>> From Palo Alto, California, it's theCUBE. Covering the Conference Boards Sixth Annual Innovation Master Class. >> Hey, welcome back here, everybody. Jeff Frick here with theCUBE. We're at the Innovation Mater Class at Xerox PARC in Palo Alto. Really excited to be here, never been here, surprisingly, for all the shows we do just up the hill next to VMware, and Tesla. This is kind of the granddaddy of locations and innovation centers, it's been around forever. If you don't know the history, get a couple books, you'll learn it pretty fast. So we're excited to be here and our next guess is Antony Brydon, four-time founder and CEO, which is not easy to do. Again, check the math on that, most people are successful a couple times, hard to do it four times. And now he's the co-founder and CEO of Directly. So Antony, great to see you. >> It's good to be here. >> So, Directly, what is directly all about for people aren't familiar with the company? >> Most companies are excited to, and pursuing, the opportunity of automating up to 85% of their customer service. That's the ambition, and giving customers a delightful answer in their first experience. Most of those companies are falling down out of the gates because there are content gaps, and data gaps, and training gaps, and empathy gaps in the systems. So we build a CX automation platform and it puts experts at the heart of AI, letting these companies build networks of product experts and then rewarding those experts for creating content for AI systems, for training AI systems, for resolving customer questions. >> Right. So let's back up a step. So Zendesk is probably one we're all familiar with. You send in a customer service node, a lot of the times it comes back, customer service to Zendesk. >> Yes. >> But you're not building kind of a competitor of Zendesk, you're more of a partner, if I believe, for those types of applications, to help those apps do a better job. >> We are, we're a partner for Zendesk, we're a partner for Microsoft Dynamics, for Service Cloud and the like, and, essentially, are building the automation systems that make their AI systems work and work better. >> Right. >> Those are pure technology systems that often lack the data and the content to deliver AI at scale and quality, and that's where our platform and the human network, the experts in the mix, come into play. >> We could probably go for a long, long time on this topic. So what are some of the key things that make them not work now? Besides just the fact that it's kind of like the old dial-in systems. It's like, I just want to hit 0000. I just want to talk to a person. I have no confidence or faith that going through these other steps is going to get me the solution. Do you still see that on the online world as well? >> No, there are very clear gaps. There are four or five areas where systems are falling down. AI project mortality, as I refer to it. Very few companies have the structured data that systems need to work at scale. >> On the back, to feed the whole thing. >> That's right. Labeled, structured, organized data. So that doesn't exist. Many companies don't have the content. That's a second area. They may have enterprised knowledge bases, but they're five years old, they're seven years old, they're outdated, they're not accurate. Many companies don't have the signal. When a automated answer's delivered, they have to wait for a customer to rate it, and that tends to be really poor signal on whether that answer was good or not. And then last, many companies just don't have the teams to maintain these algorithms and constantly tune them. And that is where experts at the heart of a platform can come into play, by building a network of product experts who know the products inside and out. These could be Airbnb hosts for one of our customers, these could by Microsoft Excel users in the Microsoft example. Those experts can create that content, train the data, and actually resolve questions, filling those gaps, solving those problems. >> Right. I'm just curious, on the expert side, how many--? I don't know if there's best practices or if there's kind of certain buckets depending on the industry. Of those expert answers are generated by people inside the company versus a really kind of active, engaged community where you've got third-party experts that are happy to participate and help provide that info. >> Over 99% of the answers and the content is actually generated by the external network. >> 99%? >> 99%. You start with sources of enterprise knowledge, but it's a long, hard, arduous process to create those internal knowledge bases, and companies really struggle to keep up, it's Britannica. By the time you ship it it's outdated and you have to start all over again. The external expert networks work more like Wikipedia. Content constantly being organically created, the successful content is promoted, the unsuccessful content is demoted, and it's an evergreen cycle where it's constantly refreshing. Overwhelmingly external. >> Overwhelming. I mean, I could see where there's certain types of products. I was telling somebody else the other day about Harley-Davidson, one of the all-time great brands. People tattoo it on their body. Now, there aren't very many brands that people tattoo on their body. So easy to get people to talk about motorcycles or some of these types of things, but how do you do it for something that's really not that exciting? What are some of the tricks and incentives to engage that community? Or is there just always some little corps that you may or may not be aware of that are happy to jump in and so passionate about those types of products? >> There are definitely some companies where there's very little expertise and passion in the ecosystem around it. They're few and far between. If you find a product, if you find a company, you can find people that rely, love, and depend on that company. I gave some of the B to C examples, but we've also got networks for enterprise software companies, folks like SAP, folks like Autodesk. And those networks have experts that are developers, resellers, VARs, systems integrators, and the like. In the overwhelming majority of cases, the talent and the passion exists, you just have to have a simple platform to onboard and start tapping that talent and passion. >> So if I hear you right, you use kind of your Encyclopedia Britannica because that's what you have to start, to get the fly wheel moving, but as you start to collect inputs from third-party community, you can start to refine and get the better information back. And I ask specifically that way because you mentioned the human factors, and making people part of this thing, which is probably part of the problem with adoption, as I'd want confidence that there's some person behind this, even if the AI is smart. I'd want at least feel like there's some human-to-human contact when I reach out to this company. >> Yeah, that's critically important, because the empathy gap is real in almost all of the systems that are traditionally out there, which is when an automated answer's delivered, in a traditional system, it typically has a much lower CSAT than when it comes from a human being. What we found is when you have an expert author that content, when his or her face is shown next to the answer as it's presented to the user, and where he or she is there to back it up should that user still need more help, there you retain the human elements that personalize the contact, that humanize the experience, and immediately get big gains in CSAT. So It think that empathy piece is really important. >> Right. I wondered if you could share any specific examples of a customer that had an automated, kind of dumb system, I'll just use that word, compared to what they can do today, and some of the impacts when they put in some of the AI-powered systems like you guys support. >> So one of the first immediate impacts is often when we go in, a automated or unassisted system will be handling a very small percentage of the queries, and percentage of the customer questions coming in, and-- >> And people are going straight to zero, they're just like, I got to go to a person. >> Yeah, we're mostly in digital channels, so less phone, but yes, because the content there-- >> As an analogy, right. >> Because the content isn't there, it doesn't hit and resolve the question in that frequent a rate, or because the training and the signal isn't there, it's giving answers that are a little off-base. So the first and lowest hanging fruit is with a content library that's get created that can get 10, 50, 100 times broader that enterprise content pretty quickly. You're able to hit a much broader set of questions at a much higher rate. That's the first low-hanging fruit and kind of immediate impact. >> And is that helping them orchestrate, coordinate, collect data form this passionate ecosystem that's outside the four walls? Is that, essentially, what you're doing in that step? >> It essentially is. It is about companies having these ecosystems of these users, millions of hours of expertise in their head, millions of hours free time on their hands, and the ability to tap that in a systematic way. >> Wow. Shift gears a little bit, you are participating on a panel here at the event, talking about startups working with big companies and there's obviously a lot of challenges, starting with vendor viability issues, which is more kind of selling to big customers versus, necessarily, partnering with big companies. But what are some of the themes that you've seen that make that collaboration successful? Because, obviously, you've got different cultures, you got different kind of rates of the way things happen, you've got, beware the big company who eats you up in meetings all the time when you're a little start-up, they'll kill you accidentally just by scheduling so many meetings. What are some of the secrets of success that you're going to share here at the event? >> So we've got experience in that. Microsoft is a partner of ours, Microsoft Ventures is an investor. I think the single biggest key is an aligned vision and a complementary approach. The aligned vision where both the start-up and the partner are aiming for a similar point on the horizon. For example, the belief that automation can delight a very large set of customers by providing them a good, instant answer, but complementary approaches where the core skillsets of the companies round out each other and become less competitive. In this case, we've partnered with-- Microsoft is best in class AI platform and cognitive services, and we're able to tap and leverage that. We're also able to bring something unique to the equation by putting experts at the heart of it. So I think that architectural structure, in the first place, is a great example of kind of getting it right. >> Right. And your experience, that's been pretty easy to establish at the head-end of the process, so that you have kind of smooth sailing ahead? >> No, I don't think it's easy to establish at the head of the process, and I think that's where all of the good work and investment needs to happen. Upfront, on that kind of shared vision, and on that kind of complementary approach. And I think it is probably 20% building that together, but it's also 80% just finding it. The selection criteria by which a corporate partner picks a startup and the startup partner picks the corporate partner. I think just selecting right is the majority of the challenge, rather than trying to craft it kind of midstream. >> If it doesn't feel good at the beginning, it's probably not going to to work out. >> Right, it's about finding it. It's a little bit like the Venture analogy. Do they find great companies, or do they build great companies? Probably a little of both, but that finding that great company is a large part of the equation. >> Yeah, helps. So, Antony, finally get a last question. So, again, four successful startups. That does not happen very often with the same team. And look at your background, you're a psychology and philosophy major, not an engineer. So I'd just love to get kind of your thoughts about being a non-tech guy starting, running, and successfully exiting tech companies here in silicon valley. What's kind of the nice thing being from a slightly different background that you've used to really drive a number of successes? So I think the-- I think two things, I think one, coming from a non-tech and coming from a psych background has given us an appreciation of the human elements in these systems that tech alone can't do it. I'd say, personally, one of the impacts of being a non-tech founder in this valley is a heck of a lot of appreciation for what teams can do. And realizing that what teams can do is far more important than what individuals can do. And I say that because as a non-tech founder, there's literally nothing I could accomplish without being a part of a team. So that, I think, non-tech founders have that in spades. A harsh and frank realization that it's about team and they can't do anything on their own. >> Well, Antony, thanks for taking a minute out of your time. Good luck on the panel this afternoon and we'll keep an eye, watch the story unfold again. >> Yep, I appreciate it. Thanks very much. >> He's Antony, I'm Jeff, you're watching theCUBE. We're at the Master at the Master Innovation Class at Xerox PARC, thanks for watching.

>> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're at Data Privacy Day at Twitter's World Headquarters in downtown San Francisco. Full-day event, a lot of seminars and sessions talking about the issue of privacy. Even though Scott McNealy in 1999 said, "Privacy's dead, get over it," everyone here would beg to differ; and it's a really important topic. We're excited to have Michelle Dennedy. She's the Chief Privacy Officer from Cisco. Welcome, Michelle. >> Indeed, thank you. And when Scott said that, I was his Chief Privacy Officer. >> Oh you were? >> I'm well acquainted with my young friend Scott's feelings on the subject. >> It's pretty interesting, 'cause that was eight years before the iPhone, so a completely different world than actually one of the prior guests we were talking about privacy is an issue in the Harvard Business Review from 125 years ago. So this is not new. >> Absolutely. >> So how have things changed? I mean that's a great perspective that you were there. What was he kind of thinking about and really what are the privacy challenges now compared to 1999? >> So different. Such a different world. I mean fascinating that when that statement was made the discussion was a press conference where we were introducing Connectivity. It was an offshoot of Java, and it basically allowed you to send from your personal computer a wireless message to your printer so that a document could come out (gasp). >> That's what it was? >> Yeah. >> Wireless printing? >> Wireless printing. And really it was gyro technology, so anything wirelessly could start talking to each other in an internet of things world. >> Right. >> So, good news bad news. The world has exploded from there, obviously; but the base premise of, can I be mobile, can I live in a world of connectivity, and still have control over my story, who I am, where I am, what I'm doing? And it was really a reframing moment of when you say privacy is dead, if what you mean by that is secrecy and hiding away and not being connected to the world around you, I may agree with you. However, privacy as a functional definition of how we define ourselves, how we live in a culture, what we can expect in terms of morality, ethics, respect, and security, alive and well, baby. Alive and well. >> (laughs) No shortage of opportunity to keep you busy. We talked to a lot of people who go to a lot of tech conferences. I have to say I don't know that we've ever talked to a Chief Privacy Officer. >> You're missing out. >> I know, so not you get to define the role, I love it. So what are your priorities as Chief Priority Officer? What are you keeping an eye on day to day as well as what are your more strategic objectives? >> It's a great question. So the rise of the Chief Privacy Officer, actually Scott was a big help in that and gave me exactly the right amount of rope to hang myself with. The way I look at it is, probably the simplest analogy is, should you have a Chief Financial Officer? >> Yeah. >> I would guess yeah, right? That didn't exist about 100 years ago. We just kind of loped along, and whoever had the biggest bag of money at the end was deemed to be successful. Where if somebody else who had no money left at the end but bought another store, you would have no way of measuring that. So the Chief Privacy Officer is that person for your digital currency. I look at the pros and the cons, the profit and the loss, of data and the data footprint for our company and for all the people to whom we sell. We think about, what are those control mechanisms for data? So think of me as your data financial officer. >> Right, right. But the data in and of itself is just stagnant, right? It's really just the data in the context of all these other applications. How it's used, where it's used, when it's used, what it's combined with, that really starts to trip into areas of value as well as potential problems. >> I feel like we scripted this before, but we didn't. >> Jeff: We did not script it, we don't script the-- >> So if I took out a rectangle out of my wallet, and it had a number on it, and it was green, what would you say that thing probably is? >> Probably Andrew Jackson on the front. >> Yeah, probably Andrew Jackson. What is that? >> A 20 dollar bill. >> Why is that a 20 dollar bill? >> Because we agree that you're going to give it to me and it has that much value, and thankfully the guy at Starbucks will give me 20 bucks worth of coffee for it. >> (laughs) Exactly. Well which could be a cup the way we're going. >> Which could be a cup. >> But that's exactly right. So is that 20 dollar bill stagnant? Yes. That 20 dollar bill just sitting on the table between us is nothing. I could burn it up, I could put it in my pocket and lose it and never see it again. I could flush it down the toilet. That's how we used to treat our data. If you recognize instead the story that we share about that piece of currency, we happen to be in a place where it's really easy to alienate that currency. I could go downstairs here and spend it. If I was in Beijing I probably would have to go and convert it into a different currency, and we'd tell a story about that conversion because our standards interface is different. Data is exactly the same way. The story that we share together today is a valuable story because we're communicating out, we're here for a purpose. >> Right. >> We're making friends. I'm liking you because you're asking me all these great questions that I would have fed you had I been able to feed you questions. >> Jeff: (laughs) But it's only that context, it's only that communicability that brings it value. We now assume as a populous that paper currency is valuable. It's just paper. It's only as good as the story that enlivens it. So now we're looking at smaller, smaller Microdata transactions of how am I tweeting out information to people who follow me? >> Jeff: Right, right. >> How do I share that with your following public, and does that give me a greater opportunity to educate people about security and privacy? Does that allow my company to sell more of my goods and services because we're building ethics and privacy into the fabric of our networks? I would say that's as valuable or more valuable than that Andrew Jackson. >> So it's interesting 'cause you talk about building privacy into the products. We often hear about building security into the products, right? Because the old way of security of building a bigger wall doesn't work any more and you really have to bake it in at all steps of the application: development, the data layer, the database, et cetera, et cetera. When you look at privacy versus security, and especially 'cause Cisco's sitting on, I mean you guys are sitting on the pipes, everything is running through your machines. >> That's right. >> How do you separate the two, how do you prioritize, and how do you make sure the privacy discussion is certainly part of that gets the right amount of relevance within the context of the security conversation? >> It's a glib answer that's much more complicated, but the security is really in many instances the what. I can really secure almost any batch of data. It can be complete gobbley gook zeroes and ones. It could be something really critical. It could be my medical records. The privacy and the data about what that context is, that's the why. I don't see them as one or the other at all. I see security and security not as not a technology but a series of verb things that you actually physically, people process technologies. That enactment should be addressed to a why. So it's kind of Peter Drucker's management of you manage what you measure. That was like incendiary advice when it first came out. Well I wanted to say that you secure what you treasure. So if you treasure a digital interaction with your employees, your customers, and your community, you should probably secure that. >> Right. But it seems like there's a little bit of a disconnect about maybe what should be treasured and what is the value with folks that have grown up. Let's pick on the young kids, not really thinking through or having the time or knowing an impact of a negative event in terms of just clicking and accepting the EULA and using that application on their phone. They just look at in a different way. Is that valid? How do they change that behavior? How do you look at this new generation, and there's this sea of data which is far larger than it used to be coming off all these devices, internet of things, obviously. People are things too. The mobile devices with all that geolocation data, and the sensor data, and then oh by the way it's all going to be in our cars and everything else shortly. How's that landscape changing and challenging you in new ways, and what are you doing about it? >> The speed and dynamics are astronomical. How do you count the stars, right? >> Jeff: (laughs) >> And should you? Isn't that kind of a waste of time? >> Jeff: Right, right. >> It used to be that knowledge, when I was a kid, was knowing what was in A to Z of the Encyclopedia Britannica. Now facts are cheap. Facts used to be expensive. You had to take time and commit to them, and physically find them, and be smart enough to read, and on, and on, and on. The dumbest kid is smarter than I was with my Encyclopedia Britannica because we have search engines. Now their commodity is how do I critically think? How do I make my brand and make my way? How do I ride and surf on a wave of untold quantities of information to create a quality brand for myself? So the young people are actually in a much better position than, I'll still count us as young. >> Jeff: Yeah, Uh huh. >> But maybe less young. >> Less young, less young than we were yesterday. >> We are digital natives, but I think I am hugely optimistic that the kids coming up are really starting to understand the power of brand: personal brand, family brand, cultural brand. And they're feeling very activist about the whole thing. >> Yeah, which is interesting 'cause that was never a factor when there was no personal brand, right? You were part of-- >> No way. >> whatever entity that you were in. >> Well, you were in a clique. >> Right. >> Right? You identified as when I was home I was the third out of four kids. I was a Roman Catholic girl in the Midwest. I was a total dork with a bowl haircut. Now kids can curate who and what and how they are over the network. Young professionals can connect with people with experience. Or they can decide, I get this all the time on Twitter actually. How did you become a Chief Privacy Officer? I'm really interested in taking a pivot in my career. And I love talking to those people 'cause they always educate me, and I hope that I give them a little bit of value too. >> Right, right. Michelle, we could go on for on and on and on. But, unfortunately, I think you got to go cover a session. So we're going to let you go. >> Thank you. >> Michelle Dennedy, thanks for taking a few minutes of your time. >> Thank you, and don't miss another Data Privacy Day. >> I will not. We'll be back next year as well. I'm Jeff Frick. You're watching theCUBE. See you next time.