huge growth >> Took off like a rocket ship. >> Yeah, you know, over the 10 quarters I worked on the game we had over a billion dollars in revenue and that was, you know, the Zynga IPO'd on the back of that, right? And we weren't the only game, but we were certainly >> That was one of the big games >> The big whale, us and poker were the two that really drove the value in Zynga at that point. After that, I went to American Express, where I worked in a division that sort of sat off on the side of American Express focusing on stored value products. I was the chief architect for that division. Stored value products and international currency exchange. So, you know, at one point, I was in charge of both a pre-paid platform and American Express's traveler's checks platform, believe it or not, a thing that still exists. Although it's not heavily used any more. And you know, finally, I went to Express Scripts, where I spent the last three years as the CTO for that org. >> It's interesting, you've got a very unique background, because you know, you've seen the web scale, talk about bare metal Yahoo days, I mean, I remember those days vividly, you know, dealing with database schemas, I mean certainly the scale of Yahoo front page, never mind the different services that they had, which by the way, silo-like, they had databases >> Very, oh totally >> So building a registration and identity system must've been like, really stitching together a core part of Yahoo, I mean, what a Herculean task that must've been. >> Yeah, it was a lot of fun. I learned a lot, you know, we, it was my first experience in figuring out how to deal with security around the web. You know, we had, at the beginning, some vulnerabilities here and there, as time went on, our standards around interacting around the web got better and better. Obviously, Yahoo has run into trouble around that in subsequent years, but it was definitely a big learning experience, being involved in you know, the development of the OAuth 2.0 spec and all of that, I was sort of sitting there advising the folks who were, you know, in the middle of that, doing all the work. >> And that became such a standard as we know, tokens, dealing with tokens and SAS. Really drove a lot of the SAS mobile generation that did cloud, which becomes kind of that next generation so you had, you know Web 1.0, Web 2.0, then you had the cloud era, cloud 2.0, now they're goin' DevOps and apps. I want to get your thought, and you throw crypto in there just for fun, of dealing with blockchain and then token economics and new kinds of paradigms are coming online >> It's amazing how far we've come in those years, right? I mean I look at the database that was built inside of Yahoo and this predated me, you know, this was back to circa 1996, I think, but you know, big massively scalable databases that were needed just because the traditional relational database just wouldn't work at that scale, and Yahoo was one of the first to sort of discover that. And now you look at the database technologies that are out there today that take some of those core concepts and just extend them so much further and they're so much easier to access, to use, to run, operate, all of those things than back in the days of Yahoozle, UDB, and it's amazing just to see how far we've come. >> Phil, I want to get your thoughts, because you know, talking about Yahoo and just your experiences and even today, at that time it was like changing the airplane's engine at 35,000 feet, it's really difficult. A lot of corporate enterprises right nhow are having that same kind of feeling with digital, and digital transformation, I'd say it's a cliche, but it is true this impact, the role of data that's playing and the just for value creation but also cybersecurity could put a company out of business, so there's all kinds of looming things that are opportunities and challenges, that are sizable, huge tasks that was once regulated to the full stack developers and the full web scalers, now the lonely CIO with the anemic enterprise staff has to turn around on a dime. Staff up, build a stack, build commodity, scale out, this is pretty massive, and not a lot of people are talking about this. What's your view on this? Because this is super important. >> Yeah it is, and you know, so I had kind of a shock, moving from working my whole career here on Silicon Valley and then going to American Express, which you know, is very similar in a lot of ways to Express Scripts, and the sort of corporate mindset around, "What is technology?" There is this notion that everything is IT and here in the valley, IT is you know, internal networks and laptops and those sorts of things, the stuff that's required to make your enterprise run internally. Their IT is all of your infrastructure, right? And IT is a service organization, it's not the competitive advantage in your industry, right? And so both of the places that I've gone have had really forward-thinking leaders that have wanted to change the way that their enterprise operates around technology, and move away from IT but, to technology, to thinking about engineering as a core competency. And that's a huge change, not only for the CIO >> You're saying they did have that vision >> They had the vision, but they didn't know how to get there, so my charter coming in and you know, others who were on the teams around me, our charter was to come in and help build a real engineering organization as opposed to an IT org that's very vendor-oriented, you know, that's dependent on third parties to tell you the right thing or the wrong thing, you know that hires consultants to come in and help set up architecture standards, because we couldn't do that on our own, we're not the experts on this side. You know, that's sort of the mindset in many old school companies, right? That needs, that I think needs to change. This notion that software is eating the world is still not something that people have gotten their heads around in many companies, right? >> And data's washing out old business models, so if software's eating the world, data's the tsunami that's coming in and going to take out the beach and the people there. >> Right. And so it's like, all of these things, it's one thing for, you know, a forward-thinking CEO like Tim Wentworth at Express Scripts, who was responsible for bringing me and the group in, you know, those kinds of folks, it's one thing to know that you have to make that transition it's another thing to have a sense of what that means for an engineering team, and all the more for the rest of the organization to be able to get behind it. I mean, people you know, I don't know any number of business partners who've been used to, just sort of taking a spec, throwing it over the wall, and saying, "Come back to me in two years when you're done." That's not how effective organizations work around technology. >> Let's drill into that, because one of the things that's cultural, I mean I do some of the interviews of theCUBE, I talk to leaders all the time like yourself, the theme keeps coming back, it's culture, it's process, technology, all those things you talk about, but culture is the number one issue people point to, saying, "That's the reason why "something did or didn't happen." >> Correct. >> So, you talk about throwing it over the fence, that's waterfall, so you think about the old waterfall methodology, agile, well documented, but the mindset of product thinking is a really novel concept to corporate America Not to Silicon Valley, and entrepreneurs, they got to launch a product, not roll out SAP over two years, right, or something they used to be doing. So that's a cultural mindset shift. >> It's difficult for folks, even if they want to get on board to come along some of the time. One of the real big successes we had early on at Express Scripts was, you know, transitioning our teams to Agile wasn't difficult, what was difficult was getting business partners to sort of come along and be actively engaged in that product development mindset and lifecycle and all those sorts of things. And you know, we had one partner in particular, we were migrating from a really old, really clunky customer care application that you know had taken years and years to build, took on average, a new agent took six weeks to get trained on it because it was so complex and it's Oracle Forms and you know, every field in the database was a field on this thing, and there were green screens to do the stuff that you couldn't do in Oracle Forms, so and we wanted to rebuild the application. We tried to get them to come along and say, "Okay, we're going to do it in really small chunks," but business partners were like, "No, we can't afford "to have our agents swiveling between two applications." And so finally after we got our first sort of full-feature complete, we begged to go into a call center, you know with our business partners, and sit down with a few agents and just have them use it and see if it looked like it worked, if it did the right thing, and it was amazing seeing the business partner go, over the course of an hour, from "I can't be engaged in this, "I don't want an agent swiveling, "I don't want to be, you know, delivering partial applications "I want the whole thing." to, "Oh my god, it works way better, "the design is much nicer, the agents seem to like it," you know, "Here are the next things we should work on, "These are the things we got wrong." They immediately pivoted, and it wasn't, it was because they're the experts, they know how to run their business, they know what's important in their call centers, they know what their agents need, and they had just never seen the movie before, they just had no concept you could work that way. >> So this is actually interesting, 'cause what you're saying is, a new thing, foreign to the business partners, the tech team's on board, being Agile, building product, they have to, they can't just hear the feature benefits, they got to feel it. >> Yeah, they have to see it >> This seems to be the experience of success before they can move. Is that a success you think culturally, something that people have to be mindful of? >> It's absolutely something you have to be mindful of. And that was just the first step down the path. I mean, that team made a number of mistakes that folks here I think in the valley wouldn't normally make, you know. Over-committing and getting themselves into deep water by trying to get too much done and actually getting less accomplished in the process because of it and you know, the engagement around using data to actually figure out what's the next feature that we build. When you've got this enormous application to migrate, you should probably have some insight as to you know, feature by feature, what are you going to work on next? And that was a real challenge, 'cause there's a culture of expertise-driven, you know being subject-matter driven, expertise driven as opposed to being data driven about how do you >> Let's talk about data-driven. We had an interview earlier this morning with another luminary here at the Mayfield 50th conference celebration that they're having, and he said, "Data is the new feedback mechanism." and his point was, is that if you treat the Agile as an R&D exercise from a data standpoint. Not from a product but get it out there, get the data circulating in, it's critical in formulation of the next >> It is, yeah, it's absolutely critical. That was the eye opener for me going to Zynga. Zynga had an incredible, probably still does have, an incredible product culture that every single thing gets rolled out behind an experiment. And so you know, that's great from an operational perspective, because it allows you to, you know, move quickly and roll things out in small increments and when it doesn't work, you can just shut it off but it's not some huge catastrophe. But it's also critical because it allows you to see what's working and what's not and the flip side of that is, some humility of the people developing the products that their ideas are not going to work sometimes just because you know this domain well doesn't mean that you're necessarily going to be the expert on exactly how everything is going to play out. And so you have to have this ability to go out, try stuff, let it fail, use that, hopefully you fail quickly, you learn what's not working and use that to inform what's the next step down the path that you take, right? And Agile plays into it, but that's for me, that's the big transition that corporations really have to struggle with, and it's hard. >> You know you're, been there done that, seen multiple waves of innovation, want to bring up something to kind of get you going here. You see this classically in the old school 90s, 80s day. Product management, product people and sales people. They're always buttin' heads, you know? Product marketing, marketing people want this sales and marketing want this, product people buttin' heads, but now with Agile, the engineering focus has been the front lines. People are building engineering teams in house. They're building custom stacks for whatever reasons, the apps are getting smarter. The engineers are getting closer to the edge, the customer if you will. How do you help companies, or how do you advise companies to think about the relationship between a product-centric culture and a sales-centric culture? Because sometimes you have companies that are all about the customer-centric, customer-centric customer-centric, product-centric and sometimes if you try to put 'em together there's always going to be an alpha-beta kind of thing there and that's the balance in this. What's your take on this? Seems to be a cutting edge topic >> Yeah, well, so you know, one of the last big initiatives that I worked on at Express Scripts. Express Scripts has the, to my knowledge, the largest automated home delivery pharmacy in the world. It's amazing if you walk into one of our pharmacies where automation is packaging and filling prescriptions and packaging and shipping and doing all of that stuff. And we've built so much efficiency into the process that we've started getting slack in the system. Every year, you're trying to figure out how to make something work better and you know, have better automation around it. And so, you know, what do you do with all of that slack? The sales team can't sign up enough new customers for Express Scripts to actually fill that capacity. And so they create a division of commoditizing this, basically white labeling your pharmacy. We called it Pharmacy as a Platform, exposing APIs to third parties who might want to come along and hey, Phil's pharmacy can now fill branded prescriptions to get sent to you in your home, right? And so that's a fantastic vision, but there's a real struggle between engineering who had all these legacy stacks that we needed to figure out how to move to be able to really live up to this, you know the core of Express Scripts was our members and not somebody else's members. And so there's a lot of rewiring at the core that needs to be done. An operations team, a product team that's, you know, running these home delivery pharmacies, and a sales team that wants to go off and sell all over the place, right? And so, you know, early on, we started off and the sales team tried to sell, like six different deals that all required different parts of the vision, but you know, they weren't really, there was no real roadmap to figure out how do you get from where we're at to the end, and we could've done any of those things, but trying to do them all at once was going to be a trainwreck. And so, you know, we stubbed our toes a couple of times along the way, but I think it just came down to having a conversation and trying to be as transparent as possible on all sides, in all sides. To you know, try to get to a place where we could be effective in delivering on the vision. The vision was right. Everybody was doing all of the right things. But if you haven't actually, with so much of this stuff, if you haven't seen the movie, if you haven't worked this way before, there's nothing I can tell you that's going to make it work magically for you tomorrow. You have to just get this together and work in small increments to figure out how to get there. >> You got to go through spring training, you got to do the reps. >> Yep, absolutely. >> All right, so on your career, as you look at what you've done in your career, and what people outside are looking at right now, you got startups trying to compete and get a market position. You have other existing suppliers who could be the old guard, retooling and replatforming, refactoring, whatever the buzz word you want to use. And then the ultimate customer who wants to consume and have the ability of having custom personalization, data analytics, unlimited elastic capability with resources for their solution. How, what advice would you give to the startup, to the supplier, and to the customer to survive this next transition of cloud 2.0, you know and data tsunami, and all the opportunities that are coming? Because if they don't, they'll be challenged a startup goes out of business, a supplier gets displaced. >> Right, I mean, well, so the startup, I don't know if I have good advice for the startup. Startups in general have to find a market that actually works for them. And so, you know, I don't know that I've got some secret key that allows startups to be effective other than don't run out of money, try to figure out how to build effectively to get you to the point where you're, you know, where you're going to win. One of my earliest, one of the earliest jobs I had in my career, I came into a startup, and I tried, one of the founders had written the initial version of the code base. I, as a headstrong engineer, was convinced that he had done horrible work, and so I sort of holed up for like, six to eight weeks doing a hundred hours a week trying to rewrite the entire code base while getting nothing done for the startup. You know, in the end, that was the one job I've ever been fired from, and I should've been fired, because, you know, honestly as a startup, you shouldn't worry about perfection from an engineering perspective. You should figure out how to try to find your marketplace. Everybody has tech debt, you can fix that as time goes on, the startup needs to figure out how to be viable more than anything else. As far as suppliers go, you know, I don't know it's interesting the, you know, I sort of look at corporate America and there are many many companies that really rely heavily on their vendors to tell them how to do things. They don't trust in their own internal engineering ability. And then there are the ones, like the teams I have built at AmEx and Express Scripts that really do want to learn it all and be independent. I would say, identify when you walk into somebody's shop which they are and sell to them appropriately. You know, I've been a Splunk customer for a long time, I love Splunk. But the Splunk sales team early on at Express Scripts tried to come in and sell me on a whole bunch of stuff that Splunk was just not good at, right? >> And you knew that. >> And I knew that, because I've been a hands-on customer every since Zynga, right? I know what it's good at, and I love it as a tool, but you know, it's not the Swiss Army knife. It can't do everything. >> Well now you got Signal FX, so now you can get the observability you need. >> Exactly, right? So yeah, I, you know, I would say, you know, for those kinds of companies, it's important to go in and understand what your customer is, you know, what your customer is asking for and respond to them appropriately. And in some cases, they're going to need your expertise, either because they're building towards it or they haven't gotten there yet, and some cases, one of the things that I have done with teams of mine in the past, was it with AppDynamics at Express Scripts, excuse me at AmEx, five or six years ago, they were sold on, you know, bringing in AppDynamics as a monitoring tool, I actually made them not bring it in, because they didn't know what they didn't know. I made them go build some basic monitoring, you know, using some open source tools, just to get some background, and then, you know, once they did, we ended up bringing AppDynamics in, but doing it in a way that they were accretive to what we were trying to accomplish and not just this thing that was going to solve all of our problems. >> And so that brings up the whole off-the-shelf general purpose software model that you were referring to. The old model was lean on your vendors. They're supplying you, and because you don't have the staff to do it yourself. That's changing, do you think that's changing? >> It is, it's changing, but again, I think there's a lot of places where people nominally want to go there, but don't know how to get there, and so, you know, people are stubbing their toes left and right. If you're doing it with this mindset of, we're constantly getting better and we're learning and it's okay to make mistakes as long as we move forward, >> It's okay to stub your toe as long as you don't cut an artery open. >> Yeah, that's true, yeah exactly >> You don't want to bleed out, that's a cybersecurity hack >> That's true, that's true. But for me a lot of the time that just comes down to how long are you waiting before you stub your toe? If you're, you know, if you wait two years before you actually try to launch something, the odds of you cutting your leg off are much higher than >> Well I want to get into the failure thing, so I think stubbing your toe brings up this notion of risk management, learning what to try, what not to do, take experiments to try to your, which is a great example. Before you get there, you mentioned suppliers. One of the things we hear and I want to get your thoughts on, is that, a lot of CIOs and C-sos, and CBOs, or whatever title is the acronym, they're trying to reduce the number of suppliers. They don't want more tools, right? They don't necessarily want another tool for the tool's sake or they might want to replatform, what does that even mean? So, we're hearing in our interviews and our discussions with partitioners, "Hey, I want to get my suppliers down, "and by the way, I want to be API driven, "so I want to start getting to a mode "where I'm dictating the relationship to suppliers." How do you respond to that? Do you see that as aspirational, real dynamic, or fiction? >> It's a good goal to give motivation, I believe it. For me, I approach the problem a little differently. I'm a big believer, well, so, because I've seen this pattern of this next tool is going to be the one that consolidates three things and it's going to be the right answer and instead of eliminating three and getting down to one, you have four, because you're, you need to unwire this new thing, there's a lot of time and effort required to get rid of, you know, your old technology stack, and move to the new one, right? I've seen that especially coming from the C-Sec for Express Scripts is an amazing guy, and you know, was definitely trying to head down that path but we stubbed our toes, we ran into problems in trying to figure out, you know, how do you move from one set of networking gear to the next set? How do you deal with, you know, all of the virus protection and all the other, there's a huge variety of tools. >> So it's not just technical debt, it's disruption >> It's disruption to the existing stack, and you've got to move from old to new, so my philosophy has always been, with technical debt, when you're in debt, and I think technical debt really does operate in a lot of ways like real debt, right? Probably good to have some of it. If you're completely debt-free, that's I've never been in that place before. >> You're comfortable. You might not be moving, >> Exactly, right? But with that technical debt, you know, there's two ways to pay down your debt. You can scrimp and save and put more money into debt principal payments as opposed to spending on other new things, or, well and/or, build productive capacity. So a huge focus for me for the engineering teams that we've built, and this is not anything new to the folks in this area, but, you know, always think about an arms race, where you're getting 1% better every day. The aggregation of marginal gains and investing in internal improvements so that your team is doubling productivity every year, which is something that's really possible for, you know, some of these engineering organizations, is the way that you deal with that, right? If you get to the point where your team is really, really productive, they can go through and eliminate all the old legacy technology. >> That's actually great advice, and it's interesting, because a lot of people just get hung up on one thing. Operating something, and then growing something, and you can have different management styles and different techniques for both, the growth team, the operating team. You're kind of bringing in and saying, we can do both. Operate with growth in mind, to 1% better approach. >> Right, you know, and for me, it's been an interesting journey, you know. I started off as the engineer and then the architect, who was always focused on just the technology, the design of the system in production. Sort of learned from there that you had to be good at the you know, all the systems that get code from a developer's desktop into production, that's a whole interrelated system that's not isolated from your production system. And then from there, it has to be the engineering team that you build has to be effective as well. And so, I've moved from being very technology-centric to somebody who says, "Okay, I have to start "with getting the team right "and getting the culture right if we're ever going to "be able to get the technology to a good place." Mind you, I still love the technology. I'm still an architect at my core, but I've come to this realization that good technology and bad teams will get crushed by bad technologies and good teams. Because now I've seen that a couple of places, where you have old but evolving technology stacks that have gone from low availability and poor performance and low ability to get new features into production to a place where you're fixing all of that at a high rate. It starts with the team. >> You're bringing us some core Silicon Valley ethos to the IT conversation, because what you're talking about is "I'll fund an A team with a B plan any day "over a B team with an A plan." >> Right. >> And where this makes sense, I think is true, is that to your point about debt, A teams know how to manage it. >> Yeah. >> So this is kind of what you're getting at here. >> Right. >> You can take that same ethos, so it's the Agile enterprise. >> Yeah, it is >> That's what we're talking about. Okay, so hypothetical final point I want to chat with you about. Let's just say you and I were startin' a company. We're chief architects, you're the chief architect, I'm a coder, what are we doing? Do I code from horizontally scalable cloud, certainly cloud native, how would you think about building, we have an app in mind, all of our requirements defined, it's going to be data-centric, it's going to be game change and have community, it might have some crypto in there, who knows, but it's going to be fun. How do we scale this out to be really fast? How would you architect this? >> Yeah, well, you know, I do start in the cloud. I go to AWS or Azure or any of the offerings that are out there, and you know, leverage everything that they have that's already wired up already for you. I mean the thing that we've seen in the evolution of software and production systems over the last, well, forever, is you get more and more leverage every day, every year, right? And so, if you and I are startin' a new company, let's go use the tools that are there to do the things that we shouldn't be wasting our time on. Let's focus on the value for our company as much as we can. Don't over-architect. I think premature optimization is a thing that you know, I learned early on is a real problem. You should, you know >> Give an example, what that would look like. >> I've seen >> Database scale decisions done with no scale >> Correct, yeah, you know? You go off >> Let's pick this! It's the most scalable database, well we have no users yet. >> Right, you know you build the super complicated caching architecture or you know, you go design the most critical part of the system out of the gate, you know, using Assembly. You use C++ or, you use a low level language when a high level language with your three users would be just fine, right? You can get the work done in a fraction of the time. >> And get the business logic down, the IP, >> Solve the problem when it becomes a problem. Like, it's, you know, I've, any number of times, I've run into systems, I've built systems where you have some issue that you run into, and you have to go back and redesign some chunk of the system. In my experience, I'm really bad at predicting, and I think engineers are really bad at predicting what are going to be the problem areas until you run into them, so just go as simple as you can out of the gate, you know. Use as many tools as you can to solve problems that, you know, maybe as an engineer, I want to go rebuild every thing from scratch every time. I get the inclination. But it's >> It's a knee-jerk reaction to do that but you stay your course. Don't over-provision, overthink it, thus start taking steps toward the destination, the vision you want to go to, and get better, operate >> Solve the problem you have when it shows up. >> So growth mindset, execute, solve the problems when they're there. >> Right, and initially the problem that you have is finding a market, you know, not building the greatest platform in the world, right? >> Find a market, exactly. >> Right? >> Phil, thanks for taking the time >> Thank you very much, appreciate it. >> Appreciate the insights. Hey, we're here for the People First, Mayfield's 50th celebration, 50 years in business. It's a CUBE co-production, I'm John Furrier, thanks for watching >> Thanks John. (outro music)

>> Announcer: From Sand Hill Road in the heart of Silicon Valley, it's theCUBE, presenting the People First Network, insights from entrepreneurs and tech leaders. (bright electronic music) >> Everyone, welcome to this special CUBE conversation. We're here at Sand Hill Road at Mayfield Fund. This is theCUBE, co-creation of the People First Network content series. I'm John Furrier, host of theCUBE. Our next guest, Yuvi Kochar, who's the Data-centric Digital Transformation Strategist at GameStop. Variety of stints in the industry, going in cutting-edge problems around data, Washington Post, comScore, among others. You've got your own practice. From Washington, DC, thanks for joining us. >> Thank you, thanks for hosting me. >> This is a awesome conversation. We were just talking before we came on camera about data and the roles you've had over your career have been very interesting, and this seems to be the theme for some of the innovators that I've been interviewing and were on the People First is they see an advantage with technology, and they help companies, they grow companies, and they assist. You did a lot of different things, most notably that I recognized was the Washington Post, which is on the mainstream conversations now as a rebooted media company with a storied, historic experience from the Graham family. Jeff Bezos purchased them for a song, with my opinion, and now growing still, with the monetization, with subscriber base growing. I think they're number one in subscribers, I don't believe, I believe so. Interesting time for media and data. You've been there for what, how many years were you at the Washington Post? >> I spent about 13 years in the corporate office. So the Washington Post company was a conglomerate. They'd owned a lot of businesses. Not very well known to have owned Kaplan, education company. We owned Slate, we owned Newsweek, we owned TV stations and now they're into buying all kinds of stuff. So I was involved with a lot of varied businesses, but obviously, we were in the same building with the Washington Post, and I had front row seat to see the digital transformation of the media industry. >> John: Yeah, we-- >> And how we responded. >> Yeah, I want to dig into that because I think that illustrates kind of a lot what's happening now, we're seeing with cloud computing. Obviously, Cloud 1.0 and the rise of Amazon public cloud. Clearly, check, done that, a lot of companies, startups go there. Why would you provision a data center? You're a startup, you're crazy, but at some point, you can have a data center. Now, hybrid cloud's important. Devops, the application development market, building your own stack, is shifting now. It seems like the old days, but upside down. It's flipped around, where applications are in charge, data's critical for the application, infrastructure's now elastic. Unlike the old days of here's your infrastructure. You're limited to what you can run on it based on the infrastructure. >> Right. >> What's your thoughts on that? >> My thoughts are that, I'm a very, as my title suggests, data-centric person. So I think about everything data first. We were in a time when cloud-first is becoming old, and we are now moving into data-first because what's happening in the marketplace is the ability, the capability, of data analytics has reached a point where prediction, in any aspect of a business, has become really inexpensive. So empowering employees with prediction machines, whether you call them bots, or you call them analytics, or you call them machine learning, or AI, has become really inexpensive, and so I'm thinking more of applications, which are built data-out instead of data-in, which is you build process and you capture data, and then you decide, oh, maybe I should build some reporting. That's what we used to do. Now, you need to start with what's the data I have got? What's the data I need? What's the data I can get? We were just talking about, everybody needs a data monetization strategy. People don't realize how much asset is sitting in their data and where to monetize it and how to use it. >> It's interesting. I mean, I got my computer science degree in the 80s and one of the tracks I got a degree in was database, and let's just say that my main one was operating system. Database was kind of the throwaway at that time. It wasn't considered a big field. Database wasn't sexy at all. It was like, database, like. Now, if you're a database, you're a data guru, you're a rock star. The world has changed, but also databases are changing. It used to be one centralized database rules the world. Oracle made a lot of money with that, bought all their competitors. Now you have open source came into the realm, so the world of data is also limited by where the data's stored, how the data is retrieved, how the data moves around the network. This is a new dynamic. How do you look at that because, again, lagging in business has a lot to do with the data, whether it's in an application, that's one thing, but also having data available, not necessarily in real time, but if I'm going to work on something, I want the data set handy, which means I can download it or maybe get real-time. What's your thoughts on data as an element in all that moving around? >> So I think what you're talking about is still data analytics. How do I get insights about my business? How do I make decisions using data in a better way? What flexibility do I need? So you talk about open source, you think about MongoDB and those kind of databases. They give you a lot of flexibility. You can develop interesting insights very quickly, but I think that is still very much thinking about data in an old-school kind of way. I think what's happening now is we're teaching algorithms with data. So data is actually the software, right? So you get an open source algorithm. I mean Google and everybody else is happy to open source their algorithms. They're all available for free. But what, the asset is now the data, which means how you train your algorithm with your data, and then now, moving towards deploying it on the edge, which is you take an algorithm, you train it, then you deploy it on the edge in an IoT kind of environment, and now you're doing decision-making, whether it's self-driving cars, I mean those are great examples, but I think it's going down into very interesting spaces in enterprise, which is, so we have to all think about software differently because, actually, data is a software. >> That's an interesting take on it, and I love that. I mean I wrote a blog post in 2007 when we first started playing with the, in looking at the network effects on social media and those platforms was, I wrote a post, it was called Data is the New Development Kit. Development kit was what people did back then. They had a development kit and they would download stuff and then code, but the idea was is that data has to be part of the runtime and the compilation of, as software acts, data needs to be resident, not just here's a database, access it, pull it out, use it, present it, where data is much more of a key ingredient into the development. Is that kind of what you're getting at? >> Yes. >> Notion of-- >> And I think we're moving from the age of arithmetic-based machines, which is we put arithmetic onto chips, and we then made general-purpose chips, which were used to solve a huge amount of problems in the world. We're talking about, now, prediction machines on a chip, so you think about algorithms that are trained using data, which are going to be available on chips. And now you can do very interesting algorithmic work right on the edge devices, and so I think a lot of businesses, and I've seen that recently at GameStop, I think business leaders have a hard time understanding the change because we have moved from process-centric, process automation, how can I do it better? How can I be more productive? How can I make better decisions? We have trained our business partners on that kind of thinking, and now we are starting to say, no, no, no, we've got something that's going to help you make those decisions. >> It's interesting, you mentioned GameStop. Obviously, well-known, my sons are all gamers. I used to be a gamer back before I had kids, but then, can't keep up anymore. Got to be on that for so long, but GameStop was a retail giant in gaming. Okay, when they had physical displays, but now, with online, they're under pressure, and I had interviewed, again, at an Amazon event, this Best Buy CIO, and he says, "We don't compete with price anymore. "If they want to buy from Amazon, no problem, "but our store traffic is off the charts. "We personalize 50,000 emails a day." So personalization became their strategy, it was a data strategy. This is a user experience, not a purchase decision. Is this how you guys are thinking about it at GameStop? >> I think retail, if you look at the segment per se, personalization, Amazon obviously led the way, but it's obvious that personalization is key to attract the customer. If I don't know what games you play, or if I don't know what video you watched a little while ago, about which game, then I'm not offering you the product that you are most prone or are looking for or what you want to buy, and I think that's why personalization is key. I think that's-- >> John: And data drives that, and data drives that. >> Data drives that, and for personalization, if you look at retail, there's customer information. You need to know the customer. You need to know, understand the customer preferences, but then there's the product, and you need to marry the two. And that's where personalization comes into play. >> So I'll get your thoughts. You have, obviously, a great perspective on how tech has been built and now working on some real cutting-edge, clear view on what the future looks like. Totally agree with you, by the way, on the data. There's kind of an old guard/new guard, kind of two sides of the street, the winners and the losers, but hey, look, I think the old guard, if they don't innovate and become fresh and new and adopt the modern things that need to attract the new expectations and new experiences from their customers, are going to die. That being said, what is the success formula, because some people might say, hey, I'm data-driven. I'm doing it, look at me, I'm data. Well, not really. Well, how do you tell if someone's really data-driven or data-centric? What's the difference? Is there a tell sign? >> I think when you say the old guard, you're talking about companies that have large assets, that have been very successful in a business model that maybe they even innovated, like GameStop came up with pre-owned games, and for the longest of times, we've made huge amount of revenue and profit from that segment of our business. So yes, that's becoming old now, but I think the most important thing for large enterprises at least, to battle the incumbent, the new upstarts, is to develop strategies which are leveraging the new technologies, but are building on their existing capability, and that's what I drive at GameStop. >> And also the startups too, that they were here in a venture capital firm, we're at Mayfield Fund, doing this program, startups want to come and take a big market down, or come in on a narrow entry and get a position and then eat away at an incumbent. They could do it fast if they're data-centric. >> And I think it's speed is what you're talking about. I think the biggest challenge large companies have is an ability to to play the field at the speed of the new upstarts and the firms that Mayfield and others are investing in. That's the big challenge because you see this, you see an opportunity, but you're, and I saw that at the Washington Post. Everybody went to meetings and said, yes, we need to be digital, but they went-- >> They were talking. >> They went back to their desk and they had to print a paper, and so yes, so we'll be digital tomorrow, and that's very hard because, finally, the paper had to come out. >> Let's take us through the journey. You were the CTO, VP of Technology, Graham Holdings, Washington Post, they sold it to Jeff Bezos, well-documented, historic moment, but what a storied company, Washington Post, local paper, was the movie about it, all the historic things they've done from a reporting and journalism standpoint. We admire that. Then they hit, the media business starts changing, gets bloated, not making any money, online classifieds are dying, search engine marketing is growing, they have to adjust. You were there. What was the big, take us through that journey. >> I think the transformation was occurring really fast. The new opportunities were coming up fast. We were one of the first companies to set up a website, but we were not allowed to use the brand on the website because there was a lot of concern in the newsroom that we are going to use or put the brand on this misunderstood, nearly misunderstood opportunity. So I think it started there, and then-- >> John: This is classic old guard mentality. >> Yes, and it continued down because people had seen downturns. It's not like media companies hadn't been through downturns. They had, because the market crashes and we have a recession and there's a downturn, but it always came back because-- >> But this was a wave. I mean the thing is, downturns are economic and there's business that happens there, advertisers, consumption changes. This was a shift in their user base based upon a technology wave, and they didn't see it coming. >> And they hadn't ever experienced it. So they were experiencing it as it was happening, and I think it's very hard to respond to a transformation of that kind in a very old-- >> As a leader, how did you handle that? Give us an example of what you did, how you make your mark, how do you get them to move? What were some of the things that were notable moments? >> I think the main thing that happened there was that we spun out washingtonpost.com. So it became an independent business. It was actually running across the river. It moved out of the corporate offices. It went to a separate place. >> The renegades. >> And they were given-- >> John: Like Steve Jobs and the Macintosh team, they go into separate building. >> And we were given, I was the CTO of the dotcom for some time while we were turning over our CTO there, and we were given a lot of flexibility. We were not held accountable to the same level. We used the, obviously, we used-- >> John: You were running fast and loose. >> And we were, yes, we had a lot of flexibility and we were doing things differently. We were giving away the content in some way. On the online side, there was no pay wall. We started with a pay wall, but advertising kind of was so much more lucrative in the beginning, that the pay wall was shut down, and so I think we experimented a lot, and I think where we missed, and a lot of large companies miss, is that you need to leave your existing business behind and scale your new business, and I think that's very hard to do, which is, okay, we're going to, it's happening at GameStop. We're no longer completely have a control of the market where we are the primary source of where, you talk about your kids, where they go to get their games. They can get the games online and I think-- >> It's interesting, people are afraid to let go because they're so used to operating their business, and now it has to pivot to a new operating model and grow. Two different dynamics, growth, operation, operating and growing. Not all managers have that growth mindset. >> And I think there's also an experience thing. So most people who are in these businesses, who've been running these businesses very successfully, have not been watching what's happening in technology. And so the technology team comes out and says, look, let me show you what we can do. I think there has to be this open and very, very candid discussion around how we are going to transform-- >> How would you talk about your peer, developed peers out there, your peers and other CIOs, and even CISOs on the security side, have been dealing with the same suppliers over, and in fact, on the security side, the supplier base is getting larger. There's more tools coming out. I mean who wants another tool? So platform, tool, these are big decisions being made around companies, that if you want to be data-centric, you want to be a data-centric model, you got to understand platforms, not just buying tools. If you buy a hammer, they will look like a nail, and you have so many hammers, what version, so platform discussions come in. What's your thoughts on this? Because this is a cutting-edge topic we've been talking about with a lot of senior engineering leaders around Platform 2.0 coming, not like a classic platform to... >> Right, I think that each organization has to leverage or build their, our stack on top of commodity platforms. You talked about AWS or Azure or whatever cloud you use, and you take all their platform capability and services that they offer, but then on top of that, you structure your own platform with your vertical capabilities, which become your differentiators, which is what you take to market. You enable those for all your product lines, so that now you are building capability, which is a layer on top of, and the commodity platforms will continue to bite into your platform because they will start offering capabilities that earlier, I remember, I started at this company called BrassRing, recruitment automation. One of the first software-as-a-service companies, and I, we bought a little company, and the CTO there had built a web server. It was called, it was his name, it was called Barrett's Engine. (chuckles) And so-- >> Probably Apache with something built around it. >> So, in those days, we used to build our own web servers. But now today, you can't even find an engineer who will build a web server. >> I mean the web stack and these notions of just simple Web 1.0 building blocks of change. We've been calling it Cloud 2.0, and I want to get your thoughts on this because one of the things I've been riffing on lately is this, I remember Marc Andreessen wrote the famous article in Wall Street Journal, Software is Eating the World, which I agree with in general, no debate there, but also the 10x Engineer, you go into any forum online, talking about 10x Engineers, you get five different opinions, meaning, a 10x Engineer's an engineer who can do 10 times more work than an old school, old classical engineer. I bring this up because the notion of full stack developer used to be a real premium, but what you're talking about here with cloud is a horizontally scalable commodity layer with differentiation at the application level. That's not full stack, that's half stack. So you think the world's kind of changing. If you're going to be data-centric, the control plane is data. The software that's domain-specific is on top. That's what you're essentially letting out. >> That's what I'm talking about, but I think that also, what I'm beginning to find, and we've been working on a couple of projects, is you put the data scientists in the same room with engineers who write code, write software, and it's fascinating to see them communicate and collaborate. They do not talk the same language at all. >> John: What's it like? Give us a mental picture. >> So a data scientist-- >> Are they throwing rocks at each other? >> Well, nearly, because the data scientists come from the math side of the house. They're very math-oriented, they're very algorithm-oriented. Mathematical algorithms, whereas software engineers are much more logic-oriented, and they're thinking about scalability and a whole lot of other things, and if you think about, a data scientist develops an algorithm, it rarely scales. You have to actually then hand it to an engineer to rewrite it in a scalable form. >> I want to ask you a question on that. This is why I got you and you're an awesome guest. Thanks for your insights here, and we'll take a detour into machine learning. Machine learning really is what AI is about. AI is really nothing more than just, I love AI, it gets people excited about computer science, which is great. I mean my kids talk about AI, they don't talk about IoT, which is good that AI does that, but it's really machine learning. So there's two schools of thought on machine. I call it the Berkeley school on one end, not Berkeley per se but Berkeley talks about math, machine learning, math, math, math, and then you have other schools of thought that are on cognition, that machine learning should be more cognitive, less math-driven, spectrum of full math, full cognition, and everything in between. What's your thoughts on the relationship between math and cognition? >> Yeah, so it's interesting. You get gray hair and you kind of move up the stack, and I'm much more business-focused. These are tools. You can get passionate about either school of thought, but I think that what that does is you lose sight of what the business needs, and I think it's most important to start with what are we here trying to do, and what is the best tool? What is the approach that we should utilize to meet that need? Like the other day, we were looking at product data from GameStop, and we know that the quality of data should be better, but we found a simple algorithm that we could utilize to create product affinity. Now whether it's cognition or math, it doesn't matter. >> John: The outcome's the outcome. >> The outcome is the outcome, and so-- >> They're not mutually exclusive, and that's a good conversation debate but it really gets to your point of does it really matter as long as it's accurate and the data drives that, and this is where I think data is interesting. If you look at folks who are thinking about data, back to the cloud as an example, it's only good as what you can get access to, and cybersecurity, the transparency issue around sharing data becomes a big thing. Having access to the data's super important. How do you view that for, as CIOs, and start to think about they're re-architecting their organizations for these digital transformations. Is there a school of thought there? >> Yes, so I think data is now getting consolidated. For the longest time, we were building data warehouses, departmental data warehouses. You can go do your own analytics and just take your data and add whatever else you want to do, and so the part of data that's interesting to you becomes much more clean, much more reliable, but the rest, you don't care much about. I think given the new technologies that are available and the opportunity of the data, data is coming back together, and it's being put into a single place. >> (mumbles) Well, that's certainly a honeypot for a hacker, but we'll get that in a second. If you and I were doing a startup, we say, hey, let's, we've got a great idea, we're going to build something. How would we want to think about the data in terms of having data be a competitive advantage, being native into the architecture of the system. I'll say we use cloud unless we need some scale on premise for privacy reasons or whatever, but we would, how would we go to market, and we have an app, as apps defined, great use case, but I want to have extensibility around the data, I don't want to foreclose any future options, How should I think about my, how should we think about our data strategy? >> Yes, so there was a very interesting conversation I had just a month ago with a friend of mine who's working at a startup in New York, and they're going to build a solution, take it to market, and he said, "I want to try it only in a small market "and learn from it," and he's going very old school, focus groups, analytics, analysis, and I sat down, we sat at Grand Central Station, and we talked about how, today, he should be thinking about capturing the data and letting the data tell him what's working and what's not working, instead of trying to find focus groups and find very small data points to make big decisions. He should actually utilize the target, the POC market, to capture data and get ready for scale because if you want to go national after having run a test in... >> Des Moines, Iowa. >> Part of New York or wherever, then you need to already have built the data capability to scale that business in today's-- >> John: Is it a SaaS business? >> No, it's a service and-- >> So he can instrument it, just watch the data. >> And yes, but he's not thinking like that because most business people are still thinking the old way, and if you look at Uber and others, they have gone global at such a rapid pace because they're very data-centric, and they scale with data, and they don't scale with just let's go to that market and then let's try-- >> Yeah, ship often, get the data, then think of it as part of the life cycle of development. Don't think it as the old school, craft, launch it, and then see how it goes and watch it fail or succeed, and know six months later what happened, know immediately. >> And if you go data-centric, then you can turn the R&D crank really fast. Learn, test and learn, test and learn, test and learn at a very rapid pace. That changes the game, and I think people are beginning to realize that data needs to be thought about as the application and the service is being developed, because the data will help scale the service really fast. >> Data comes into applications. I love your line of data is the new software. That's better than the new oil, which has been said before, but data comes into the app. You also mentioned that app throws off data. >> Yuvi: Yes. >> We know that humans have personal, data exhaust all the time. Facebook made billions of dollars on our exhaust and our data. The role of data in and out of the application, the I/O of the application, is a new concept, you brought that up. I like that and I see that happening. How should we capture that data? This used to be log files. Now you got observability, all kinds of new words kind of coming into this cloud equation. How should people think about this? >> I think that has to be part of the design of your applications, because data is application, and you need to design the application with data in mind, and that needs to be thought of upfront, and not later. >> Yuvi, what's next for you? We're here in Sand Hill Road, VC firm, they're doing a lot of investments, you've got a great project with GameStop, you're advising startups, what's going on in your world? >> Yes, so I'm totally focused, as you probably are beginning to sense, on the opportunity that data is enabling, especially in the enterprise. I'm very interested in helping business understand how to leverage data, because this is another major shift that's occurring in the marketplace. Opportunities have opened up, prediction is becoming cheap and at scale, and I think any business runs on their capability to predict, what is the shirt I should buy? How many I should buy? What color should I buy? I think data is going to drive that prediction at scale. >> This is a legit way that everyone should pay attention to. All businesses, not just one-- >> All businesses, everything, because prediction is becoming cheap and automated and granular. That means you need to be able to not just, you need to empower your people with low-level prediction that comes out of the machines. >> Data is the new software. Yuvi, thanks so much for great insight. This is theCUBE conversation. I'm John Furrier here at Sand Hill Road at the Mayfield Fund, for the People First Network series. Thanks for watching. >> Yuvi: Thank you. 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>> Announcer: From Sand Hill Road in the heart of Silicon Valley, it's "theCUBE," presenting the People First Network, insights from entrepreneurs and tech leaders. (upbeat electronic music) >> Hi, everyone, welcome to this special "CUBE" conversation. I'm John Furrier, co-host of "theCUBE" and co-founder of SiliconANGLE Media. We are on Sand Hill Road at Mayfield Fund, the venture capitalist funding startups. We're here with Tara Vaishnav, who is the vice president of technology, innovation, and advanced analytics at The Clorox Company, as part of the People First Network co-creation of content with SiliconANGLE and Mayfield. Tara, welcome. >> Well, thank you very much for having me! And congratulations to Mayfield on 50 amazing years, wow! >> 50 years they have been in Sand Hill Road, they've been investing in some great startups. They really have a great philosophy about people first. >> Yep. >> And you've had a very distinguished career in technology, IT, in big companies. Long tenures, too, like, you know, decades. >> Yes, oh, yes. >> And now at Clorox, a consumer company. So talk about your journey, where your experience is, where you started, tell us about your background. >> Yeah, well, I grew up in India, if it's not obvious already. I came to the United States after I finished my undergrad in India, I had an undergrad in electrical engineering. Came over here, got my electrical engineering master's at the University of Southern California, go Trojans. And after that, I worked for several companies, but mostly in health care and life sciences. So the past four years, I have been the vice president of IT at The Clorox Company, which is a CPG company, so quite a bit of a learning curve there. >> Health care, serving patients, now you're serving consumers. >> That's right, that's right. >> Clorox is well-known for their analytics, well-known for technology, innovation. >> Tara: Yes, yeah. >> I've interviewed a bunch of folks at Clorox, they've always been at the head of the curve. >> Tara: Yeah. >> Like Procter & Gamble, you guys, consumer companies have to be. >> Tara: Definitely. >> Now, more than ever, digital disruption is an opportunity for companies to have a better relationship with their customers. >> Tara: Absolutely. >> And changes the makeup of their brand as well, since it touches the customer. How do you see that evolving? What's the current state of the art of some of the things you're working on? >> Yeah, it's pretty fascinating, actually. And I hate to use cliches, but things like consumer experience is really at the heart of it. We're a brand company, at the end of the day, and how people feel about us is really, really important. It's not so much, it is about the products, and we make amazing products, but how do they feel about us as a company, and how do they engage with us differently than they did before? We do not buy the same way as we did even five years ago. And so, learning that, learning the new, evolving consumer, and getting really close to what's important to them, that's really on the forefront of how we think about our digital transformation. >> One of the cool things that's great about the People First Network that we've been doing-- >> Tara: Yeah. >> This content, is that we have a lot of luminaries who have had a storied career, like yourself, have looked at the changes and the waves of innovation that have come before, and now, more than ever, omnichannel, how you advertise and reach customers, how they interact, how they buy and consume. When you look at health care and some of the things you've been involved in, in the '90s, remember, client-server was big, they had computers. >> Tara: (laughs) Oh, yes. Oh, yeah. >> IT has changed a lot. >> It has. >> What is the most striking thing that you see from those changes in this new wave that we're living now? >> You know, so, (sharply exhales) I was fortunate in that I decided that data was where it was at, right from the beginning of my career. That's how I kind of made my way up my career ladder, is really that focus on data. I had a software engineering background, but really felt the power of data to change things. What has happened, if I think about some of the big changes, or the key milestones, if you will, in my career, one of the first real big changes came about when data, which was up until that point really sort of coming along for the ride, you had applications, applications had data, when data actually became the mainstay and the applications kind of came and went. I remember one of my mentors in the past, a past CIO, actually, telling me that applications come and go, but data is forever. And when that really started to become a thing was when big data and big data technologies became, came of enterprise age, if you will, along with cloud technologies. That marriage really, that was, I think, the tipping point where the things that you could do with data and the way that you could get insights from data really took on a life of its own, if you will. >> You know, one of the things, that's a great point. I'd love to get your insights as a leader and as you grew with data, because it wasn't really obvious at that time. Certainly, people had databases and that, the big data, the applications had data. >> Tara: Sure, sure, yeah. >> But it was always kind of old-school data. "Hey, get some data, let's look at the demographics, "let's look at the Consumer Price Index," blah, blah, blah, all kinds of data. But access to data became driven by the database. >> Tara: Correct. >> So there might've been data available-- >> Tara: Yeah. >> But getting it in the hands of the practitioners even now is hard, but even back then, you might not have had the data. So as a leader who's sought data-- >> Tara: Yeah. >> As a strategic advantage. By the way, that's rare early, isn't it? So, (laughs) awesome for you. >> You know, I got lucky. >> How did you get through that? How did you lead the organization to make data at the center of things? >> It is a very good question. There were a few things that started to take shape once big data and the marriage of the cloud started to happen. It started to open up doors, break down organizational silos. When you brought that data together, the business value, or the potential business value that could be unlocked, became obvious. The way that we approached it, though, under my leadership, I always believe in small steps. I believe in leapfrog, but I believe that you have to feed innovation or innovative thinking out in small doses. People are not always ready to consume it in one big (laughs) fell swoop, if you will. So doing things incrementally, but with an idea towards transformation, was, I think, the secret sauce that I used to approach these things. So as a couple of examples, in Kaiser Permanente, when I worked there for almost seven years, I was instrumental in bringing their big data platform to life. But it was not just a matter of, "Here's the technology "for technology's sake." It was a matter of, "Here are some real problems "that we are having a lot of difficulty in solving today. "Let's show you how we can solve those differently "in an amazing way." And we proved that. It was an experiment, that we proved that, and that really started to get us those adopters, if you will. >> John: So take baby steps. >> Yep. >> Don't try to do wholesale changes hardcore. >> Correct, correct. >> Let people get used to it. >> Yeah. >> This must've had an impact on culture. >> Yes, yes. >> And this comes up a lot in the DevOps culture we've seen in the past decade, even now. >> Yeah. >> Getting people to change has become very difficult. >> Yes! >> John: We all know that person-- >> Yes. >> Has their project that's their baby, adding features, "No, don't take my "baby away from me." >> Tara: Yes, yes, yes. >> "I don't want to change." >> (laughs) Oh, yeah. >> How do you make that happen? How do you lead people through that very difficult transformation at an emotional level, on a business level? What's the strategy there? What's your technique? >> Yeah, so, again, back to, you have to show results. And you have to show results incrementally in a way that people can appreciate them and consume them. You have to look at technology from a business value perspective. Business value comes first, technology is just along for the ride. That's how people see it, and that's how they should see it. >> John: Mm-hm. >> It's what you can do with the technology that makes a difference. So, some of the techniques that I have used in the past have been, number one, you do have to find like-minded people in the organization. You can't go at it alone. You have to start to build your clan, if you will, of innovators, so you've got a target audience that you're chippin' away at, slowly, but you've got to build credibility. Because results build credibility. Credibility builds trust. Trust removes barriers. So that's kind of the way that I approach things. I bring like-minded people together, I find people in the organization, of the people that are resistant, that I can bring onto "my side," if you will, and I use their knowledge, their insights, their knowledge of how this person who is obviously a stakeholder, and an important stakeholder, how they think and what's important to them, and I use that language and that person to be able to approach individuals in different ways. It's about culture. >> And it's always good to make them, you know, success has many fathers, if you will-- >> Yep. >> Is always an expression. Making them feel part of the solution. >> Absolutely. >> So I got to ask you a question. Is having a software background, coming into the tech world and the business world, this, now, you're starting to see applications really dictate to the infrastructure. Elastic clouds are out there. >> Tara: Yes. >> You have data as a resource now. If you were entering the market as a young software engineer today, and you were asked to come in and make an impact, knowing what you know, how do you see the world today? Because, you know, a lot of software engineers creating value from men, and, now, a lot more women are coming on board. >> Yeah, yeah. >> It's still lower numbers, but still, software's not just that software engineer. >> Yeah. >> It's software architecture, it's software engineering, software development, UX, UI-- >> Tara: Yeah. >> Analytics, a lot of range-- >> Tara: Yeah, yeah. >> Of software opportunities. How would you attack the marketplace today if you were coming in and entering the workforce or in the middle of your career? >> Yes, you know, when I look at my career, which is a little longer than I'd like to admit, I see myself as a young undergraduate student in India. I was one of six girls in a class of about 50. I was striving to get a degree in what was called, actually, electronics and telecommunication. I was in a minority. I came over here to the United States, and I continued to be in the minority. I look at my career, which is more than 25 years old. I have also continued to stay in the minority throughout that career. The biggest difference between where I am now in my career versus where I was then is I don't care as much anymore that I'm in the minority. (both laugh) Right? What is fascinating to me, though, John, is when I look at some of the very young students, actually, we had a high school intern program for the first time this year at Clorox, which is actually interesting. We typically have college interns, but this year, Clorox, a 105-year-old company in the middle of the Silicon Valley, having the ability to see that the very, very young generation can think very differently, and bringing in the high school intern, or a set of high school interns, to help with that journey, I think, was forward-thinking for the company. And those kids, the confidence that they have? They are not shackled by knowing too much, you know? >> John: Yes. >> But they know what's relevant, they know how to make things happen, and boy, do they know how to use technology to make problems that we consider problems that would take months, happen so quickly. They were with us for four weeks. In four weeks, they developed an app, a website. They developed our logo. They developed a PR video for us. They had an innovation showcase. In four weeks, four little students. >> It's interesting, for the first time (Tara laughs) in my career, I can admit that, from a self-awareness standpoint, "Well, I really don't know what I'm talking about." These young kids have a different view, because now their experiences are different. >> Tara: Yes. >> And so, the insight coming out of this new generation really is pretty compelling. >> Tara: It is. >> They are adding a lot more because there's been a shift in expectations, there's been a shift in experiences-- >> Tara: Yes. >> For this new generation, and they're at the forefront, so it's a big wave coming. What's your thoughts on that? Because analytics is a big part of your career now, and it always-- >> Tara: Yes, yes. >> Has been, but now, more than ever-- >> Yeah. >> The younger generation, they want instant gratification, they want value. >> They do. >> They don't want to wait and be told-- >> They do. >> They want to see the immediacy. >> They do. >> Talk about this new shift, this new younger generation. >> Yeah, yeah. You know, there used to be the good old days, where we could, say, put a product out there and, you know, eventually it kind of works its way into the consumer ecosystem, and then we'd get to hear back, over the course of time. Customers would call in with a recommendation or a complaint. It's very different now. Things are out there instantaneously. We put something out there, you're getting comments and reviews, some of them good, some of them not so good. It's out there, and it's out there instantly. And that also, the modern consumer is not shy. They kind of hide behind the keyboard, and they're putting their comments out there, right? (both laugh) They're the keyboard warriors! >> John: (laughs) Yeah. >> So being able to respond to that and having not just the data, but the ability to extract insights from data and to extract insights in real time, that is crucial. And so, gone are the days where you had months to do your analytics. You have to be able to do your analytics in the flow, you have to be able to take in new information, incorporate it into your models, be able to do predictive analytics on it. So technology and the way that it is evolving is super critical for survival these days. >> So, survival, and also competitive advantage, we've heard-- >> Oh, for sure. >> From other CIOs, and also CSOs, from a security standpoint-- >> Yes, yes. >> There's business risks involved. How real-time do you see the advantage being? Obviously, near real time is pretty much what people talk about. >> Yeah. >> Real time is to the second, and self-driving cars will certainly need that. >> Yeah, yeah, yeah. >> But as a leader chasing the real-time holy grail-- >> Yeah. >> Seems to be a theme we hear. How do you react to that, and how do you view real-time data? >> There is definitely something that builds up to the richness of data that you can take advantage of in "real time." And I am saying "real time" in quotes because there is a contextuality associated with it. The wonder of modern advanced analytics and machine learning is that you have an existing model that you're tweaking and evolving with new information, and that model is serving as your guide as you receive new information. So, does it have to be reactive, or can it be proactive? You're building the insights, and then you're adding on new information as you see it. And you're using technology to help you make more holistic decisions. And at the end of the day, there is something to be said about the human aspect of it. The machine can give you guidance-- >> John: Yes. >> But the human being needs to make the decision. >> I'd love to ask you a quick question on that, because I think this is something that we talk about all the time. >> Yeah. >> Humans are critical in the equation, machines augment the humans. >> Yes. >> In the data world, if you're "data-driven," which has been (laughs) a cliche, "We're data-driven!" >> Tara: Yes, yes. >> It takes on multiple forms. >> Tara: Yes. >> I've seen multiple actors saying, "We're data-driven," but they're really just correlating data. >> Tara: Yeah. >> The causation side of it is, what's causing things, that's more of a management thing. >> Tara: Yeah. >> So causation and correlation are two different variables-- >> Tara: Yes. >> In the analytics field right now-- >> Tara: Yeah. >> That are being amplified as, you got to know the distinction between correlation, because you can correlate anything, causation is something that might be more designed towards figuring out something, and you really can't rest on one more than the other. >> Yeah. (laughs) >> Your thoughts on the balance between the two. >> You're talking to someone who worked in health care for-- (laughs) >> John: (laughs) I probably won't get you to continue. >> For almost seven years. Causation and correlation are-- >> John: More important than ever. >> Are more important than ever. And I think more and more, the boundary between what machines can do and how they can augment human beings, versus actually having the machines help you make decisions, it's getting fuzzier, and machines are able to do more and more. I mean, all of the knowledge that you could read about 24 hours a day cannot sit in your head. You have to be able to leverage machines to help you make those decisions. So as far as causation and correlation, I think the correlation is something that the machine can be the master of. It can see patterns where you may not even think to look for patterns. So I think that, let's give it up to the machines. Correlation is where-- >> John: They got that. >> The machines have got that, and you got to set them up so that they can do that for you. Causation is where the tricky area starts to happen. Because there is a lot to say, especially when you talk about doctors, about experience and working with individuals. Each individual is different. You can't say that the causation for this person is the same as that because the correlations are similar. No, you have to look, there are so many factors that go into what is causing-- >> John: Yeah. >> A disease or a condition in a person. So I think that is where the human element and experience really, really still make a difference. >> In the media business, we call it behavioral and contextual. >> Yes. >> Context is really important for really aligning-- >> It is. >> With whatever the problem statement may be. >> Yes, yes. >> Correlation, behavior, machines can do that. >> Correct. >> That's awesome, great, great, great insight there. A final question for you is, for other folks out there, CIOs or IT executives, as they look at the digital transformation journey, which, again, very cliche, but very real, there's a lot of opportunities, but also potential pitfalls if not executed properly. >> Tara: Yeah. >> Your thoughts on general roadmaps or best practices around how to tackle transformation, if they're doing it, coming in for the first time or at the beginning, or if they're in the middle of a digital transformation, and they're stuck in the mud-- >> Yeah, yeah. >> Or "Oh my God, "my head person quit. "I got to get more people." >> Yeah. >> "I need developers," or people on the back end of the transformation, different parts of the journey. What's your advice? >> Yeah, I've got a couple of, again, from the scars of my past, a couple of things that I think are important. Number one, when I joined Clorox, I had the stretch goal of actually building out their cybersecurity program. I had not done that in the previous part of my career. I was an enterprise architect, that's where I would spend most of my many years. But cybersecurity, and I hired the CSO and built out that program for Clorox, it puts a whole different lens on how you look at your transformation, and it is an important lens. And I think I would not have been rounded, as either an enterprise architect who's developing technology strategy or a digital technology innovator, if I did not have that lens of, there is risk that you need to consider. Now, the point to remember is that you can't over-rotate one way or the other. You have to consider risk and opportunity, and there's a fine line. And I think the smartest CIOs and senior executives know where that fine line exists, and are able to tell when you need to go this way or that way. So that's one thing that I would say, is don't lose that lens. Technology can do wonderful things for you, but so can the hackers from a different-- >> You got to be aware-- >> You've got to be aware. >> And then, you've got to shape it, too, as it evolves. Is that something that you see as important? >> You have to have that lens of, you're doing this wonderful, amazing thing, however, what if the unintended audience is able to access whatever you're doing? And what can they do with it? So that's one thing that I would say, is keep that balance in mind. Again, don't over-rotate one way or the other, but keep that balance in mind. The other thing that I would say is, innovation is a state of mind that needs to be nurtured and developed, and it needs to be sought from every part of the organization. The only way to scale innovation is to have everybody be an innovator in the organization. So that would be my advice, is innovation can come from the youngest high school intern, or, we actually just had someone at Clorox celebrate their 50th year at Clorox. So, you know-- >> John: Yeah. >> Innovation can come from anywhere in the organization. You have to always be ready, open-minded, and prepared to grab that opportunity when it happens. >> My final takeaway for this is in context to where we are now, we're on Sand Hill Road-- >> Yes. >> At Mayfield Fund, they're a venture capitalist. >> Yes. >> They fund early-stage and growth. >> Yep. >> The younger generation, we just talked about the insights that they can have, new shifts that are happening in experiences, expectations. The startups, more than ever, have an opportunity to have customers like Clorox. >> Tara: Yes, yes. >> What used to be, "Well, a startup, "risk, don't go through the, go through TSA, "and when you get approved, "then we'll talk to you," kind of thing. (Tara guffaws) It's a big, painful process. >> Used to be? >> Now, more than ever, startups want to land the big Clorox deals. >> Yes, yes. >> They want to show the value proposition, time to value, shortening, with cloud and other things. What's your advice to startups who want to sell to you or hope to, aspire to, be successful in the marketplace? >> You know, I love startups, and I spent a lot of time with them. What I have seen as differentiating in the startups that I have seen is, some of them, they're out there, they want your business. So they are looking at you from that, "Can I get your business?" And then there are other startups that, I'm sure they've got that lens, but they don't make it obvious to you. To them, the value is in working with you. You're a company that is well-reputed. You've got a ton of amazing data that can be used to develop your models. You've got a ton of insights and understanding of the business that you can get by just working with this "reputed" company, like Clorox. Those in itself, you can't put a tangible, material value on that, but that is what helps startups build relevant and amazing products. And that, in itself, is "payment." The money will come, but look to the experiences, look to the ability to leverage data, and, above all, look to how you can position your product in a way that it is solving a business problem. Don't do technology for technology's sake. >> So, your advice would be, don't focus on on the PO. If they're venture-backed, they probably have some runway. >> Yes. >> Focus on the value proposition. >> Absolutely, and learning how companies operate and what's important to them, take the time to do that. >> How about scale? Do you hear that a lot with startups, they want to try to use the value proposition? One, they have to get in the door and show value, so that's one. >> Tara: Of course. >> Kind of table stakes, get through the door. >> Okay, yep. >> Then it's more about how they can be operationalized. That becomes something I've seen with startups. What's your thoughts on that? Because one of the benefits of getting in the door is getting (laughs) in the door, but staying in-- >> Yeah. >> Is about operationalizing that new value proposition. How do you look at that as a leader? >> (sharply exhales) Yeah, the word operationalization is an interesting one. So, companies like Clorox, I mean, while I love to work with startups, I will tell you that I do experiments, four, six, eight weeks, we've got a metric. If we go beyond that, it's probably a project that needs to go through a different route. But we do these experiments, and we do them quickly. The thing that we do worry about is, "Okay, great startup, great product. "Is it enterprise-ready?" You know? And I think that is where a lot of startups struggle a little bit, is, can they prove to you that their product is Fort Knox, that it won't be a way through which your systems get hacked? Can they prove to you that they've got a good handle on where they are going, what their roadmap is, what capabilities they are developing in their roadmap? Can they showcase that to you in a way that makes sense to you? We're looking for companies that are not just here today and gone tomorrow, companies that are here for the long run. And then, even if they can't do all of that, show that you integrate really well with our other products. Because, guess what, if you don't work out so well for us, little startup, we want to be able to replace you. We want to have that option. And if you don't integrate seamlessly and can be plucked out and put back in again, then we're stuck with something that we can't extract from our environment. So they've got to think how we think, is what I would advise them. (laughs) >> Tara, thanks so much for this great insight. For startups out there, for folks entering their career, for other women who are looking to break into tech, we have a great inspirational leader here. >> Thank you. >> John: Thank you for spending the time, we really appreciate it. >> Thank you very much, really appreciate it. >> Thank you very much. I'm John Furrier. You're watching the People First program with SiliconANGLE and Mayfield. Thanks for watching. (upbeat electronic music)

>> Over and welcome to this special cube conversation here in the Palo Alto Studios of Cube. Part of our People. First project with Mayfield Fund and Co creation with Cuban John Very your host. Very special guest. Judy Estrin. She's the CEO of J Labs and author of the book Closing the Innovation Gap. She's also well known for being an Internet entrepreneur. Pioneer worked on the initial TCP IP protocol with Vin Cerf from When the A Stanford Great History Computer Science. You have computer systems in your blood, and now you're mentoring a lot of companies. Author you a lot of work, and you're lending your voice to some cutting edge issues here in Silicon Valley and around the world. Thanks for joining me today for the conversation. >> Thank you. It's fun to be here, >> So I love the fact that you're here. You're a celebrity in the commute computer industry circles. You were there at the beginning, when the computer systems or the Internet were being connected as they built out of stone of the whole system's revolution in the eighties, and the rest is history. Now we have cloud computing, and now we're seeing a whole nother level step function of scale. And so you've kind of seen it all. You've seen all all the waves. Actually, something like make is they have seen some of the ways, but you've seen all of them. The most compelling thing I think that's happening now is the convergence of social science and computer science. Kind of our motto. Silicon Angle. You recently wrote to Post on Medium that that has been kind of trending and going viral. I want to get your perspective on that. And they're They're interesting because they they bring a little bit of computer science called the authoritative Authority Terrian Technology Reclaiming Control far too attention, part one. We go into great detail to lay out some big picture computer industry discussions. What's it all about? What's what's the What's the idea behind these stories? >> So let me back up a little bit in that, a Sze Yu said. And we can go into this if you want. I was very involved in a lot of thie, ah, innovation that happened in the Village Valley in terms of microprocessors, the Internet, networking, everything that laid the foundation for a lot of the things we see today incredible opportunities for my career for problems we solved over the last ten years. Ten, twelve years. Um, I began to see a shift and a shift in the culture and a shift in the way technology was impacting us. And it's not all good or bad. It's that it felt like we were out of balance and that we were becoming shorter and shorter, term focused and actually my book in two thousand eight closing the innovation gap. The main message there is let's not forget about the seeds you plant that all of this comes from because we're reaping the benefit of those seeds. We're not planning new seats and that we were becoming in the Valley in the nation the way we thought about things more and more short term focused and technology was causing some of that and benefitting and not been and at a disadvantage because of that. So that started with my book in two thousand eight and then in twenty fourteen, I think it was I did a Ted talk a Ted X talk called Balancing our Digital Diets, and I was even Mohr concerned that we were out of whack in terms of the consequences of innovation, and I drew an analogy to our food's systems, where so much innovation and creating cheap calories and energy and things like high fructose corn syrup that it took years to realize that, Oh, there's some negative consequences of that innovation. And so that was kind of a warning that, um, we weren't thinking enough about the consequences of at that point. Social media. That was before fake news, and I talked about tweets and how truth that lies went faster than truth, not knowing how bad that situation was going to be and then leading up to the election and after the election. We all know and have all learned now about the impacts of these technologies on our democracy, and I believe on our society and humanity. And I don't think it's just about our election system. I think it's about our psyches and how the technology's air impacting the way we think our fear and anxiety level of our kids and us is adults. So I been talking to people about it and advising, and I finally decided as, uh, I was collaborating with people that I felt that a lot of the awareness was in pockets that we talked about data privacy or we talked about addiction. But these air things were all interrelated, and so I wanted to one ad. My voices is technologists because I think a lot of the people who are writing the building, the awareness and talking about it if you are in government or a journalist's or even a social scientist people, it's really easy to say, Yeah, you say that, but you don't understand. It's more complicated than that. You don't understand the technology. So one, I do understand that technology. So I felt adding my voice as a technologist. But I'm also, uh, just increasingly concerned about what we do about it and that we take a more holistic view. So that's what, what what the pieces are about. And the reason I broke it into two pieces is because they're too long for most people, even the way they are. But the first is to build awareness of the problems which we can dig into it a high level if you want. And then the second is to throw out ideas as we move towards discussing solutions. So let me take a breath because you were goingto jump in, and then I can. >> No, it's just because you're connecting the foundational of technology foundation technology, identifying impact, looking at pockets of awareness and then looking at how it's all kind of coming together when you talk like that The first time I saw O subsystem interrupt us connection so someone could get like a operating system. And I think the society that you're pointing out in the article, the first one intention was there only to relate. And I think that's the key part. I think that's interesting because we run into people all the time when we do our cue broadcasts that have awareness here and don't know what's going on this. So this context that's highly cohesive. But there's no connection, right? So the decoupled right but highly cohesive, That's kind of systems. Architecture concept. So how do we create a robust technology's society system where technology and I think that's a threat that we're seeing this? What I cleaned out of the articles was your kind of raising the flag a little bit to the notion of big picture right system, kind of a foundational, but let's look at consequences and inter relationships, and how can we kind of orchestrate and figure out solutions? So what was the reaction to expand on that concept? Because this is where I was. It was provocative to me, >> right? So I think there are two thought trains that I just went down. One is that one of the problems we have that has been created by technology and technology is suffering from again. It's causing both cause and effect is not enough seats, system thinking and so one issue, which is not just this is not just about social media and not just about a I, but over the last twenty years we've increasingly trained, I think, are, Ah, engineers and computer scientists in Mohr transactional thinking. And as we move quicker and quicker to solve problems, we are not training our leaders or training our technologist to think in terms of systems. And so what I mean by systems is two things that you can break, that any problems have pieces. But those pieces air inter connected. We are interconnected, and that you, if you don't keep those things in mind, then you will not design things in a way, I believe that have the longevity and make the right type decisions. The second is the law of consequences when you have a system, if you do something here, it's going to impact something here. And so that whole notion of taking was thinking through consequences. I'm afraid that we're training people as we are focusing on being more and more agile, moving more and more quickly that it's in technology and in society that we're losing some of that system, thinking >> that they kind of think that's the trade off is always around. Whenever he had systems conversations in the past, but my old systems had on trade offs, we have overhead, so we have more memory. How do we handle things? So this is kind of That's just what happens. You tell about consequence, but >> we don't have all those we I'm older than you. But we started at a time when that we were limited. We were limited by memory. We were limited by processing. We were limited by band with and a different times. As thie industry emerged, the constraints were in different areas. Today, you don't have any of those constraints. And so, if you don't have any of those constraints. You don't get trained in thinking about trade offs and thinking about consequences. So when when we come into just what drove me to write, this one set of things are foundational issues and what I mean by foundational it's it's our relationship to technology. And the fact of the matter is, as a society, um, we put technology on a pedestal, and we have, uh, this is not to be taken out of Cut is not to be taken the extreme of talking about people, but overall, our relationship with technology is a bullying, controlling relationship. That's why I called it authoritarianism. >> Upgrade your iPhone to the new version. >> Well, whether it's as a user that you're giving up your your your authority to all these notifications and to your addiction, whether it is the fact that it is the control with the data, whether it is predictive ai ai algorithms that are reading your unconscious behaviors and telling you what you think, because if it's suggesting what you by putting things in front of you. So there are all of these behaviors that our relationship with technology is not a balanced relationship and you could one. You have a culture where the companies that are that have that power are driving towards. It's a culture of moving fast growth only don't think about the consequences. It's not just the unintended consequences, but it's the consequences of intended use. So the business models and at which we don't need to go into, because I think a lot of other people talk about that all end up with a situation which is unhealthy for us as people and humanity and for us as a society. So you take that part and it is. There's a parallel here, and we should learn from what happened with industrial Ah, the industrial revolution. We want progress. But if we don't pay attention to the harm, the harmful byproducts and trade offs of progress, it's why we have issues with climate. It's why we have plastic in our oceans. It's because you, you judge everything by progresses just growth and industrialization without thinking about well being or the consequences. Well, I believe we now face a similar challenge of digitization, so it's not industrialization. But it's digitalization that has byproducts in a whole number of areas. And so what the the article does is get into those specifics, whether it's data or anxiety, how we think our cognitive abilities, our ability to solve problems, All of those things are byproducts of progress. And so we should debate um, where we what we're willing to give up one last thing. And then I'll have to come in, which is one of the problems with both of these is is humans value convenience. We get addicted to convenience, and if somebody gives us something that is going to make things more convenient, it sure is held to go backward. And that's one of the reasons the combination of measuring our goodness as a country or a CZ. Globalization by economic growth and measuring our personal wellness by convenience, if something is more convenient, were happier. Take those two together, and it makes a dangerous cop combination because then our need for community convenience gets manipulated for continued economic growth. And it doesn't necessarily end up in, Ah, progress from, ah, well being perspective. >> It's interesting point about the digitization, because the digital industrial revolution, when the digital revolution is happening, has consequences. We're seeing them and you point them out in your post Facebook and fake news. There's also the global landscape is the political overlay. There's societal impact. There's not enough scholars that I've been trained in the art of understanding into relationships of technology, and Peg used to be a nerd thing. And now my kids are growing up. Digital natives. Technology is mainstreams, and there it is. Politics. You know, the first hack collection, Some of the control, The first president actually trolled his way. That president, I said that I'm the kid. That was my position. He actually was a successful troll and got everyone he trolled the media and you got the attention. These air new dynamics, This is reality. So is you look forward and bring these ideas, and I want to get your thoughts on ideas on how to bring people together. You've been on a CTO Cisco Systems. I know you've been sleeping on a board. This is a cross pollination opportunity. Bring people together to think about this. How do you do You look at that? How do you view how to take the next steps as a as an industry, as a society and as a global nations? It eventually, because cyber security privacy is becoming polarized. Also on a geography bases in China they have. GPR is hard core there. In Europe, he got Asia. With Chinese. You got America being American. It's kind of complicated as a system architecture thinking. How do you look at this? What is the playing field where the guard rails? What's your thoughts on this? Because it's a hard one, >> right? So it is a hard one and it isn't. It isn't easy to pave out a path that says it's solvable. Um, nor does Climate right now. But you have to believe we're going to figure it out because we have to figure it out. So I think there are a lot of pieces that we need to start with, and then we need to adjust along the way. And, um, one piece is and let me back up. I am not. I don't believe we can leave this up to the industry to solve the incentives and the value systems and the understanding of the issues. The industry is coming from an industry perspective, and you can't also. You also can't leave it just two technologists because technologists have a technology person perspective. I don't believe that you just can have government solve it for a variety of reasons. One is, if it takes a spectrum of things to legislation, tends to be retroactive, not forward looking. And you need to be really careful not to come up with regulation that actually reinforces the status quo as opposed to making something better. But I think we need to. We do need to figure out how to govern in a way that includes all of these things. So once >> it's running, it's clear that watching the Facebook hearing and watching soon dark sky in front of the house. Our current elected officials actually don't even know how the Internet works, so that's one challenge. So you have a shift in its every beat >> and it and it's actually, if you think about the way legislation often gets made one of the problems with our democracy right now, I'm not going to put it in quotes. But I want to put it >> out. >> Is that the influence of money on our democracy means that so often the input toe legislation comes from industry. So whether it's again big tech, big pharma, big Oil, big. That's the way this cycle works in places where we have had successful legislation that industry input, what you need industry input. You just don't want industry to be the on ly input that is balanced with other input. And so we need infrastructure in the world. In the country that has policy ideas, technology. This needs to come from civil society, from the academy from non profits. So you need the same way we have environmental sciences. We need to fund from government, not just industry funded that science. That's number one. And then we need ways to have conversations about influencing companies to do the right thing. Some of it is going to be through legislation some of it is going to be for through pressure. This, in some ways is like tobacco in some ways, like it's like food. In some ways, it's like climate on DH. It's so and an underlying any of this to happen. We need people to understand and to speak up because awareness amongst whether it's individuals, parents, teachers, we need to give people the information to protect themselves and to push back on companies and to rally pushback on government. Because if if there's not an awareness of people are walking around saying, Don't take away my service, don't make this less convenient don't tax my soda. Don't tell me my text messages. That's right, so and I'm not saying taxes of the way. But if there isn't what what I'm focused on is, how do we build awareness? How do we get information out? How do we get companies like yours and others that this becomes part of >> our >> messaging of understanding so we can be talking about I >> think it's, you know back, Teo, The glory days of the TCP epi Internet revolution. He sent a package from here to there. It's a step. Take a first step. I personally listening to you talk feel and I said, It's on The Cuban people know that. You know, my my rap know that I've been pounding this. There's a counter culture in there somewhere. Counter culture's is where action happens, and I think you know, tax regulation and, you know, the current generations inherited. It is what it is we have. You're laying out essentially the current situation. John Markoff wrote a great book, What the door Mail said, talking about how the sixties counterculture influence the computer industry from breaking in for getting computer time for time sharing, too hippy revolution question I have for you put you on the spot. Is Is there a counterculture in your mind? Coming a digital hippie quotes is because I feel it. I feel that that let the air out of the balloon before it pops. Something has to happen and I think has to be a counterculture. I yet yet can't put my finger on it. Maybe it's a digital kind of a revolution, something compelling that says Whoa time out. >> All right? I think we need a couple of counter culture's in that in layers of it, because, um, I think there is going to be or is starting to be a counterculture amongst technologist and the technology industry and entrepreneurs who are some it's still small who are saying, You know what? This chasing unicorns and fastest growth and scale, you know, move faxed and break things. But, um, we want to move fast, but we want to think about whether we're breaking what we're breaking is really dangerous, you know, move fast and break things is fine, but if it's oops, we broke democracy. That isn't something that, uh that is I'm sorry you have to think about and adapt more quickly. So I think there is Are people who are talking about let's talk openly about the harm. Let's not just be tech optimists. Let's understand that it's small, but it's beginning and you're seeing it in a I for instance, the people who are saying Look, were technologists, we want to be responsible. This is a powerful weapon or tool. And let's make sure we think about how we use it. Let me just say one thing, which is, I think we needed another kind of counterculture, which I'm hoping is happing in a number of areas, which is societally saying, You know, we have a slow food movement. Maybe we just need a slow down, a little bit movement. So if you look at mindfulness, if you look at kids who are starting to say, You know what? I want to talk to someone in person, I don't. So we we need some of that counter movement where I'm hoping the pedestal starts to come back. In terms of people looking for real connectivity and not just numbers of connections, >> it's interesting, You know, everything has a symmetrical, responsible thing about it. For every fake news payload and network effect is potentially an opposite reaction of quality network effect. It's interesting, and I don't know where it is, but I think that's got it could be filled, certainly on the economic side, by new entrepreneurial thinking, like one observation I'm making is you know this. Remember, they'll bad boys of tech and he's smiling. Now It's bad gals, too, which is growing still lower numbers. So I think there's gonna be a shift to the good, the good folks right moment. But she's a she's a good entrepreneur. She's not just out there to make a quick buck or hey, mission driven za signal we're seeing. So you start to see a little bit more of a swing to Whoa, hey, let's recognize that it's not about, you know, could Buck or >> so, yes, but between you and I, it's teeny compared to the other forces. So that's what those of us who believe that needs to happen need to continue to >> one of those forces money making. >> I think it's a combination of, Ah, money and how much money, Dr. Celebrity culture, um, the forces, the power that's in place is so strong that it's hard to break through, um, short term thinking, not even being trained. So like so many things in our culture, where you have entrenched power and then you see uprising and you get hope and that's where you need the hope. But, um, we've seen it so often in so many movements, from race to gender, where you think, Oh, that's solved, it's not solved and then you come back in and come back at it. So I just I would argue that there is little bits of it, but it needs fuel. It needs continuity. It it. And the reason I think we need some government regulation is it needs help because it's not gonna >> happen. You should question, you know, some successes that I point out Amazon Web services, Google even having a long game kind of narrative they're always kind of were misunderstood at first. Remember, Google was loud by search is not doing too well. Then the rest is history. Amazon was laughed. Amazon Web services was laughed at. So people who have the long game seemed to be winning in these transitions. And that's kind of what you're getting at. You think long term, the long game. If you think in terms of the long term vision, you then going look at consequences differently. How many people do you run in? The valleys actually think like that. Okay, >> so we're talking about two different things. One is long term thinking, and I do think that apple, Google, Amazon have taken long term thinking's. So there are a good example. But if you look at them, if we look at the big companies in terms of the way they approached the market and competition and their potential negative impacts on overall society, they're part of the power. They're not doing anything to change the systems, to not >> have good and continue to benefit. The rich get richer. >> So there this This is why it's complicated. There are not good guys and bad guys there are. These people are doing this and that. So do I think overall dough? I see more long term thinking. Um, not really. I think that the incentives in the investment community, the incentives in the stock market. The incentives culturally are still very much around shorter term thinking. Not that there aren't any, but >> yeah, I would agree. I mean, it tends to be, you know, Hey, we're crushing it. We're winning, you know? Look at us. Growth hack. I mean, just the languages. Semantics. You look at that. I think it's changed. I think Facebook is, I think, the poster child of short term thinking growth hacks move fast, break stuff and look where they are, you know, they can't actually sustaining and brand outside of Facebook, they have to buy Instagram and these other companies to actually get the kind of growth. But certainly Facebook is dominate on the financial performance, but they're kind of sitting in their situation. I think you know the bro Grammer movement, I think is kind of moving through the white common ear culture of Okay, let's get some entrepreneurship going. Great. Rod. I think that's stabilising. I think we're seeing with cloud really science and thinking for good. That's a positive sign. >> Well, I'm I'm glad to hear that from you, you know, and all >> you're probably going with. >> No, no, no, I'll take that and take that into feeding my hope because I hope, >> well, the movement is classic. Look, we're not gonna tolerate this anymore. I think transparency in my final question to you before you get to some of the more entrepreneur Question says, If you look at the role of community on data, science and connectedness, one of the things about being connected is you got potential potential for collective intelligence. So if you look at data, as I said, networks, what if there was a way to kind of hone that network to get to the truth fast? Esther, something we've been working on here, and I think that's something that, you know changes media. It changes the game. But collective intelligent, the role of the community now becomes a stakeholder and potentially laying out. So his problems and you're part of the Mayfield community was co created this video with roll community, super important people. The rule of the of the person your thoughts on >> so I community is a word that is has takes on a lot of meetings, and the problem is when you mean it one way and use it the other way, the same as data driven. So I think there's at one level which is community and conductivity that has to do with collecting input from lots of sources. And when you talk about investigative journalism or they're in environmental situations or all sorts of areas where the ability to collect information from lots of sources that air interested and analyze that information that is one level of community and connectivity and networking because of people you know which is great, there's another type. When people talk about community, they mean a sense of community in terms of what humans need and what that connectivity is. And most online networks don't give you that level. The online needs to be augmented by, Ah, inter personal understanding. And one of the problems. I think with today's technology is we're fitting humans into bits that technology Khun Support, as opposed to recognizing what are our human needs that we want to hold on to and saying There are some things that are not going to fit into somebody's data set. So in that first type of community than absolutely, I think there's lots of benefits of the cloud and wisdom of the crowd. But if you're talking about humans connecting in people. You don't have the same type of, uh, that that really community online tools can help. But we should never confuse what happens in our online world >> with your final question for, you know, we got We're pushing the time here. Thank you for spending time. First of all, it's great conversation. You've seen the movie with venture capital from the beginning. You know, all the original players seeing what is now just where's that come from? Where are we? What's the state of VC? Then? He hope to the future, they all adding value. How do you see that evolving and where are we with? >> You know, I would. I think venture capital has gone through a lot of different phases. And like so many things, especially those of us who want computers, we liketo lump them all together. They're not altogether. There are some small, Yes, like they field. And the I do think, though, that something shifted in the lead up to the dot com. Ah, and later the burst. And what shifted is venture capitalists. Before that time were company builders. They were the financiers, but they saw themselves with the entrepreneur building companies because of the expansion leading up to two thousand, and the funds grew and the people coming into the field were, they became more bankers and they took more financial supposed to balancing financing and entrepreneurship. It felt like it moved. Maurin toe. This is a private equity play, Um, and I think the dynamic with entrepreneurs and the methodology overall shifted, and I don't know that that's changed Now again, not across the board. I think there are some, uh, those firms that have identified our partners within firms who still very much want Teo filled companies and partner with entrepreneurs. But I think the dynamic shifted, and if you view them as that's what they are, is private equity investors. And don't expect something else. If people need money, that's a good pick. Ones that are the best partner >> is your partner. If you want a banker, go here. If you want Builder, go their key distinction. Judy. Thanks for sharing that insight. We're Judy Estrin. Sea of Jail as author of Closing Innovation. Gabbas Wellman's well known entrepreneur advisor board member formally CTO of Cisco. And again, Great gas. Thanks for coming on I'm John for Herewith. Cube conversation. Part ofmy Mayfield. People first with the Cube. Thanks for watching.

(upbeat music) >> Hello there and welcome to a special Cube conversation here at The Cube's Palo Alto studios, I'm John Furrier. Join with me for this special Cube Conference, Stu Miniman with Wikibon and The Cube co-host as well just up at Amazon Web Services Summit. Stu, great to see you again. Our next guest is Ben Golub, who's the executive chairman and interim CEO of Storj, pronounced storage. So it's a really hot cryptocurrency, blockchain based storage solution. I should say decentralized storage, not necessarily cryptocurrency, but tokens are involved, encryption. Great to see you. >> Great to see you, it's good to be back. >> Formerly Docker CEO and now advising at Mayfield Fund as a venture partner and also interim CEO of a hot-- >> Yeah really exciting company. And I'm really excited to talk to you about it today. >> So let's just jump into it. So obviously the ICO craze is awesome and we've always speculated that the blockchain and the decentralized applications are coming is going to be the real action. But yet it's going to create efficiencies where there's inefficiencies. >> Sure. >> Venture capital is one of them and that's why the ICO craze is going. People are raising a boatload of money that they probably wouldn't have gotten that amount. >> Wouldn't have gotten, yeah no dilution, things like that. It's interesting yeah. >> So give us an update on Storj or storage. How much in ICO did they raised, whitepapers out there? It's peer to peer, give a quick, take a minute to explain what the company's doing. >> Yeah well I guess that I should probably start by saying that I think that blockchain is bigger than just cryptocurrency, and decentralized is bigger than blockchain, and Storj is primarily a decentralized storage company. So we're about decentralized apps and the whole thing would absolutely work even if we were just using dollars. But I think it does make it a whole lot more exciting. And so the company, kind of unique in the crypto space in that we actually had a running service that was providing real value, before we did the large token sale. And the token sale raised about $30 million. Fortunately they took about 10 of that in Ethereum and Bitcoin which rose up. So there's a good deal more than that in the bank account right now. >> John: Hopefully they converted to fiat currency. >> And then they converted to fiat along the way. >> It's at an all-time high of $20,000 right now. It's like $7,000, something like that. >> Yeah, so you know, didn't sell everything at the peak, but didn't sell at the-- >> Yeah, so we've been having many blockchain and crypto or token-based economic kind of things. But the real question is what's happening? Now we know the action's been on the infrastructure side. We look at all the top hedge funds, Polychain, amongst others. They love these deals because it's infrastructure. Is that where the action is and how are you guys looking at that because at the same time, there's a wave of decentralized applications also known as Dapps coming on. So there's a relationship going on between how fast the infrastructure can go, and then how applications are going to work with either on chain or off chain dynamics. >> Sure, sure. So maybe it would be helpful to give you a sense of what it is that we do. 'Cause I think that if you do that, then I think it makes sense in the context of decentralized infrastructure, decentralized apps, but also actually traditional infrastructure as well. I've always been searching for a company that I could describe at Thanksgiving. I've never succeeded, so I always end up saying that I'm in computers, and fixing somebody's printer. (laughing) But I guess if I were to describe Storj at Thanksgiving, I'd say it's basically the Airbnb of storage, or the Airbnb of disc drives. So Airbnb, people have lots of condos or vacation properties that aren't being used all the time, and so Airbnb brings them together with people who want to rent those, and they're the largest hotel company in the world, without owning a single property. And we're kind of doing the same thing with Storj, in that there is, first of all, this explosion in the amount of data that's getting created. It would fill a stack of CD-ROMs to Mars and back this year. Yet the price of cloud storage hasn't come down. And 90% of all the disc drives that are out there are only about 10% utilized. So seems like a problem that needs a solution. And that's what we've done. We've basically brought together a very large network of individuals and companies that have spare storage capacity and matched them up with people who need storage. The really cool aspect, there are many cool aspects about it, but one of them is that basically if you want to store on the Storj network, we take your file, you encrypt it, so we never hold the keys. You encrypt it, it's all scrambled up, we break it up into between 20 and 80 pieces, and we spread those out across 150,000 or so nodes that we have in our network. So it's super cheap, but it's also super secure. Great performance because the data's way out at the edge. And super available because there's no storm or power outage or idiot tripping over a power cord that can take out your storage. >> So, Ben, you touched on, first question I was going to ask, of course, trust and security. Storage I absolutely have to worry about, so it sounds like that's at the core, but there's a number of dynamics going on in the industry. Object storage was great, let's spread it out, let's make it more decentralized, but most of the core storage industry is speeds and feeds and latency's super important, and even when you start getting to distributed architecture, I worry about that latency. So what are kind of the use cases, what are some of the key customer issues? Is price a big piece of it? Or what solutions does Storj solve that others can't? >> I always said when I was at Cluster, which was a storage company that there were four things that mattered in storage. There's certainly price; there was security; as in I don't want anybody to be able to access it; there's availability, I never want to drop or lose files; and finally there's performance, how fast I can get it. And so for a huge range of use cases that involve files, basically everything that object storage is kind of used for today, the design of our system is actually much better because we've encrypted it locally and then spread it out, you really can't attack it. First of all, you'd have to figure out... So a would-be attacker who wanted to find one of your files in the storage network would have to figure out which of the 80 or the 20 nodes out of 150,000 it's located on. If they found one of those, and they got the small portion of the file that's there, they wouldn't be able to do anything with it 'cause it's encrypted. Even if they were somehow able to decrypt it by stealing the key from you, not from us... >> So encryption and immutability... >> And immutability, right. So you get all of that. So for the security piece, it's great. For the availability piece, I never lose a file. It's really, really good, because if you just look at the math, the chances that somehow... You can basically lose 10 out of 20 nodes and still be able to recover your files. And all of our nodes are run by different people, different power supply. >> So let's take a step back. How many nodes are on the network now, you said? >> 150,000 now, run by 70,000 farmers, is what we call them. They're not miners, 'cause they're not just solving that problem, they're just producing something of value. 70,000 farmers, and then we have on the network right now, over 50 petabytes of data, which is a really large amount, and yet, we don't run a single data center. >> Have you guys raised any venture at all, or is it all ICO proceeds? >> There was a small seed round that was done, before the ICO craze. But other than that, it's all-- >> And how many people are working on the company? >> 25. >> So you guys are a classic startup. The working product, how does that look now? Is it on the blockchain, is it off the chain, how's it working, Bitcoin? >> So I've described to you what the product does. So far nothing I've described to you involves blockchain. The way the economics work is that as a user, somebody who wants to store on our network, we quote a price in dollars. You can either pay us in dollars or in the Storj token, and as a farmer, you get compensated with a Storj token. And that's done, of course, using blockchain we're actually part of Ethereum. >> Is that ERC-20 token? >> ERC-20 token, yeah. There are also interesting things that we are working on using blockchain for things like you just mentioned, data integrity, so I can make sure that if I'm doing a snapshot of a database, and I want to make sure that it's exactly what it is, nobody can tamper with it, et cetera, then that's a perfect use of blockchain. But using blockchain for the stuff I was talking about before, like figuring out where the shards are and making sure that they're uptime and reliable, that's actually stuff where blockchain isn't the best answer. >> Ben, tell us a little bit about the customers that you find there, 'cause storage administrators, that role's been changing a lot, but the typical storage administrator, if you tell them, "Oh yeah, I'm doing some distributed thing, "somewhere else, and paying in crypto-currency," they'd be like, are you kidding me? I want this thing that I can lock and hold and guard with a gun. >> This is like anything else, there's an adoption curve, and right now it's clearly very much early adopters. And actually similarly to Docker and similar to the cloud in general, it's developers who are leading the way. Developers are saying, oh, wow, I can write to the storage network in the same way that I would have written to S3, only it's cheaper, for many use cases, more performing, and not centralized, so I'm not trusting one cloud provider. So for certain use cases, this is fantastic. >> Are there certain cloud native apps that you're finding have strong affinity here? >> Yeah, so basically what we have affinity with right now, and let's be clear, this is early days. I wouldn't recommend that people store their most sensitive data on this, but-- >> Not Oracle certified yet, is what you're saying? >> We're not Oracle certified, no. (laughing) Basically anything involving a large file that you're not writing to very frequently, but you're reading a lot, or that's getting read by lots of people around the world, we're a really good solution. It's one of the things I think I mentioned to you. So we've got 150,000 nodes. They're located in I think it's now 180 countries, and all over the U.S. So if you want to get your data close to the edge, the people who are consuming your data are really close to the edge, this is actually really good. And because it's spread across so many, you get the benefit of parallelism, so it's super fast, in addition to being super safe and super secure. >> How does it work for the farmers? Because we have video files, so we would love to spread our video files on the Storj network. So let's just say... >> I'd do a special deal for you, too, you know. >> Of course, yeah, get a little token action going on both sides, Cube coins. But the availability thing is concerning. Whose computers is it being stored on? Is it extra capacity? Is it servers? Is it people's home computers? What's the, is it that kind of model? >> Sure, so basically yeah, we, just as Airbnb measures reputation, we measure reputation, too. And so if you don't have a good reputation, certain characteristics, we won't send data to you. What it basically means is you've got to have dedicated hardware and a dedicated connection. So we do have people who are running things in their home, but it's not a laptop, it's not on your phone. But if you have a disc drive that's connected with reasonably high capacity and reasonably well connected, then you'll establish good reputation. But what we are seeing is we are seeing a lot of universities, a lot of small businesses, some data center operators who have spare capacity or just want to use us as like, be both a farmer and a user. So backup and get stuff on their capacity as a good idea. And interestingly enough, we also are getting a lot of people who were Bitcoin miners and bought equipment, which is good quality equipment, but there's such an arms race in doing that. >> So they abandoned, because it was too hard for them to get coins. >> It's too hard to make money, right, and very expensive, specialized equipment, and in our case, basically general high quality equipment works well. >> What's the profit model? How do the farmers make money? Take our Cube videos, as an example, so I'm paying you guys, and you're distributing those tokens? >> You're paying us and you're paying us either in dollars or tokens. And then farmers get compensated in tokens. Right now, about 60 cents on every dollar goes to farmers. And farmers get more storage based off of their reputation. We charge people based on both how much you're storing as well as how much bandwidth egress that you're doing, and we compensate farmers exactly the same way. >> It's handled through a consensus protocol that you guys have? >> Yeah, yeah, so the payment and assessing reputation we actually use good distributed blockchain as well there, right, so you're not counting on Storj to be in the middle there. Now, with the remaining 40 cents, which I think is actually the really interesting part, we keep some of that, we put some back into the network, but what I'm really excited about is that this is now a way for us to economically empower demand partners as well. The first thing we announced was FileZilla, but we have lots of other open source projects waiting in the wings, and we're happy to share with them. So as opposed to centralized cloud, where it's really hard to make money as an open source company, we're not an open source project in our case, right? We're happy if you're sending us users and data, to give you a really meaningful percentage. >> Any kind of freemium model you guys are playing with? I can imagine this being pretty interesting, because S3 democratized and lowered the cost barrier, obviously with cloud. >> S3 has been great for many things. >> How low are you in terms of the disruption? You guys are probably going to have to come in and undercut S3, is that the strategy? Or is that the price value? >> I think what I learned from my time in storage, is price is important but you have to be really safe and available and reliable, 'cause people's data is really important. But we looked across a pretty broad set of use cases, in comparing us to the traditional cloud providers we're probably a third. And we could go lower. What I think is really interesting in our case is that the economics just work really well. So from our perspective, if you're a farmer, you've already got, it's spare capacity, you don't need any more electricity to run this thing, you've got bandwidth, right? You don't need to hire any more people. So it's almost pure margin for a farmer, which is great for them. And so we can give economic value to farmers, we can give economic value to our customers, we can give economic value to partners. >> Any kind of economic models you can share in terms of what someone would make? Let's just say that I had this big music library that's not being used anymore, and I had a-- >> Well, as a customer of course, if you've got data that you want to store on our network, you'll save a lot of money, and it's probably a third of what you might pay. >> But is there any kind of, if I'm a farmer, I want to join the network? >> But if you're a farmer. >> How much am I going to make? >> It really depends on how much you're storing and how good your connection is, but as a farmer, I think you can make decent money. This could probably be I don't know off the top of my head, $20, $30 a month per drive, which isn't bad, and certainly much easier than making money-- >> So it kind of depends like the Airbnb model, depends how well you're using-- >> How well you're used. So some people earn less, some people earn more. And again, for most of the farmers, this is pure margin. >> Great, we got a couple back to back rooms, Stu. We should get some drives up there and get on board. We could pay for the cameras. >> And look, I think for videos, you guys would actually be a perfect use case with a lot of the stuff that's going to be coming out later this year. You get both storage and CDN like things for free, in the sense that because-- >> I'm really glad you brought that up, 'cause I want to ask you about Videocoin, 'cause Halsey Minor has Videocoin, another ICO, he raised $50 million. We covered that on Silicon Angle. But he's trying to democratize Acromi. Is that similar to what you guys are doing? >> I guess you could say yeah, we're further democratizing object storage, democratizing S3, but I think we can also democratize Acromi, we can democratize Isilon, there's certain other really exciting things that are-- >> What other services, you mentioned CDN, so it's not just storing the information, but that global dispersion, what does that enable? >> It used to be that people had a really big difference between archival which is slow, hard to get at, and CDN, right? And but actually, given the way that we're doing this thing, we can be pretty seamless. Pay archival for stuff that's staying in archival, but go up market if you're going to be having a lot of people read it. >> So I got to ask you about the, obviously, security. You're looking at it for additional services around redundancy, I can see that being a nice headroom for you. On a personal note, you've been involved in a lot of industry companies that have done very well, entrepreneurial success. >> Ben: Why am I doing this? (laughing) >> I can tell you're having fun. How could you not have fun, it's a whole 'nother generation of innovation, disruption coming, a whole 'nother price point. So what's it like, are you having fun? And if you could talk to your 22-year-old self right now, 'cause I wish I was 22 right now in this market-- >> Are you saying I'm not 22? >> How do you explain this? And when you go to parties, even in the Valley, and people say, "Man, you're crazy, it's a fricken' "scam out there," how do you explain to 'em this revolution? Because this is like a special, unique wave. How would you talk about that? >> Actually I describe it the same way to people in the Valley the same way that I described at the beginning, which is that blockchain is bigger than cryptocurrency, and decentralized is much bigger than blockchain. And Storj is first and foremost decentralized. It's about decentralized computing, decentralized storage, supporting decentralized apps, keeping the internet from ending up in the hands of just three people, three companies, which I think is really important. But also I feel very good that, to the extent that Storj does touch on cryptocurrency, that we've done it the right way. We had the service working first before we did the token sale. We raised what now appears to be a modest amount in the token sale, tried to be very transparent and at the forefront. >> You probably could've gotten more if you wanted to. >> Probably, right? But we were trying to be forefront in terms of governance and transparency, and I think that it'll probably be a good thing, just as it was kind of a good thing that the bubble burst in the late '90s and you got rid of a lot of such not great companies and not such great operators. I think that the current corrections, or whatever, in the crypto market I think will-- >> Like pets.com is gone, but DogeCoin still exists. (laughing) >> So I'm sure that somebody has a crypto base pets.com or webvan lurking in the wings somewhere. Kodak just did it. >> I got to ask you, you're super smart. You went to some really good schools, I think Princeton, Harvard Business School. So you got a good education, so I got to get your take on the whole token economics vision. 'Cause this is, if you look at outside the tech trends, there's actually new economic models that are coming out. Have you looked at token economics? New liquidity on the one side, you've got sovereignty, you've got consensus. These are not just tech issues, these are society issues. What's your vision around that? How are you viewing it? What's the upside? How is this shaping the future? >> Yeah, I think if you're a token network, you sort of have to have some central bank chops as well, right? And we actually have a central banker. >> John: So you have a chief economic officer? >> So we don't, no, we have an advisor-- >> John: Public policy. >> I actually had a degree in public policy at one point. But we need to think about the token supply in the same way you'd think about the money supply. We're backed by something real, so it's sort of like having currencies backed by gold. We need to make sure that the market grows and the network grows. And my fundamental belief is that the more the network grows, the more people use it, the more value that we're able to provide, that'll be good for token economics in the long run. In the short run, though, what we've done, is again, we price based off of dollars, and we compensate farmers based off the token based off of the spot price. So for farmers, we've tried to remove any need to worry about volatility or things like that. >> So I want your reaction-- >> Or the price. >> I've said on The Cube multiple times that in the old days of venture startups, the CTO was everything. You had to have a great CTO or VP of engineering and great senior executive team on the entrepreneurial team. Now it's almost like the chief economic officer is a critical piece, 'cause you've got public policy intersecting with economics. You've got new kinds of math that's not technical algorithm but it's kind of business algorithms. >> It is, business algorithms. Just like any economy, the money supply matters. And people's trust in that money matters. And the supply matters. All that stuff like that, and stability matters. So I think absolutely this new breed of network based token companies will have to worry about that, and probably should think about a chief economics officer, but it doesn't mean that you don't also have to have a great CTO and great technology, 'cause that's how you make the network valuable and grow. And one of the reasons that gave me both excitement and comfort about going to Storj is that the economic model works, fundamentally, even if the crypto's not there. >> John: 'Cause technology is decentralized. >> Decentralized storage makes sense even if you're buying and selling it with dollars or pounds or rubles, or whatever. >> Ben, great to see you, thanks for coming in and sharing the Ben Golub School of Economics, Public Policy for Tokens. You can give a class at Stanford on that soon, although that's the competition's school. >> Maybe, yes. Slightly different. We still like them. >> Great to see you, congratulations. Storj, pronounced storage. Great, successful ICO, hot startup, really, an example of the infrastructure opportunities of a new decentralized infrastructure that can be and will soon, we think, it will be critical infrastructure in a whole new way. Great to see you. >> Ben: Really good to see you, great to be back with you. >> It's the Cube Conversation, I'm John Furrier, Stu Miniman, thanks for watching. (upbeat music)