>>The Cube presents UI Path Forward five, brought to you by UI Path. >>Hi everybody. Welcome to Las Vegas. We're here in the Venetian, formerly the Sans Convention Center covering UI Path Forward five. This is the fourth time the Cube has covered forward, not counting the years during Covid, but UiPath was one of the first companies last year to bring back physical events. We did it at the Bellagio last year, Lisa Martin and myself. Today, my co-host is David Nicholson, coming off of last week's awesome CrowdStrike show back here in Vegas. David talking about UI path. UI path is a company that had a very strange path, as I wrote one time to IPO this company that was founded in 2005 and was basically a development shop. And then they realized they got lightning in a bottle with this RPA thing. Yeah. And Daniel Deez, the founder of the company, just really drove it hard and they really didn't do any big kind of VC raise for several years. >>And then all of a sudden, boom, the rocket ship took off, kind of really got out over their skis a little bit, but then got to IPO and, and has had a very successful sort of penetration into the market. The IPO obviously has not gone as well. We can talk about that, but, but they've hit a billion dollars in arr. There aren't a lot of companies that, you know, have hit a billion dollars in ARR that quickly. These guys had massive valuations that were cut back, obviously with the, with the downturn, but also some execution misuses. But the one thing about UiPath, Dave, is they've been very successful at penetrating customers. And that's the thing you always get at forward customer stories. And the other thing I'll, I'll, I'll add is that it started out with the narrative was, oh, automation software, robots, they're gonna take away jobs. The opposite has happened, the zero unemployment. Now basically we're heading into a recession, we're actually probably in a recession. And so how do you combat a recession? You put automation to work and gain if, if, if, if inflation is five to 7% and you can get 20% from automation. Well, it's a good roi. But you sat in the keynotes, it was really your first exposure to the company. What were your thoughts? >>Yeah, I think the whole subject is interesting. I think if you've been involved in tech for a while, the first thing you think of is, well, hold on a second. Isn't this just high tech scripting? Aren't you essentially just automating stuff? How, how cool can that possibly be? >>Well, it kinda was in the >>Beginning. Yeah, yeah. But, but, but when you dig into it, to your, to your point about the concern about displacing human beings, the first things that can automate it are the mundane and the repetitive tasks, which then frees individuals up frontline individuals who are doing those tasks to do more strategic things for the business. So when you, when we, you know, one of the things that was talked about in the keynote was this idea of an army of citizen developers within an organization. Not, you know, not just folks who are innovating and automating at the core of enterprise applications, but also folks out on the front line automating the tasks that are interfering with their productivity. So it seems like it's a win-win for, for everybody throughout the enterprise. >>Yeah. So let's take a, let's take folks through the, the keynote to, basically we learned there are 3,500 people here, roughly, you know, we're in the Venetian and we do a lot of shows at, at the Venetian, formerly the San Convention Center. The one thing about UiPath, they, they are a cool company. Yeah, they are orange colors, kinda like pure storage, but they got the robots moving around. The setup is very nice, it's very welcoming and very cool, but 300 3500 attendees, including partners and UiPath employees, 250 sessions. They've got a CIO, automation council and a pickleball court inside this hall, which pickleball is, you know, all the rage. So Bobby, Patrick and Mary Telo kicked it off. Bobby's the cmo, Mary's the head of branding, and Bobby raised four themes. It it, this is a tool that it's, this is RPA is going from a tool to a way of operating and innovating. >>The second thing is, the big news here is the UI path business platform, something like that. They're calling, but they're talking about about platform and they're really super gluing that to digital transformation. The third is really outcomes shifting from tactical. I have a robot, a software robot on my desk doing, you know, mimicking what I do with the script to something that's transformative. We're seeing this operationalized very deeply. We'll go into some examples. And then the fourth theme is automation is being featured as a strategic line item in annual reports. Bobby Patrick, as he left the stage, I think he was commenting on my piece where I said that RPA automation is more discretionary than some other things. He said, this is not discretionary, it's strategic. You know, unfortunately when you're heading into a recession, you can, you can put off some of the more strategic items. However, the flip side of that, Dave, is as they were saying before, if you're gonna, if if you're, if you're looking at five to 7% inflation may be a way to attack that is with automation. Yeah. >>There's no question, there's no question that automation is a way to attack that. There's no question that automation is critical moving forward. There's no question that we have moved. We're in the, you know, we're, we're still in the age of cloud, but automation is gonna be absolutely critical. The question is, what will UI path's role be in that market? And, and, and when you hear, when you hear UI path talk about platform versus tool sets and things like that, that's a critical differentiator because if they are just a tool, then why wouldn't someone exploit a tool that is within an application environment instead of exploiting a platform? So what I'm gonna be looking for in terms of the, the folks we talked to over the next few days is this question of, you know, make the case that this is actually a platform that extends across all kinds of application environments. If they can't seize that high ground moving forward, it's it's gonna be, it's gonna be tough for them. >>Well, they're betting the company on >>That, that's Rob Ensslin coming in. That's why he's part of the, the equation. But >>That platform play is they are betting the company. And, and the reason is, so the, the, the history here is in the early days of this sort of RPA craze, Automation Anywhere and UI path went out, they both raised a ton of money. UI Path rocketed out to the lead. They had a much e easier to install, you know, Automation Anywhere, Blue Prism, some of the other legacy business process folks, you know, kind of had on-prem, Big Stacks, UiPath came in a really simple self-serve platform and took off and really got a foothold in the market. And then started building or or making some of these acquisitions like Process Gold, like cloud elements, which is API automation. More recently Reiner, We, which is natural language processing. We heard them up on the stage today and they've been putting that together to do not just rpa but process mining, task mining, you know, document automation, et cetera. >>And so Rob Ins insulin was brought in from Google, formerly Google and SAP, to really provide that sort of financial and go to market expertise as well as Shim Gupta who's, who's the cfo. So they, they, and they were kinda late with that. They sort of did all this post ipo. I wish they had done it, you know, somewhat beforehand, but they're sort of bringing in that adult supervision supervision that's necessary. Rob Sland, I thought was very cogent. He was assertive on stage, he was really clear, he was energetic. He talked about the phases, e r p, Internet cloud and the now automation is a new S-curve. He quoted a Forester analyst talking about that. He also had a great quote. He said, you know, the old adage better, faster, cheaper, pick two. He said, You don't have to do that anymore with automation. He cited reports from analysts, 50% efficiency improvement, 40% productivity improvement, 40% improvement in customer satisfaction. >>And then what I always, again, love about UiPath is they're no shortage of customers. They do as good a job as anybody, and I think I would say the best of, of, of getting customers to talk about their experiences. You'll see that on the cube all this week, talked about Changi airport from Singapore. They're adding 50 able to service 50 million new customers, new travelers with no new headcount company called Vital or retail. And how you say that a hundred thousand employees having access to it. Uber, 150% ROI in one year. New York state getting 1.2 million relief checks out in two weeks and identifying potentially 12 billion in fraud. They also talk about 25% of the, of the UI path finance team is digital. And they've, they've only incremented headcount, you know, very slightly one and a half times their revenue's grown. What a 10 x? And really he talked about how to, for how to turn automation into a force multiplier for growth. And to your point, I think that's their challenge. What were your thoughts on Rob ens insulin's keynote? >>First of all, in addition to his background, Rob brings a brand with him. Rob Ensslin is a brand, and that brand is enterprise overarching platform. Someone you go to for that platform play, not for a tool set. And again, I'll, I'll say it again. It's critically important that they, that they demonstrate this to the marketplace, that they are a platform worth embracing as opposed to simply a tool set. Because the large enterprise software providers are going to provide their own tool sets within their platforms. And if you can't convince someone that it's worth doing two things instead of one thing, you're, you're, you're never gonna make it. So I've had experiences with Rob when he was at Google. He's, he's, he's the right person for the job and I, and I I I buy into his strategy and narrative about where we are and the critical nature of automation question remains, will you I path to be able to benefit from that trend. >>So a couple things on that. So your point about sap, you know, is right on EY was up on stage. They, EY is a huge SAP customer and they chose UI path to automate their SAP installation, right? And they're going all in with UI path as a partner. Of course. I I often like to say that the global system integrators, they like to eat at the trough, right? When you see GSIs like EY and others coming into the ecosystem, that means there's business being done. We saw Orange up on stage, which was really interesting. >>Javier from Spain. Yeah. Yep. >>Talking about he had this really cool dashboard and then Ted Coomer was talking about the business automation platform and all the different chapters and the evolution. They've gotta get to a platform play because the thing I failed to mention is Microsoft a couple years ago made a tuck in acquisition and got it to this market really providing individual automations and making it, you know, it's Microsoft, they're gonna make it really easy to add it really >>Cheaply. SAP would tell you that they have the same thing and, >>And then, and then just grow from that. So UiPath has to pivot to a platform play. They started this back in 2019, but as you know, it takes a long time to integrate stuff. Okay. So they're, they're, they're working through that. But this is, you know, Rob ends and put up on the, the slide go big, I, I tweeted, took a page outta Michael Dell. Go big or go home. Final thoughts before we break? >>I think go big or go home is pretty much sums it up. I mean this is, this is an existential mission that UiPath is on right now, starting to stay forward. They need to seize that high ground of platform versus tool set. Otherwise they will never get beyond where they are now. I I I, I do wanna mention too, to folks in the audience, there's a huge difference between a billion dollar valuation and a billion dollars in revenue every year. So, so, you know, these, these guys have reached a milestone, there's no question about that. But to get to that next level platform, platform, platform, and I know we'll be, we'll be probing our guests on that question over the next couple years. >>Yeah. And the key is obviously gonna be keep servicing the customers, you know, all the financial machinations and you know, they reduced yesterday their guidance from the high end being 25% ARR growth down to roughly 20% when you, when you factor out currency conversions. UiPath has a lot of business overseas. They're taking that overseas revenue and converting it back to dollars though dollars are appreciated. So they're less of them. I know this is kind of the inside baseball, but, but we're gonna get into that over the next two days. Dave Ante and Dave, you're watching the Cubes coverage of UI path forward, five from Las Vegas. We'll be right back, right after this short break.

>>From around the globe. It's the cube with digital coverage, a BizOps manifesto unveiled brought to you by biz ops coalition. >>Hey, welcome back everybody. Jeff Frick here with the cube. Welcome back to our ongoing coverage of the biz ops manifesto. Unveil. Something has been in the works for a little while. Today's the formal unveiling, and we're excited to have three of the core founding members of the manifesto authors of the manifesto. If you will, uh, joining us again, we've had them all on individually. Now we're going to have a great power panel. First up. We're gonna have Mitt Kirsten returning he's the founder and CEO of Tasktop mic. Good to see you again. Where are you dialing in from? >>Great to see you again, Jeff I'm dialing from Vancouver, >>We're Canada, Vancouver, Canada. One of my favorite cities in the whole wide world. Also we've got Tom Davenport come in from across the country. He's a distinguished professor and author from Babson college, Tom. Great to see you. And I think you said you're at a fun, exotic place on the East coast >>Realm of Memphis shoes. That's on Cape Cod. >>Great to see you again and also joining surge Lucio. He is the VP and general manager enterprise software division at Broadcom surge. Great to see you again, where are you coming in from? >>Uh, from Boston right next to Cape Cod. >>Terrific. So welcome back, everybody again. Congratulations on this day. I know it's been a lot of work to get here for this unveil, but let's just jump into it. The biz ops manifesto, what was the initial reason to do this? And how did you decide to do it in a kind of a coalition, a way bringing together a group of people versus just making it an internal company, uh, initiative that, you know, you can do better stuff within your own company, surge, why don't we start with you? >>Yeah, so, so I think we were at a really critical juncture, right? Many, um, large enterprises are basically struggling with their digital transformation. Um, in fact, um, many recognized that, uh, the, the business side, it collaboration has been, uh, one of the major impediments, uh, to drive that kind of transformation. That, and if we look at the industry today, many people are, whether we're talking about vendors or, um, you know, system integrators, consulting firms are talking about the same kind of concepts, but using very different language. And so we believe that bringing all these different players together, um, as part of the coalition and formalizing, uh, basically the core principles and values in a BizOps manifesto, we can really start to F could have a much bigger movement where we can all talk about kind of the same concepts and we can really start to provide, could have a much better support for large organizations to, to transform. Uh, so whether it is technology or services or, um, or training, I think that that's really the value of bringing all of these players together, right. >>And mic to you. Why did you get involved in this, in this effort? >>So I've been closely involved the agile movement since it started two decades with that manifesto. And I think we got a lot of improvement at the team level, and I think that was just no. Did we really need to improve at the business level? Every company is trying to become a software innovator, trying to make sure that they can pivot quickly and the changing market economy and what everyone's dealing with in terms of needing to deliver value to customers sooner. However, agile practices have really focused on these metrics, these measures and understanding processes that help teams be productive. Those things now need to be elevated to the business as a whole. And that just hasn't happened. Uh, organizations are actually failing because they're measuring activities and how they're becoming more agile, how teams are functioning, not how much quickly they're delivering value to the customer. So we need to now move past that. And that's exactly what the manifesto provides. Right, >>Right, right. And Tom, to you, you've been covering tech for a very long time. You've been looking at really hard challenges and a lot of work around analytics and data and data evolution. So there's a definitely a data angle here. I wonder if you could kind of share your perspective of what you got excited to, uh, to sign onto this manifesto. >>Sure. Well, I have, you know, for the past 15 or 20 years, I've been focusing on data and analytics and AI, but before that I was a process management guy and a knowledge management guy. And in general, I think, you know, we've just kind of optimize that to narrow a level, whether you're talking about agile or dev ops or ML ops, any of these kinds of ops oriented movements, we're making individual project, um, performance and productivity better, but we're not changing the business, uh, effectively enough. And that's the thing that appealed to me about the biz ops idea, that we're finally creating a closer connection between what we do with technology and how it changes the business and provides value to it. >>Great. Uh, surge back to you, right? I mean, people have been talking about digital transformation for a long time and it's been, you know, kind of trucking along and then covert hit and it was instant Lightswitch. Everyone's working from home. You've got a lot more reliance on your digital tools, digital communication, uh, both within your customer base and your partner base, but also then your employees when you're, if you could share how that really pushed this all along. Right? Because now suddenly the acceleration of digital transformation is higher. Even more importantly, you got much more critical decisions to make into what you do next. So kind of your portfolio management of projects has been elevated significantly when maybe revenues are down, uh, and you really have to, uh, to prioritize and get it right. >>Yeah. Maybe I'll just start by quoting Satina Nello basically recently said that they're speeding the two years of digital preservation just last two months in any many ways. That's true. Um, but yet when we look at large enterprises, they're still struggling with a kind of a changes in culture. They really need to drive to be able to disrupt themselves. And not surprisingly, you know, when we look at certain parts of the industry, you know, we see some things which are very disturbing, right? So about 40% of the personal loans today are being, uh, origin data it's by fintechs, uh, of a like of Sophie or, uh, or a lending club, right? Not to a traditional brick and mortar for BEC. And so the, well, there is kind of a much more of an appetite and it's a, it's more of a survival type of driver these days. >>Uh, the reality is that's in order for these large enterprises to truly transform and engage on this digital transformation, they need to start to really align the business nightie, you know, in many ways and make cover. Does agile really emerge from the core desire to truly improve software predictability between which we've really missed is all the way we start to aligning the software predictability to business predictability, and to be able to have continual sleep continuous improvement and measurement of business outcomes. So by aligning that of these, uh, discuss inward metrics, that's, it is typically being using to business outcomes. We think we can start to really ELP, uh, different stakeholders within the organization to collaborate. So I think there is more than ever. There's an imperative to acts now. Um, and, and resolves, I think is kind of the right approach to drive that kind of transformation. Right. >>I want to follow up on the culture comment, uh, with you, Tom, because you've talked before about kind of process flow and process flow throughout a whore and an organization. And, you know, we talk about people process and tech all the time. And I think the tech is the easy part compared to actually changing the people the way they think. And then the actual processes that they put in place. It's a much more difficult issue than just the tech issue to get this digital transformation in your organization. >>Yeah. You know, I've always found that the soft stuff about, you know, the culture of a behavior, the values is the hard stuff to change and more and more, we, we realized that to be successful with any kind of digital transformation you have to change people's behaviors and attitudes. Um, we haven't made as much progress in that area as we might have. I mean, I've done some surveys suggesting that most organizations still don't have data driven cultures. And in many cases there is a lower percentage of companies that say they have that then, um, did a few years ago. So we're kind of moving in the wrong direction, which means I think that we have to start explicitly addressing that, um, cultural, behavioral dimension and not just assuming that it will happen if we, if we build system, if we build it, they won't necessarily come. Right. >>Right. So I want to go to you Nick. Cause you know, we're talking about workflows and flow, um, and, and you've written about flow both in terms of, um, you know, moving things along a process and trying to find bottlenecks, identify bottlenecks, which is now even more important again, when these decisions are much more critical. Cause you have a lot less, uh, wiggle room in tough times, but you also talked about flow from the culture side and the people side. So I wonder if you can just share your thoughts on, you know, using flow as a way to think about things, to get the answers better. >>Yeah, absolutely. And I'll refer back to what Tom has said. If you're optimized, you need to optimize your system. You need to optimize how you innovate and how you deliver value to the business and the customer. Now, what we've noticed in the data, since that we've learned from customers, value streams, enterprise organizations, value streams, is that when it's taking six months at the end to deliver that value with the flow is that slow. You've got a bunch of unhappy developers, unhappy customers when you're innovating half so high performing organizations, we can measure third and 10 float time and dates. All of a sudden that feedback loop, the satisfaction your developer's measurably goes up. So not only do you have people context, switching glass, you're delivering so much more value to customers at a lower cost because you've optimized for flow rather than optimizing for these other approximate tricks that we use, which is how efficient is my agile team. How quickly can we deploy software? Those are important, but they do not provide the value of agility of fast learning of adaptability to the business. And that's exactly what the biz ops manifesto pushes your organization to do. You need to put in place this new operating model that's based on flow on the delivery of business value and on bringing value to market much more quickly than you were before. Right. >>I love that. And I'm going back to you, Tom, on that to follow up. Cause I think, I don't think people think enough about how they prioritize what they're optimizing for. Cause you know, if you're optimizing for a versus B, you know, you can have a very different product that you kick out and let you know. My favorite example is with Clayton Christianson and innovator's dilemma talking about the three inch hard drive. If you optimize it for power, you know, is one thing, if you optimize it for vibration is another thing and sure enough, you know, they missed it on the poem because it was the, it was the game console, which, which drove that whole business. So when you, when you're talking to customers and we think we hear it with cloud all the time, people optimizing for cost efficiency, instead of thinking about it as an innovation tool, how do you help them kind of rethink and really, you know, force them to, to look at the, at the prioritization and make sure they're prioritizing on the right thing is make just said, what are you optimizing for? >>Oh yeah. Um, you have one of the most important aspects of any decision or, um, attempt to resolve a problem in an organization is the framing process. And, um, you know, it's, it's a difficult aspect of the decision to frame it correctly in the first place. Um, there, it's not a technology issue. In many cases, it's largely a human issue, but if you frame that decision or that problem incorrectly to narrowly say, or you frame it as an either or situation where you could actually have some of both, um, it, it's very difficult for the, um, process to work out correctly. So in many cases that I think we need to think more at the beginning about how we bring this issue or this decision in the best way possible before we charge off and build a system to support it. You know, um, it's worth that extra time to think, think carefully about how the decision has been structured, right >>Surgery. I want to go back to you and talk about the human factors because as we just discussed, you can put it in great technology, but if the culture doesn't adopt it and people don't feel good about it, you know, it's not going to be successful and that's going to reflect poorly on the technology, even if it had nothing to do with it. And you know, when you look at the, the, the core values, uh, of the Bezos manifesto, you know, a big one is trust and collaboration, you know, learn, respond and pivot. I wonder if you can share your thoughts on, on trying to get that cultural shift, uh, so that you can have success with the people or excuse me, with the technology in the process and helping customers, you know, take this more trustworthy and kind of proactive, uh, position. >>So I think, I think at the ground level, it truly starts with the realization that we're all different. We come from different backgrounds. Um, oftentimes we tend to blame the data. It's not uncommon my experiments that we spend the first 30 minutes of any kind of one hour conversation to debate the validity of the data. Um, and so, um, one of the first kind of, uh, probably manifestations that we've had or revelations as we start to engage with our customers is spike, just exposing, uh, high-fidelity data sets to different stakeholders from their different lens. We start to enable these different stakeholders to not debate the data. That's really collaborate to find a solution. So in many ways, when, when, when we think about kind of the types of changes we're trying to, to truly affect around data driven decision making, it's all about bringing the data in context, in the context that is relevant and understandable for, for different stakeholders, whether we're talking about an operator or develop for a business analyst. >>So that's, that's the first thing. The second layer I think, is really to provide context to what people are doing in their specific cycle. And so I think one of the best examples I have is if you start to be able to align business KPI, whether you are counting, you know, sales per hour, or the engagements of your users on your mobile applications, whatever it is, you can start to connect that PKI to the business KPI, to the KPIs that developers might be looking at, whether it is the number of defects or a velocity or whatever, you know, metrics that they are used to to actually track you start to, to be able to actually contextualize in what we are the effecting, basically a metric that is really relevant in which we see is that DC is a much more systematic way to approach the transformation than say, you know, some organizations kind of creating, uh, some of these new products or services or initiatives, um, to, to drive engagements, right? >>So if you look at zoom, for instance, zoom giving away a it service to, uh, to education, he's all about, I mean, there's obviously a marketing aspect in therapists. It's fundamentally about trying to drive also the engagement of their own teams. And because now they're doing something for good and the organizations are trying to do that, but you only can do this kind of things in a limited way. And so you really want to start to rethink how you connect to, everybody's kind of a business objective fruit data, and now you start to get people to stare at the same data from their own lens and collaborate on all the data. Right, >>Right. That's a good, uh, Tom, I want to go back to you. You've been studying it for a long time, writing lots of books and getting into it. Um, why now, you know, what w why now are we finally aligning business objectives with, with it objectives? You know, why didn't this happen before? And, you know, what are the factors that are making now the time for this, this, this move with the, uh, with the biz ops? >>Well, and much of the past, it was sort of a back office related activity. And, you know, it was important for, um, uh, producing your paychecks and, uh, um, capturing the customer orders, but the business wasn't built around it now, every organization needs to be a software business, a data business, a digital business, the auntie has been raised considerably. And if you aren't making that connection between your business objectives and the technology that supports it, you run a pretty big risk of, you know, going out of business or losing out to competitors. Totally. So, um, and, uh, even if you're in a, an industry that hasn't historically been terribly, um, technology oriented customer expectations flow from, uh, you know, the digital native, um, companies that they work with to basically every industry. So you're compared against the best in the world. So we don't really have the luxury anymore of screwing up our it projects or building things that don't really work for the business. Um, it's mission critical that we do that well. Um, almost every time, I just want to follow up by that, Tom, >>In terms of the, you've talked extensively about kind of these evolutions of data and analytics from artismal stage to the big data stage, the data economy stage, the AI driven stage and what I find diff interesting that all those stages, you always put a start date. You never put an end date. Um, so you know, is the, is the big data I'm just going to use that generically a moment in time finally here, where we're, you know, off mahogany row with the data scientists, but actually can start to see the promise of delivering the right insight to the right person at the right time to make that decision. >>Well, I think it is true that in general, these previous stages never seemed to go away. The, um, the artisinal stuff is still being done, but we would like for less than less of it to be artisinal, we can't really afford for everything to be artisinal anymore. It's too labor and time consuming to do things that way. So we shift more and more of it to be done through automation and B to be done with a higher level of productivity. And, um, you know, at some point maybe we reached the stage where we don't do anything artisanally anymore. I'm not sure we're there yet, but, you know, we are, we are making progress. Right, >>Right. And Mick, back to you in terms of looking at agile, cause you're, you're such a, a student of agile when, when you look at the opportunity with ops, um, and taking the lessons from agile, you know, what's been the inhibitor to stop this in the past. And what are you so excited about? You know, taking this approach will enable. >>Yeah. I think both Sergeant Tom hit on this is that in agile what's happened is that we've been measuring tiny subsets of the value stream, right? We need to elevate the data's there. Developers are working on these tools that delivering features that the foundations for, for great culture are there. I spent two decades as a developer. And when I was really happy is when I was able to deliver value to customers, the quicker I was able to do that the fewer impediments are in my way, that quicker was deployed and running in the cloud, the happier I was, and that's exactly what's happening. If we can just get the right data, uh, elevated to the business, not just to the agile teams, but really these values of ours are to make sure that you've got these data driven decisions with meaningful data that's oriented around delivering value to customers. Not only these legacies that Tom touched on, which has cost center metrics from an ITK, from where, for it being a cost center and something that provided email and then back office systems. So we need to rapidly shift to those new, meaningful metrics that are customized business centric and make sure that every development the organization is focused on those as well as the business itself, that we're measuring value and that we're helping that value flow without interruptions. >>I love that mic. Cause if you don't measure it, you can't improve on it and you gotta, but you gotta be measuring the right thing. So gentlemen, uh, thank you again for, for your time. Congratulations on the, uh, on the unveil of the biz ops manifesto and together this coalition >>Of, of, uh, industry experts to get behind this. And, you know, there's probably never been a more important time than now to make sure that your prioritization is in the right spot and you're not wasting resources where you're not going to get the ROI. So, uh, congratulations again. And thank you for sharing your thoughts with us here on the cube. Alright, so we had surge, Tom and Mick I'm. Jeff, you're watching the cube, it's a biz ops manifesto and unveil. Thanks for watching. We'll see you next time >>From around the globe. It's the cube with digital coverage of BizOps manifesto, unveiled brought to you by biz ops coalition and welcome back Friday, Jeff Frick here with the cube we're in our Palo Alto studios. And we'd like to welcome you back to our continuing coverage of biz ops manifesto, unveil exciting day to really, uh, kind of bring this out into public. There's been a little bit of conversation, but today's really the official unveiling and we're excited to have our next guest to share a little bit more information on it. He's Patrick tickle. He's a chief product officer for planned view. Patrick. Great to see you. Yeah, it's great to be here. Thanks for the invite. So why the biz ops manifesto, why the biz optical edition now when you guys have been at it, it's relatively mature marketplace businesses. Good. What was missing? Why, why this, uh, why this coalition? >>Yeah, so, you know, again, why is, why is biz ops important and why is this something I'm, you know, I'm so excited about, but I think companies as well, right. Well, you know, in some ways or another, this is a topic that I've been talking to, you know, the market and our customers about for a long time. And it's, you know, I really applaud, you know, this whole movement, right. And, um, in resonates with me, because I think one of the fundamental flaws, frankly, of the way we've talked about technology and business literally for decades, uh, has been this idea of, uh, alignment. Those who know me, I occasionally get off on this little rant about the word alignment, right. But to me, the word alignment is, is actually indicative of the, of the, of the flaw in a lot of our organizations and biz ops is really, I think now trying to catalyze and expose that flaw. >>Right. Because, you know, I always say that, you know, you know, alignment implies silos, right. Instantaneously, as soon as you say there's alignment, there's, there's obviously somebody who's got a direction and other people that have to line up and that, that kind of siloed, uh, nature of organizations. And then frankly, the passive nature of it. Right. I think so many technology organizations are like, look, the business has the strategy you guys need to align. Right. And, and, you know, as a product leader, right. That's where I've been my whole career. Right. I can tell you that I never sit around. I almost never use the word alignment. Right. I mean, whether I never sit down and say, you know, the product management team has to get aligned with Deb, right. Or the dev team has to get aligned with the delivery and ops teams. I mean, what I say is, you know, are we on strategy, right? >>Like we've, we have a strategy as a, as a full end to end value stream. Right. And that there's no silos. And I mean, look, every on any given day we got to get better. Right. But the context, the context we operate is not about alignment. Right. It's about being on strategy. And I think I've talked to customers a lot about that, but when I first read the manifesto, I was like, Oh yeah, this is exactly. This is breaking down. Maybe trying to eliminate the word alignment, you know, from a lot of our organizations, because we literally start thinking about one strategy and how we go from strategy to delivery and have it be our strategy, not someone else's that we're all aligning to it. And it's a great way to catalyze that conversation. That I've, it's been in my mind for years, to be honest. Right. >>So, so much to unpack there. One of the things obviously, uh, stealing a lot from, from dev ops and the dev ops manifesto from 20 years ago. And as I look through some of the principles and I looked through some of the values, which are, you know, really nicely laid out here, you know, satisfy customers, do continuous delivery, uh, measure, output against real results. Um, the ones that, that jumps out though is really about, you know, change, change, right? Requirements should change frequently. They do change frequently, but I'm curious to get your take from a, from a software development point, it's easy to kind of understand, right. We're making this widget and our competitors, beta widget plus X, and now we need to change our plans and make sure that the plus X gets added to the plan. Maybe it wasn't in the plan, but you talked a lot about product strategy. So in this kind of continuous delivery world, how does that meld with, I'm actually trying to set a strategy, which implies the direction for a little bit further out on the horizon and to stay on that while at the same time, you're kind of doing this real time continual adjustments. Cause you're not working off a giant PRD or MRD anymore. >>Yeah, yeah, totally. Yeah. You know, one of the terms, you know, that we use internally a lot and even with my customers, our customers is we talked about this idea of rewiring, right. And I think, you know, it's kind of a, now an analogy for transformation. And I think a lot of us have to rewire the way we think about things. Right. And I think at Planview where we have a lot of customers who live in that, you know, who operationalize that traditional PPM world. Right. And are shifting to agile and transforming that rewire is super important. And, and to your point, right, it's, you've just, you've got to embrace this idea of, you know, just iterative getting better every day and iterating, iterating, iterating as to building annual plans or, you know, I get customers occasionally who asked me for two or three year roadmap. >>Right. And I literally looked at them and I go, there's no, there's no scenario where I can build a two or three year roadmap. Right. You, you, you think you want that, but that's not, that's not the way we run. Right. And I will tell you the biggest thing that for us, you know, that I think is matched the planning, uh, you know, patents is a word I like to use a lot. So the thing that we've like, uh, that we've done from a planning perspective, I think is matched impedance to continuous delivery is instituting the whole program, implement, you know, the program, increment planning, capabilities and methodologies, um, in the scaled agile world. Right. And over the last 18 months to two years, we really have now, you know, instrumented our company across three value streams. You know, we do quarterly PI program increment 10 week planning, you know, and that becomes, that becomes the Terra firma of how we plant. >>Right. And it's, what are we doing for the next 10 weeks? And we iterate within those 10 weeks, but we also know that 10 weeks from now, we're going to, we're going to adjust iterate again. Right. And that shifting of that planning model, you know, to being as cross-functional is that as that big room planning kind of model is, um, and also, uh, you know, on that shorter increment, when you get those two things in place, all sudden the impedance really starts to match up, uh, with continuous delivery and it changes, it changes the way you plan and it changes the way you work. Right? >>Yeah. Their thing. Right. So obviously a lot of these things are kind of process driven, both within the values, as well as the principles, but there's a whole lot, really about culture. And I just want to highlight a couple of the values, right? We already talked about business outcomes, um, trust and collaboration, uh, data driven decisions, and then learn, respond and pivot. Right. A lot of those are cultural as much as they are process. So again, is it the, is it the need to really kind of just put them down on paper and you know, I can't help, but think of, you know, the hammering up the, uh, the thing in the Lutheran church with their, with their manifesto, is it just good to get it down on paper? Because when you read these things, you're like, well, of course we should trust people. And of course we need an environment of collaboration and of course we want data driven decisions, but as we all know saying it and living, it are two very, very different things. >>Yeah. Good question. I mean, I think there's a lot of ways you bring that to life you're right. And just hanging up, you know, I think we've all been through the hanging up posters around your office, which these days, right. Unless you're going to hang a poster and everybody's home office. Right. You can't even, you can't even fake it that you think that might work. Right. So, um, you know, you really, I think we've attacked that in a variety of ways. Right. And you definitely have to, you know, you've got to make the shift to a team centric culture, right. Empowered teams, you know, that's a big deal. Right. You know, a lot of, a lot of the people that, you know, we lived in a world of quote unquote, where we were lived in a deep resource management world for a long, long time. >>And right. A lot of our customers still do that, but you know, kind of moving to that team centric world is, uh, is really important and core the trust. Um, I think training is super important, right. We've, you know, we've internally, right. We've trained hundreds employees over the last a year and a half on the fundamentals really of safe. Right. Not necessarily, you know, we've had, we've had teams delivering in scrum and the continuous delivery for, you know, for years, but the scaling aspect of it, uh, is where we've done a lot of training and investment. Um, and then, you know, I think, uh, leadership has to be bought in. Right. You know? And so when we pie plan, you know, myself and Cameron and the other members of our leadership, you know, we're NPI planning, you know, for, for four days. Right. I mean, it's, it's, you've got to walk the walk, you know, from top to bottom and you've got to train on the context. Right. And then you, and then, and, and then once you get through a few cycles where you've done a pivot, right. Or you brought a new team in, and it just works, it becomes kind of this virtuous circle where he'll go, man, this really works so much better than what we used to do. Right. >>Right. The other really key principle to this whole thing is, is aligning, you know, the business leaders and the business prioritization, um, so that you can get to good outcomes with the development and the delivery. Right. And we, we know again, and kind of classic dev ops to get the dev and the production people together. So they can, you know, quickly ship code that works. Um, but adding the business person on there really puts, puts a little extra responsibility that they, they understand the value of a particular feature or particular priority. Uh, they, they can make the, the, the trade offs and that they kind of understand the effort involved too. So, you know, bringing them into this continuous again, kind of this continuous development process, um, to make sure that things are better aligned and really better prioritize. Cause ultimately, you know, we don't live in an infinite resources situation and people got to make trade offs. They got to make decisions as to what goes and what doesn't go in for everything that goes. Right. I always say you pick one thing. Okay. That's 99 other things that couldn't go. So it's really important to have, you know, this, you said alignment of the business priorities as well as, you know, the execution within, within the development. >>Yeah. I think that, you know, uh, you know, I think it was probably close to two years ago. Forester started talking about the age of the customer, right. That, that was like their big theme at the time. Right. And I think to me what that, the age of the customer actually translates to and Mick, Mick and I are both big fans of this whole idea of the project and product shift, mixed book, you know, it was a great piece on a, you're talking about, you know, as part of the manifesto is one of the authors as well, but this shift from project to product, right? Like the age of the customer, in my opinion, the, the embodiment of that is the shift to a product mentality. Right. And, and the product mentality in my opinion, is what brings the business and technology teams together, right? >>Once you, once you're focused on a customer experience is delivered through a product or a service. That's when I that's, when I started to go with the alignment problem goes away, right. Because if you look at software companies, right, I mean, we run product management models yeah. With software development teams, customer success teams, right. That, you know, the software component of these products that people are building is obviously becoming bigger and bigger, you know, in an, in many ways, right. More and more organizations are trying to model themselves over as operationally like software companies. Right. Um, they obviously have lots of other components in their business than just software, but I think that whole model of customer experience equaling product, and then the software component of product, the product is the essence of what changes that alignment equation and brings business and teams together because all of a sudden, everyone knows what the customer's experiencing. Right. And, and that, that, that makes a lot of things very clear, very quickly. >>Right. I'm just curious how far along this was as a process before, before COBIT hit, right. Because serendipitous, whatever. Right. But the sudden, you know, light switch moment, everybody had to go work from home and in March 15th compared to now we're in October and this is going to be going on for a while. And it is a new normal and whatever that whatever's going to look like a year from now, or two years from now is TBD, you know, had you guys already started on this journey cause again, to sit down and actually declare this coalition and declare this manifesto is a lot different than just trying to do better within your own organization. >>Yeah. So we had started, uh, you know, w we definitely had started independently, you know, some, some, you know, I think people in the community know that, uh, we, we came together with a company called lean kit a handful of years ago, and I give John Terry actually one of the founders LeanKit immense credit for, you know, kind of spearheading our cultural change and not, and not because of, we were just gonna be, you know, bringing agile solutions to our customers, but because, you know, he believed that it was going to be a fundamentally better way for us to work. Right. And we kind of, you know, we started with John and built, you know, out of concentric circles of momentum and, and we've gotten to the place where now it's just part of who we are, but, but I do think that, you know, COVID has, you know, um, I think pre COVID a lot of companies, you know, would, would adopt, you know, the would adopt digital slash agile transformation. >>Um, traditional industries may have done it as a reaction to disruption. Right. You know, and in many cases, the disruption to these traditional industries was, I would say a product oriented company, right. That probably had a larger software component, and that disruption caused a competitive issue, uh, or a customer issue that caused companies and tried to respond by transforming. I think COVID, you know, all of a sudden flatten that out, right. We literally all got disrupted. Right. And so all of a sudden, every one of us is dealing with some degree of market uncertainty, customer uncertainty, uh, and also, you know, none of us were insulated from the need to be able to pivot faster, deliver incrementally, you know, and operate in a different, completely more agile way, uh, you know, post COVID. Right. Yeah. That's great. >>So again, a very, very, very timely, you know, a little bit of serendipity, a little bit of planning. And, you know, as, as with all important things, there's always a little bit of lock in, uh, and a lot of hard work involved. So a really interesting thank you for, for your leadership, Patrick. And, you know, it really makes a statement. I think when you have a bunch of leaderships across an industry coming together and putting their name on a piece of paper, uh, that's aligned around us some principles and some values, which again, if you read them who wouldn't want to get behind these, but if it takes, you know, something a little bit more formal, uh, to kind of move the ball down the field, and then I totally get it and a really great work. Thanks for, uh, thanks for doing it. >>Oh, absolutely. No. Like I said, the first time I read it, I was like, yep. Like you said, this is all, it's all makes complete sense, but just documenting it and saying it and talking about it moves the needle. I'll tell you as a company, you gotta, we're pushing really hard on, uh, you know, on our own internal strategy on diversity and inclusion. Right. And, and like, once we wrote the words down about what, you know, what we aspire to be from a diversity and inclusion perspective, it's the same thing. Everybody reads the words that goes, why wouldn't we do this? Right. But until you write it down and kind of have again, a manifesto or a Terra firma of what you're trying to accomplish, you know, then you can rally behind it. Right. As opposed to it being something that's, everybody's got their own version of the flavor. Right. And I think it's a very analogous, you know, kind of, uh, initiative. Right. And, uh, and it's happening, both of those things right. Are happening across the industry these days. Right. >>And measure it too. Right. And measure it, measure, measure, measure, get a baseline. Even if you don't like to measure, even if you don't like what the, even if you can argue against the math, behind the measurement, measure it. And at least you can measure it again and you can, and you've got some type of a comp and that is really the only way to, to move it forward. We're Patrick really enjoyed the conversation. Thanks for, uh, for taking a few minutes out of your day. >>It's great to be here. It's an awesome movement and we're glad to be a part of it. >>All right. Thanks. And if you want to check out the biz ops, Manifesta go to biz ops, manifesto.org, read it. You might want to sign it. It's there for you. And thanks for tuning in on this segment will continuing coverage of the biz op manifesto unveil you're on the cube. I'm Jeff, thanks for watching >>From around the globe. It's the cube with digital coverage of biz ops manifesto unveiled brought to you by biz ops coalition. >>Hey, welcome back, everybody Jeffrey here with the cube. We're coming to you from our Palo Alto studios. And welcome back to this event is the biz ops manifesto unveiling. So the biz ops manifesto and the biz ops coalition had been around for a little while, but today's the big day. That's kind of the big public unveiling, or we're excited to have some of the foundational people that, you know, have put their, put their name on the dotted, if you will, to support this initiative and talk about why that initiative is so important. And so the next guest we're excited to have is dr. Mick Kirsten. He is the founder and CEO of Tasktop mic. Great to see you coming in from Vancouver, Canada, I think, right? Yes. Great to be here, Jeff. Thank you. Absolutely. I hope your air is a little better out there. I know you had some of the worst air of all of us, a couple, a couple of weeks back. So hopefully things are, uh, are getting a little better and we get those fires under control. Yeah. >>Things have cleared up now. So yeah, it's good. It's good to be close to the U S and it's going to have the Arabic cleaner as well. >>Absolutely. So let's, let's jump into it. So you you've been an innovation guy forever starting way back in the day and Xerox park. I was so excited to do an event at Xerox park for the first time last year. I mean, that, that to me represents along with bell labs and, and some other, you know, kind of foundational innovation and technology centers, that's gotta be one of the greatest ones. So I just wonder if you could share some perspective of getting your start there at Xerox park, you know, some of the lessons you learned and what you've been able to kind of carry forward from those days. >>Yeah. I was fortunate to join Xerox park in the computer science lab there at a fairly early point in my career, and to be working on open source programming languages. So back then in the computer science lab, where some of the inventions around programming around software development games, such as object programming, and a lot of what we had around really modern programming levels constructs, those were the teams I had the fortunate of working with, and really our goal was. And of course, there's, as, as you noticed, there's just this DNA of innovation and excitement and innovation in the water. And really it was the model that was all about changing the way that we work was looking at for how we can make it 10 times easier to white coat. But this is back in 99. And we were looking at new ways of expressing, especially business concerns, especially ways of enabling people who are wanting to innovate for their business to express those concerns in code and make that 10 times easier than what that would take. >>So we create a new open source programming language, and we saw some benefits, but not quite quite what we expected. I then went and actually joined Charles Stephanie, that former to fucking from Microsoft who was responsible for, he actually got Microsoft word as a sparking into Microsoft and into the hands of bill Gates and that company that was behind the whole office suite and his vision. And then when I was trying to execute with, working for him was to make PowerPoint like a programming language to make everything completely visual. And I realized none of this was really working, that there was something else, fundamentally wrong programming languages, or new ways of building software. Like let's try and do with Charles around intentional programming. That was not enough. >>That was not enough. So, you know, the agile movement got started about 20 years ago, and we've seen the rise of dev ops and really this kind of embracing of, of, of sprints and, you know, getting away from MRDs and PRDs and these massive definitions of what we're going to build and long build cycles to this iterative process. And this has been going on for a little while. So what was still wrong? What was still missing? Why the biz ops coalition, why the biz ops manifesto? >>Yeah, so I basically think we nailed some of the things that the program language levels of teams can have effective languages deployed to soften to the cloud easily now, right? And at the kind of process and collaboration and planning level agile two decades, decades ago was formed. We were adopting and all the, all the teams I was involved with and it's really become a self problem. So agile tools, agile teams, agile ways of planning, uh, are now very mature. And the whole challenge is when organizations try to scale that. And so what I realized is that the way that agile was scaling across teams and really scaling from the technology part of the organization to the business was just completely flawed. The agile teams had one set of doing things, one set of metrics, one set of tools. And the way that the business was working was planning was investing in technology was just completely disconnected and using a whole different set of measures. Pretty >>Interesting. Cause I think it's pretty clear from the software development teams in terms of what they're trying to deliver. Cause they've got a feature set, right. And they've got bugs and it's easy to, it's easy to see what they deliver, but it sounds like what you're really honing in on is this disconnect on the business side, in terms of, you know, is it the right investment? You know, are we getting the right business ROI on this investment? Was that the right feature? Should we be building another feature or should we building a completely different product set? So it sounds like it's really a core piece of this is to get the right measurement tools, the right measurement data sets so that you can make the right decisions in terms of what you're investing, you know, limited resources. You can't, nobody has unlimited resources. And ultimately you have to decide what to do, which means you're also deciding what not to do. And it sounds like that's a really big piece of this, of this whole effort. >>Yeah. Jeff, that's exactly it, which is the way that the agile team measures their own way of working is very different from the way that you measure business outcomes. The business outcomes are in terms of how happy your customers are, but are you innovating fast enough to keep up with the pace of a rapidly changing economy, roughly changing market. And those are, those are all around the customer. And so what I learned on this long journey of supporting many organizations transformations and having them try to apply those principles of agile and dev ops, that those are not enough, those measures technical practices, uh, those measured sort of technical excellence of bringing code to the market. They don't actually measure business outcomes. And so I realized that it really was much more around having these entwined flow metrics that are customer centric and business centric and market centric where we need it to go. Right. >>So I want to shift gears a little bit and talk about your book because you're also a bestselling author from project to product and, and, and you, you brought up this concept in your book called the flow framework. And it's really interesting to me cause I know, you know, flow on one hand is kind of a workflow and a process flow and, and you know, that's how things get done and, and, and embrace the flow. On the other hand, you know, everyone now in, in a little higher level existential way is trying to get into the flow right into the workflow and, you know, not be interrupted and get into a state where you're kind of at your highest productivity, you know, kind of your highest comfort, which flow are you talking about in your book? Or is it a little bit of both? >>That's a great question. It's not one I get asked very often cause to me it's absolutely both. So that the thing that we want to get, that we've learned how to master individual flow, that there's this beautiful book by me, how you teaches me how he does a beautiful Ted talk by him as well about how we can take control of our own flow. So my question with the book with question replies, how can we bring that to entire teams and really entire organizations? How can we have everyone contributing to a customer outcome? And this is really what if you go to the biz ops manifesto, it says, I focus on outcomes on using data to drive whether we're delivering those outcomes rather than a focus on proxy metrics, such as, how quickly did we implement this feature? No, it's really how much value did the customer go to the future? >>And how quickly did you learn and how quickly did you use that data to drive to that next outcome? Really that with companies like Netflix and Amazon have mastered, how do we get that to every large organization, every it organization and make everyone be a software innovator. So it's to bring that, that concept of flow to these end to end value streams. And the fascinating thing is we've actually seen the data. We've been able to study a lot of value streams. We see when flow increases, when organizations deliver value to a customer faster, developers actually become more happy. So things like that and point out promoter scores, rise, and we've got empirical data for this. So that the beautiful thing to me is that we've actually been able to combine these two things and see the results and the data that you increase flow to the customer. Your developers are more, >>I love it. I love it, right, because we're all more, we're all happier when we're in the flow and we're all more productive when we're in the flow. So I, that is a great melding of, of two concepts, but let's jump into the, into the manifesto itself a little bit. And you know, I love that you took this approach really of having kind of four key values and then he gets 12 key principles. And I just want to read a couple of these values because when you read them, it sounds pretty brain dead. Right? Of course. Right. Of course you should focus on business outcomes. Of course you should have trust and collaboration. Of course you should have database decision making processes and not just intuition or, you know, whoever's the loudest person in the room, uh, and to learn and respond and pivot. But what's the value of actually just putting them on a piece of paper, because again, this is not this, these are all good, positive things, right? When somebody reads these to you or tells you these are sticks it on the wall, of course. But unfortunately of course isn't always enough. >>No. And I think what's happened is some of these core principles originally from the agile manifesto in two decades ago, uh, the whole dev ops movement of the last decade of flow feedback and continue learning has been key. But a lot of organizations, especially the ones undergoing digital transformations have actually gone a very different way, right? The way that they measure value, uh, in technology and innovation is through costs for many organizations. The way that they actually are looking at that they're moving to cloud is actually as a reduction in cost. Whereas the right way of looking at moving to cloud is how much more quickly can we get to the value to the customer? How quickly can we learn from that? And how quickly can we drive the next business outcome? So really the key thing is, is to move away from those old ways of doing things of funding projects and cost centers, to actually funding and investing in outcomes and measuring outcomes through these flow metrics, which in the end are your fast feedback and how quickly you're innovating for your customer. >>So these things do seem very obvious when you look at them. But the key thing is what you need to stop doing to focus on these. You need to actually have accurate realtime data of how much value you fund to the customer every week, every month, every quarter. And if you don't have that, your decisions are not driven on data. If you don't know what your bottleneck is. And this is something that in decades of manufacturing, a car manufacturers, other manufacturers, master, they always know where the bottom back in their production processes. You ask a random CIO when a global 500 company where their bottleneck is, and you won't get a clear answer because there's not that level of understanding. So have to actually follow these principles. You need to know exactly where you fall. And I guess because that's, what's making your developers miserable and frustrated, then having them context, which I'm trash. So the approach here is important and we have to stop doing these other things, >>Right? There's so much there to unpack. I love it. You know, especially the cloud conversation because so many people look at it wrong as, as, as a cost saving a device, as opposed to an innovation driver and they get stuck, they get stuck in the literal. And I, you know, I think at the same thing, always about Moore's law, right? You know, there's a lot of interesting real tech around Moore's law and the increasing power of microprocessors, but the real power, I think in Moore's laws is the attitudinal change in terms of working in a world where you know that you've got all this power and what you build and design. I think it's funny to your, your comment on the flow and the bottleneck, right? Cause, cause we know manufacturing, as soon as you fix one bottleneck, you move to your next one, right? You always move to your next point of failure. So if you're not fixing those things, you know, you're not, you're not increasing that speed down the line, unless you can identify where that bottleneck is or no matter how many improvements you make to the rest of the process, it's still going to get hung up on that one spot. >>That's exactly it. And you also make it sound so simple, but again, if you don't have the data driven visibility of where the bottom line is, and these bottlenecks are adjusted to say, it's just whack-a-mole right. So we need to understand is the bottleneck because our security reviews are taking too long and stopping us from getting value for the customer. If it's that automate that process. And then you move on to the next bottleneck, which might actually be that deploying yourself into the cloud was taking too long. But if you don't take that approach of going flow first, rather than again, that sort of cost reduction. First, you have to think of that approach of customer centricity and you only focused on optimizing costs. Your costs will increase and your flow will slow down. And this is just one of these fascinating things. Whereas if you focus on getting back to the customer and reducing your cycles on getting value, your flow time from six months to two weeks or two, one week or two event, as we see with, with tech giants, you actually can both lower your costs and get much more value that for us to get that learning loop going. >>So I think I've seen all of these cloud deployments and one of the things that's happened that delivered almost no value because there was such big bottlenecks upfront in the process and actually the hosting and the AP testing was not even possible with all of those inefficiencies. So that's why going float for us rather than costs where we started our project versus silky. >>I love that. And, and, and, and it, it begs repeating to that right within the subscription economy, you know, you're on the hook to deliver value every single month because they're paying you every single month. So if you're not on top of how you're delivering value, you're going to get sideways because it's not like, you know, they pay a big down payment and a small maintenance fee every month, but once you're in a subscription relationship, you know, you have to constantly be delivering value and upgrading that value because you're constantly taking money from the customer. So it's such a different kind of relationship than kind of the classic, you know, big bang with a maintenance agreement on the back end really important. Yeah. >>And I think in terms of industry shifts that that's it that's, what's catalyzed. This interesting shift is in this SAS and subscription economy. If you're not delivering more and more value to your customers, someone else's and they're winning the business, not you. So one way we know is to delight our customers with great user experiences. Well, that really is based on how many features you delivered or how much, how big, how many quality improvements or scalar performance improvements you delivered. So the problem is, and this is what the business manifesto, as well as the full frame of touch on is if you can't measure how much value you delivered to a customer, what are you measuring? You just backed again, measuring costs and that's not a measure of value. So we have to shift quickly away from measuring cost to measuring value, to survive in the subscription economy. >>We could go for days and days and days. I want to shift gears a little bit into data and, and, and a data driven, um, decision making a data driven organization cause right day has been talked about for a long time, the huge big data meme with, with Hadoop over, over several years and, and data warehouses and data lakes and data oceans and data swamps, and can go on and on and on. It's not that easy to do, right? And at the same time, the proliferation of data is growing exponentially. We're just around the corner from, from IOT and 5g. So now the accumulation of data at machine scale, again, this is going to overwhelm and one of the really interesting principles, uh, that I wanted to call out and get your take right, is today's organizations generate more data than humans can process. So informed decisions must be augmented by machine learning and artificial intelligence. I wonder if you can, again, you've got some great historical perspective, um, reflect on how hard it is to get the right data, to get the data in the right context, and then to deliver it to the decision makers and then trust the decision makers to actually make the data and move that down. You know, it's kind of this democratization process into more and more people and more and more frontline jobs making more and more of these little decisions every day. >>Yeah. I definitely think the front parts of what you said are where the promises of big data have completely fallen on their face into the swamps as, as you mentioned, because if you don't have the data in the right format, you've cannot connect collected at the right way. You want that way, the right way you can't use human or machine learning effectively. And there've been the number of data warehouses in a typical enterprise organization. And the sheer investment is tremendous, but the amount of intelligence being extracted from those is, is, is a very big problem. So the key thing that I've noticed is that if you can model your value streams, so yes, you understand how you're innovating, how you're measuring the delivery of value and how long that takes. What is your time to value these metrics like full time? You can actually use both the intelligence that you've got around the table and push that down as well, as far as getting to the organization, but you can actually start using that those models to understand and find patterns and detect bottlenecks that might be surprising, right? >>Well, you can detect interesting bottlenecks when you shift to work from home. We detected all sorts of interesting bottlenecks in our own organization that were not intuitive to me that had to do with, you know, more senior people being overloaded and creating bottlenecks where they didn't exist. Whereas we thought we were actually an organization that was very good at working from home because of our open source roots. So that data is highly complex. Software value streams are extremely complicated. And the only way to really get the proper analyst and data is to model it properly and then to leverage these machine learning and AI techniques that we have. But that front part of what you said is where organizations are just extremely immature in what I've seen, where they've got data from all their tools, but not modeled in the right way. Right, right. >>Right. Well, all right. So before I let you go, you know, let's say you get a business leader, he buys in, he reads the manifesto, he signs on the dotted line and he says, Mick, how do I get started? I want to be more aligned with, with the development teams. You know, I'm in a very competitive space. We need to be putting out new software features and engaging with our customers. I want to be more data-driven how do I get started? Well, you know, what's the biggest inhibitor for most people to get started and get some early wins, which we know is always the key to success in any kind of a new initiative. >>Right? So I think you can reach out to us through the website, uh, there's the manifesto, but the key thing is just to get you set up it's to get started and to get the key wins. So take a probably value stream that's mission critical. It could be your new mobile and web experiences or, or part of your cloud modernization platform or your analytics pipeline, but take that and actually apply these principles to it and measure the end to end flow of value. Make sure you have a value metric that everyone is on the same page on the people, on the development teams, the people in leadership all the way up to the CEO. And one of the, what I encourage you to start is actually that content flow time, right? That is the number one metric. That is how you measure it, whether you're getting the benefit of your cloud modernization, that is the one metric that Adrian Cockcroft. When the people I respect tremendously put into his cloud for CEOs, the metric, the one, the one way to measure innovation. So basically take these principles, deploy them on one product value stream, measure, sentiment, flow time, and then you'll actually be well on your path to transforming and to applying the concepts of agile and dev ops all the way to, to the business, to the way >>You're offering model. >>Well, Mick really great tips, really fun to catch up. I look forward to a time when we can actually sit across the table and, and get into this. Cause I just, I just love the perspective and, you know, you're very fortunate to have that foundational, that foundational base coming from Xerox park and they get, you know, it's, it's a very magical place with a magical history. So to, to incorporate that into, continue to spread that well, uh, you know, good for you through the book and through your company. So thanks for sharing your insight with us today. >>Thanks so much for having me, Jeff. >>All right. And go to the biz ops manifesto.org, read it, check it out. If you want to sign it, sign it. They'd love to have you do it. Stay with us for continuing coverage of the unveiling of the business manifesto on the cube. I'm Jeff. Rick. Thanks for watching. See you next time >>From around the globe. It's the cube with digital coverage of biz ops manifesto unveiled brought to you by biz ops coalition. >>Hey, welcome back everybody. Jeff Frick here with the cube come due from our Palo Alto studios today for a big, big reveal. We're excited to be here. It's the biz ops manifesto unveiling a thing's been in the works for awhile and we're excited to have our next guest. One of the, really the powers behind this whole effort. And he's joining us from Boston it's surge, Lucio, the vice president, and general manager enterprise software division at Broadcom surge. Great to see you. >>Hi, good to see you, Jeff. Glad to be here. >>So you've been in this business for a very long time. You've seen a lot of changes in technology. What is the biz ops manifesto? What is this coalition all about? Why do we need this today and in 2020? >>Yeah. So, so I've been in this business for close to 25 years, right? So about 20 years ago, the agile manifesto was created. And the goal of the agile manifesto was really to address the uncertainty around software development and the inability to predict the efforts to build software. And, uh, if you, if you roll that kind of 20 years later, and if you look at the current state of the industry, uh, the product, the project management Institute, estimates that we're wasting about a million dollars, every 20 seconds in digital transformation initiatives that do not deliver on business results. In fact, we were recently served a third of the, uh, a number of executives in partnership with Harvard business review and 77% of those executives think that one of the key challenges that they have is really at the collaboration between business and it, and that that's been kind of a case for, uh, almost 20 years now. >>Um, so the, the, the key challenge we're faced with is really that we need a new approach and many of the players in the industry, including ourselves, I've been using different terms, right? Some are being, are talking about value stream management. Some are talking about software delivery management. If you look at the site, reliability engineering movement, in many ways, it embodies a lot of these kind of concepts and principles. So we believed that it became really imperative for us to crystallize around, could have one concept. And so in many ways, the, uh, the BizOps concept and the business manifesto are bringing together a number of ideas, which have been emerging in the last five years or so, and, and defining the key values and principles to finally help these organizations truly transform and become digital businesses. And so the hope is that by joining our forces and defining public key principles and values, we can help the industry, uh, not just, uh, by, you know, providing them with support, but also, uh, tools and consulting that is required for them to truly achieve the kind of transformation that everybody's seeking. >>Right, right. So COVID now we're six months into it, approximately seven months into it. Um, a lot of pain, a lot of bad stuff still happening. We've got a ways to go, but one of the things that on the positive side, right, and you've seen all the memes and social media is, is a driver of digital transformation and a driver of change. Cause we had this light switch moment in the middle of March and there was no more planning. There was no more conversation. You've suddenly got remote workforces, everybody's working from home and you got to go, right. So the reliance on these tools increases dramatically, but I'm curious, you know, kind of short of, of the beginnings of this effort in short of kind of COVID, which, you know, came along unexpectedly. I mean, what were those inhibitors because we've been making software for a very long time, right? The software development community has, has adopted kind of rapid change and, and iterative, uh, delivery and, and sprints, what was holding back the connection with the business side to make sure that those investments were properly aligned with outcomes. >>Well, so, so you have to understand that it is, is kind of a its own silos. And traditionally it has been treated as a cost center within large organizations and not as a value center. And so as a result could have a traditional dynamic between it and the business is basically one of a kind of supplier up to kind of a business. Um, and you know, if you, if you go back to, uh, I think you'll unmask a few years ago, um, basically at this concept of the machines to build the machines and you went as far as saying that, uh, the machines or the production line is actually the product. So, um, meaning that the core of the innovation is really about, uh, building, could it be engine to deliver on the value? And so in many ways, you know, we have missed on this shift from, um, kind of it becoming this kind of value center within the enterprises. >>And, and he talks about culture. Now, culture is a, is a sum total of beavers. And the reality is that if you look at it, especially in the last decade, uh, we've agile with dev ops with, um, I bring infrastructures, uh, it's, it's way more volatile today than it was 10 years ago. And so the, when you start to look at the velocity of the data, the volume of data, the variety of data to analyze this system, um, it's, it's very challenging for it to actually even understand and optimize its own processes, let alone, um, to actually include business as sort of an integral part of kind of a delivery chain. And so it's both kind of a combination of, of culture, um, which is required as well as tools, right? To be able to start to bring together all these data together, and then given the volume variety of philosophy of the data, uh, we have to apply some core technologies, which have only really, truly emerged in the last five to 10 years around machine learning and analytics. And so it's really kind of a combination of those freaks, which are coming together today to really help organizations kind of get to the next level. Right, >>Right. So let's talk about the manifesto. Let's talk about, uh, the coalition, uh, the BizOps coalition. I just liked that you put down these really simple, you know, kind of straightforward core values. You guys have four core values that you're highlighting, you know, business outcomes, over individual projects and outputs, trust, and collaboration, oversight, load teams, and organizations, data driven decisions, what you just talked about, uh, you know, over opinions and judgment and learned, respond and pivot. I mean, surgery sounds like pretty basic stuff, right? I mean, aren't, isn't everyone working to these values already. And I think he touched on it on culture, right? Trust and collaboration, data driven decisions. I mean, these are fundamental ways that people must run their business today, or the person that's across the street, that's doing it. It's going to knock them out right off their blog. >>Yeah. So that's very true. But, uh, so I'll, I'll mention in our survey, we did, uh, I think about six months ago and it was in partnership with, uh, with, uh, an industry analyst and we serve at a, again, a number of it executives to understand how many we're tracking business outcomes I'm going to do with the software executives. It executives we're tracking business outcomes. And the, there were less than 15% of these executives were actually tracking the outcomes of a software delivery. And you see that every day. Right? So in my own teams, for instance, we've been adopting a lot of these core principles in the last year or so, and we've uncovered that 16% of our resources were basically aligned around initiatives, which are not strategic for us. Um, I take, you know, another example, for instance, one of our customers in the, uh, in the airline industry and Harvard, for instance, that a number of, uh, um, that they had software issues that led to people searching for flights and not returning any kind of availability. >>And yet, um, you know, the, it teams, whether it's operations, software environments were completely oblivious to that because they were completely blindsided to it. And so the connectivity between kind of the inwards metrics that RT is using, whether it's database time, cycle time, or whatever metric we use in it are typically completely divorced from the business metrics. And so at its core, it's really about starting to align the business metrics with what the, the software delivery chain, right? This, uh, the system, which is really a core differentiator for these organizations. It's about connecting those two things and, and starting to, um, infuse some of the agile culture and principles. Um, that's emerged from the software side into the business side. Um, of course the lean movement and other movements have started to change some of these dynamic on the, on the business side. And so I think this, this is the moment where we are starting to see kind of the imperative to transform. Now, you know, Covina obviously has been a key driver for that. The, um, the technology is right to start to be able to weave data together and really kind of, uh, also the cultural shifts, uh, Prue agile through dev ops through, uh, the SRE movement, uh frulein um, business transformation, all these things are coming together and that are really creating kind of the conditions for the BizOps manifesto to exist. >>So, uh, Clayton Christianson, great, uh, Harvard professor innovator's dilemma might still my all time favorite business books, you know, talks about how difficult it is for incumbents to react to, to disruptive change, right? Because they're always working on incremental change because that's what their customers are asking for. And there's a good ROI when you talk about, you know, companies not measuring the right thing. I mean, clearly it has some portion of their budget that has to go to keeping the lights on, right. That that's always the case, but hopefully that's an, an ever decreasing percentage of their total activity. So, you know, what should people be measuring? I mean, what are kind of the new metrics, um, in, in biz ops that drive people to be looking at the right things, measuring the right things and subsequently making the right decisions, investment decisions on whether they should do, you know, move project a along or project B. >>So there, there are only two things, right? So, so I think what you're talking about is portfolio management, investment management, right. And, um, which, which is a key challenge, right? Um, in my own experience, right? Uh, driving strategy or a large scale kind of software organization for years, um, it's very difficult to even get kind of a base data as to who is doing what, uh, um, I mean, some of our largest customers we're engaged with right now are simply trying to get a very simple answer, which is how many people do I have and that specific initiative at any point in time, and just tracking that information is extremely difficult. So, and again, back to a product project management Institute, um, there, they have estimated that on average, it organizations have anywhere between 10 to 20% of their resources focused on initiatives, which are not strategically aligned. >>So, so that's one dimensional portfolio management. I think the key aspect though, that we are, we're really keen on is really around kind of the alignment of a business metrics to the it metrics. Um, so I'll use kind of two simple examples, right? And my background is around quality and I've always believed that the fitness for purpose is really kind of a key, um, uh, philosophy if you will. And so if you start to think about quality as fitness for purpose, you start to look at it from a customer point of view, right. And fitness for purpose for a core banking application or mobile application are different, right? So the definition of a business value that you're trying to achieve is different. Um, and so the, and yeah, if you look at our, it, operations are operating there, we're using kind of a same type of, uh, kind of inward metrics, uh, like a database off time or a cycle time, or what is my point of velocity, right? >>And so the challenge really is this inward facing metrics that it is using, which are divorced from ultimately the outcome. And so, you know, if I'm, if I'm trying to build a poor banking application, my core metric is likely going to be uptight, right? If I'm trying to build a mobile application or maybe your social, a mobile app, it's probably going to be engagement. And so what you want is for everybody across it, to look at these metric and what are the metrics within the software delivery chain, which ultimately contribute to that business metric. And some cases cycle time may be completely irrelevant, right? Again, my core banking app, maybe I don't care about cycle time. And so it's really about aligning those metrics and be able to start to, um, Charles you mentioned, uh, around the, the, um, uh, around the disruption that we see is, or the investors is the dilemma now is really around the fact that many it organizations are essentially applying the same approaches of, for innovation, like for basically scrap work, then they would apply to kind of over more traditional projects. And so, you know, there's been a lot of talk about two-speed it, and yes, it exists, but in reality are really organizations, um, truly differentiating, um, all of the operate, their, their projects and products based on the outcomes that they're trying to achieve. And this is really where BizOps is trying to affect. >>I love that, you know, again, it doesn't seem like brain surgery, but focus on the outcomes, right. And it's horses for courses, as you said, this project, you know, what you're measuring and how you define success, isn't necessarily the same as, as on this other project. So let's talk about some of the principles we talked about the values, but, you know, I think it's interesting that, that, that the BizOps coalition, you know, just basically took the time to write these things down and they don't seem all that super insightful, but I guess you just got to get them down and have them on paper and have them in front of your face. But I want to talk about, you know, one of the key ones, which you just talked about, which is changing requirements, right. And working in a dynamic situation, which is really what's driven, you know, this, the software to change in software development, because, you know, if you're in a game app and your competitor comes out with a new blue sword, you got to come out with a new blue sword. >>So whether you had that on your Kanban wall or not. So it's, it's really this embracing of the speed of change and, and, and, and making that, you know, the rule, not the exception. I think that's a phenomenal one. And the other one you talked about is data, right? And that today's organizations generate more data than humans can process. So informed decisions must be generated by machine learning and AI, and, you know, in the, the big data thing with Hadoop, you know, started years ago, but we are seeing more and more that people are finally figuring it out, that it's not just big data, and it's not even generic machine learning or artificial intelligence, but it's applying those particular data sets and that particular types of algorithms to a specific problem, to your point, to try to actually reach an objective, whether that's, you know, increasing the, your average ticket or, you know, increasing your checkout rate with, with, with shopping carts that don't get left behind in these types of things. So it's a really different way to think about the world in the good old days, probably when you got started, when we had big, giant, you know, MRDs and PRDs and sat down and coded for two years and came out with a product release and hopefully not too many patches subsequently to that. >>It's interesting. Right. Um, again, back to one of these surveys that we did with, uh, with about 600, the ITA executives, and, uh, and, and we, we purposely designed those questions to be pretty open. Um, and, and one of them was really wrong requirements and, uh, and it was really a wrong, uh, kind of what do you, what is the best approach? What is your preferred approach towards requirements? And if I were to remember correctly, over 80% of the it executives set that the best approach they'll prefer to approach these core requirements to be completely defined before software development starts, let me pause there we're 20 years after the agile manifesto, right? And for 80% of these idea executives to basically claim that the best approach is for requirements to be fully baked before salt, before software development starts, basically shows that we still have a very major issue. >>And again, our hypothesis in working with many organizations is that the key challenge is really the boundary between business and it, which is still very much contract based. If you look at the business side, they basically are expecting for it deliver on time on budget, right. But what is the incentive for it to actually delivering on the business outcomes, right? How often is it measured on the business outcomes and not on an SLA or on a budget type criteria? And so that's really the fundamental shift that we need to, we really need to drive up as an industry. Um, and you know, we, we talk about kind of this, this imperative for organizations to operate that's one, and back to the, the, um, you know, various Doris dilemna the key difference between these larger organization is, is really kind of, uh, if you look at the amount of capital investment that they can put into pretty much anything, why are they losing compared to, um, you know, startups? What, why is it that, uh, more than 40% of, uh, personal loans today or issued not by your traditional brick and mortar banks, but by, um, startups? Well, the reason, yes, it's the traditional culture of doing incremental changes and not disrupting ourselves, which Christiansen covered the length, but it's also the inability to really fundamentally change kind of a dynamic picture. We can business it and, and, and partner right. To, to deliver on a specific business outcome. >>All right. I love that. That's a great, that's a great summary. And in fact, getting ready for this interview, I saw you mentioning another thing where, you know, the, the problem with the agile development is that you're actually now getting more silos. Cause you have all these autonomous people working, you know, kind of independently. So it's even a harder challenge for, for the business leaders to, to, as you said, to know, what's actually going on, but, but certainly I w I want to close, um, and talk about the coalition. Um, so clearly these are all great concepts. These are concepts you want to apply to your business every day. Why the coalition, why, you know, take these concepts out to a broader audience, including either your, your competition and the broader industry to say, Hey, we, as a group need to put a stamp of approval on these concepts, these values, these principles. >>So first I think we, we want, um, everybody to realize that we are all talking about the same things, the same concepts. I think we were all from our own different vantage point, realizing that things after change, and again, back to, you know, whether it's value stream management or site reliability engineering, or biz ops, we're all kind of using slightly different languages. Um, and so I think one of the important aspects of BizOps is for us, all of us, whether we're talking about, you know, consulting agile transformation experts, uh, whether we're talking about vendors, right, provides kind of tools and technologies or these large enterprises to transform for all of us to basically have kind of a reference that lets us speak around kind of, um, in a much more consistent way. The second aspect is for, to me is for, um, DS concepts to start to be embraced, not just by us or trying, or, you know, vendors, um, system integrators, consulting firms, educators, thought leaders, but also for some of our old customers to start to become evangelists of their own in the industry. >>So we, our, our objective with the coalition needs to be pretty, pretty broad. Um, and our hope is by, by starting to basically educate, um, our, our joint customers or partners, that we can start to really foster these behaviors and start to really change some of dynamics. So we're very pleased at if you look at, uh, some of the companies which have joined the, the, the, the manifesto. Um, so we have vendors such as desktop or advance, or, um, uh, PagerDuty for instance, or even planned view, uh, one of my direct competitors, um, but also thought leaders like Tom Davenport or, uh, or cap Gemini or, um, um, smaller firms like, uh, business agility, institutes, or agility elf. Um, and so our goal really is to start to bring together, uh, fall years, people would have been LP, large organizations, do digital transformation vendors. We're providing the technologies that many of these organizations use to deliver on this digital preservation and for all of us to start to provide the kind of, uh, education support and tools that the industry needs. Yeah, >>That's great surge. And, uh, you know, congratulations to you and the team. I know this has been going on for a while, putting all this together, getting people to sign onto the manifesto, putting the coalition together, and finally today getting to unveil it to the world in, in a little bit more of a public, uh, opportunity. So again, you know, really good values, really simple principles, something that, that, uh, shouldn't have to be written down, but it's nice cause it is, and now you can print it out and stick it on your wall. So thank you for, uh, for sharing this story and again, congrats to you and the team. >>Thank you. Thanks, Jeff. Appreciate it. >>Oh, my pleasure. Alrighty, surge. If you want to learn more about the BizOps manifest to go to biz ops manifesto.org, read it and you can sign it and you can stay here for more coverage. I'm the cube of the biz ops manifesto unveiled. Thanks for watching. See you next >>From around the globe. It's the cube with digital coverage of this ops manifesto unveiled brought to you by bill. >>Hey, welcome back, everybody Jeffrey here with the cube. Welcome back to our ongoing coverage of the biz ops manifesto unveiling. It's been in the works for awhile, but today's the day that it actually kind of come out to the, to the public. And we're excited to have a real industry luminary here to talk about what's going on, why this is important and share his perspective. And we're happy to have from Cape Cod, I believe is Tom Davenport. He is a distinguished author and professor at Babson college. We could go on, he's got a lot of great titles and, and really illuminary in the area of big data and analytics Thomas. Great to see you. >>Thanks Jeff. Happy to be here with you. >>Great. So let's just jump into it, you know, and getting ready for this. I came across your LinkedIn posts. I think you did earlier this summer in June and right off the bat, the first sentence just grabbed my attention. I'm always interested in new attempts to address longterm issues, uh, in how technology works within businesses, biz ops. What did you see in biz ops, uh, that, that kind of addresses one of these really big longterm problems? >>Well, yeah, but the longterm problem is that we've had a poor connection between business people and it people between business objectives and the, it solutions that address them. This has been going on, I think since the beginning of information technology and sadly it hasn't gone away. And so biz ops is a new attempt to deal with that issue with, you know, a new framework, eventually a broad set of solutions that increase the likelihood that we'll actually solve a business problem with an it capability. >>Right. You know, it's interesting to compare it with like dev ops, which I think a lot of people are probably familiar with, which was, you know, built around, uh, agile software development and a theory that we want to embrace change that that changes. Okay. Uh, and we want to be able to iterate quickly and incorporate that. And that's been happening in the software world for, for 20 plus years. What's taken so long to get that to the business side, because as the pace of change has changed on the software side, you know, that's a strategic issue in terms of execution on the business side that they need now to change priorities. And, you know, there's no PRDs and MRDs and big, giant strategic plans that sit on the shelf for five years. That's just not the way business works anymore. It took a long time to get here. >>Yeah, it did. And you know, there have been previous attempts to make a better connection between business and it, there was the so called alignment framework that a couple of friends of mine from Boston university developed, I think more than 20 years ago, but you know, now we have better technology for creating that linkage. And the, you know, the idea of kind of ops oriented frameworks is pretty pervasive now. So I think it's time for another serious attempt at it. Right. >>And do you think doing it this way, right. With the, with the biz ops coalition, you know, getting a collection of, of, of kind of likeminded individuals and companies together, and actually even having a manifesto, which we're making this declarative statement of, of principles and values, you think that's what it takes to kind of drive this kind of beyond the experiment and actually, you know, get it done and really start to see some results in, in, uh, in production in the field. >>I think certainly, um, no one vendor organization can pull this off single handedly. It does require a number of organizations collaborating and working together. So I think our coalition is a good idea and a manifesto is just a good way to kind of lay out what you see as the key principles of the idea. And that makes it much easier for everybody to understand and act on. >>I think it's just, it's really interesting having, you know, having them written down on paper and having it just be so clearly articulated both in terms of the, of the values as well as, as the, uh, the principles and the values, you know, business outcomes matter trust and collaboration, data driven decisions, which is the number three or four, and then learn, respond and pivot. It doesn't seem like those should have to be spelled out so clearly, but, but obviously it helps to have them there. You can stick them on the wall and kind of remember what your priorities are, but you're the data guy. You're the analytics guy, uh, and a big piece of this is data and analytics and moving to data-driven decisions. And principle number seven says, you know, today's organizations generate more data than humans can process and informed decisions can be augmented by machine learning and artificial intelligence right up your alley. You know, you've talked a number of times on kind of the mini stages of analytics. Um, and how has that's evolved over, over time, you know, as you think of analytics and machine learning, driving decisions beyond supporting decisions, but actually starting to make decisions in machine time. What's that, what's that thing for you? What does that make you, you know, start to think, wow, this is, this is going to be pretty significant. >>Yeah. Well, you know, this has been a longterm interest of mine. Um, the last generation of AI, I was very interested in expert systems. And then, um, I think, uh, more than 10 years ago, I wrote an article about automated decision-making using what was available then, which was rule-based approaches. Um, but you know, this addresses an issue that we've always had with analytics and AI. Um, you know, we, we tended to refer to those things as providing decision support. The problem is that if the decision maker didn't want their support, didn't want to use them in order to make a decision, they didn't provide any value. And so the nice thing about automating decisions, um, with now contemporary AI tools is that we can ensure that data and analytics get brought into the decision without any possible disconnection. Now, I think humans still have something to add here, and we often will need to examine how that decision is being made and maybe even have the ability to override it. But in general, I think at least for, you know, repetitive tactical decisions, um, involving a lot of data, we want most of those, I think to be at least recommended if not totally made by an algorithm or an AI based system, and that I believe would add to the quality and the precision and the accuracy of decisions and in most organizations, >>No, I think, I think you just answered my next question before I, before Hey, asked it, you know, we had dr. Robert Gates on a former secretary of defense on a few years back, and we were talking about machines and machines making decisions. And he said at that time, you know, the only weapon systems, uh, that actually had an automated trigger on it were on the North Korea and South Korea border. Um, everything else, as you said, had to go through a sub person before the final decision was made. And my question is, you know, what are kind of the attributes of the decision that enable us to more easily automated? And then how do you see that kind of morphing over time, both as the data to support that as well as our comfort level, um, enables us to turn more and more actual decisions over to the machine? >>Well, yeah, it's suggested we need, um, data and, um, the data that we have to kind of train our models has to be high quality and current. And we, we need to know the outcomes of that data. You know, um, most machine learning models, at least in business are supervised. And that means we need to have labeled outcomes in the, in the training data. But I, you know, um, the pandemic that we're living through is a good illustration of the fact that, that the data also have to be reflective of current reality. And, you know, one of the things that we're finding out quite frequently these days is that, um, the data that we have do not reflect, you know, what it's like to do business in a pandemic. Um, I wrote a little piece about this recently with Jeff cam at wake forest university, we called it data science quarantined, and we interviewed with somebody who said, you know, it's amazing what eight weeks of zeros will do to your demand forecast. We just don't really know what happens in a pandemic. Um, our models maybe have to be put on the shelf for a little while and until we can develop some new ones or we can get some other guidelines into making decisions. So I think that's one of the key things with automated decision making. We have to make sure that the data from the past and that's all we have of course, is a good guide to, you know, what's happening in the present and the future as far as we understand it. Yeah. >>I used to joke when we started this calendar year 2020, it was finally the year that we know everything with the benefit of hindsight, but it turned out 20, 20 a year. We found out we actually know nothing and everything thought we knew, but I wanna, I wanna follow up on that because you know, it did suddenly change everything, right? We got this light switch moment. Everybody's working from home now we're many, many months into it, and it's going to continue for a while. I saw your interview with Bernard Marr and you had a really interesting comment that now we have to deal with this change. We don't have a lot of data and you talked about hold fold or double down. And, and I can't think of a more, you know, kind of appropriate metaphor for driving the value of the BizOps when now your whole portfolio strategy, um, these to really be questioned and, and, you know, you have to be really, uh, well, uh, executing on what you are, holding, what you're folding and what you're doubling down with this completely new environment. >>Well, yeah, and I hope I did this in the interview. I would like to say that I came up with that term, but it actually came from a friend of mine. Who's a senior executive at Genpact. And, um, I, um, used it mostly to talk about AI and AI applications, but I think you could, you could use it much more broadly to talk about your entire sort of portfolio of digital projects. You need to think about, well, um, given some constraints on resources and a difficult economy for a while, which of our projects do we want to keep going on pretty much the way we were and which ones are not that necessary anymore? You see a lot of that in AI, because we had so many pilots, somebody told me, you know, we've got more pilots around here than O'Hare airport and AI. Um, and then, but the ones that involve double down they're even more important to you. They are, you know, a lot of organizations have found this out in the pandemic, on digital projects. It's more and more important for customers to be able to interact with you, um, digitally. And so you certainly wouldn't want to, um, cancel those projects or put them on hold. So you double down on them and get them done faster and better. >>Right, right. Uh, another, another thing that came up in my research that you quoted, um, was, was from Jeff Bezos, talking about the great bulk of what we do is quietly, but meaningfully improving core operations. You know, I think that is so core to this concept of not AI and machine learning and kind of the general sense, which, which gets way too much buzz, but really applied right. Applied to a specific problem. And that's where you start to see the value. And, you know, the, the BizOps, uh, manifesto is, is, is calling it out in this particular process. But I'd love to get your perspective as you know, you speak generally about this topic all the time, but how people should really be thinking about where are the applications where I can apply this technology to get direct business value. >>Yeah, well, you know, even talking about automated decisions, um, uh, the kind of once in a lifetime decisions, uh, the ones that, um, ag Lafley, the former CEO of Procter and gamble used to call the big swing decisions. You only get a few of those. He said in your tenure as CEO, those are probably not going to be the ones that you're automating in part because, um, you don't have much data about them. You're only making them a few times and in part, because, um, they really require that big picture thinking and the ability to kind of anticipate the future, that the best human decision makers, um, have. Um, but, um, in general, I think where they are, the projects that are working well are, you know, when I call the low hanging fruit ones, the, some people even report to it referred to it as boring AI. >>So, you know, sucking data out of a contract in order to compare it to a bill of lading for what arrived at your supply chain companies can save or make a lot of money with that kind of comparison. It's not the most exciting thing, but AI, as you suggested is really good at those narrow kinds of tasks. It's not so good at the, at the really big moonshots, like curing cancer or, you know, figuring out well what's the best stock or bond under all circumstances or even autonomous vehicles. Um, we, we made some great progress in that area, but everybody seems to agree that they're not going to be perfect for quite a while. And we really don't want to be driving around on them very much unless they're, you know, good and all kinds of weather and with all kinds of pedestrian traffic and you know, that sort of thing, right? That's funny you bring up contract management. >>I had a buddy years ago, they had a startup around contract management and was like, and this was way before we had the compute power today and cloud proliferation. I said, you know, how, how can you possibly build software around contract management? It's language, it's legal, ease. It's very specific. And he's like, Jeff, we just need to know where's the contract. And when does it expire? And who's the signatory. And he built a business on those, you know, very simple little facts that weren't being covered because their contracts contractor in people's drawers and files and homes, and Lord only knows. So it's really interesting, as you said, these kind of low hanging fruit opportunities where you can extract a lot of business value without trying to, you know, boil the ocean. >>Yeah. I mean, if you're Amazon, um, uh, Jeff Bezos thinks it's important to have some kind of billion dollar projects. And he even says it's important to have a billion dollar failure or two every year. But I think most organizations probably are better off being a little less aggressive and, you know, sticking to, um, what AI has been doing for a long time, which is, you know, making smarter decisions based on, based on data. >>Right? So Tom, I want to shift gears one more time before, before we let you go on on kind of a new topic for you, not really new, but you know, not, not a, the vast majority of, of your publications and that's the new way to work, you know, as, as the pandemic hit in mid March, right. And we had this light switch moment, everybody had to work from home and it was, you know, kind of crisis and get everybody set up. Well, you know, now we're five months, six months, seven months. A number of companies have said that people are not going to be going back to work for a while. And so we're going to continue on this for a while. And then even when it's not what it is now, it's not going to be what it was before. So, you know, I wonder, and I know you, you, uh, you teased, you're working on a new book, you know, some of your thoughts on, you know, kind of this new way to work and, and the human factors in this new, this new kind of reality that we're kind of evolving into, I guess. >>Yeah. I missed was an interest of mine. I think, um, back in the nineties, I wrote an article called, um, a coauthored, an article called two cheers for the virtual office. And, you know, it was just starting to emerge. Then some people were very excited about it. Some people were skeptical and, uh, we said two cheers rather than three cheers because clearly there's some shortcomings. And, you know, I keep seeing these pop up. It's great that we can work from our homes. It's great that we can accomplish most of what we need to do with a digital interface, but, um, you know, things like innovation and creativity and certainly, um, uh, a good, um, happy social life kind of requires some face to face contact every now and then. And so I, you know, I think we'll go back to an environment where there is some of that. >>Um, we'll have, um, times when people convene in one place so they can get to know each other face to face and learn from each other that way. And most of the time, I think it's a huge waste of people's time to commute into the office every day and to jump on airplanes, to, to, um, give every little, um, uh, sales call or give every little presentation. Uh, we just have to really narrow down what are the circumstances where face to face contact really matters. And when can we get by with, with digital, you know, I think one of the things in my current work I'm finding is that even when you have AI based decision making, you really need a good platform in which that all takes place. So in addition to these virtual platforms, we need to develop platforms that kind of structure the workflow for us and tell us what we should be doing next, then make automated decisions when necessary. And I think that ultimately is a big part of biz ops as well. It's not just the intelligence of an AI system, but it's the flow of work that kind of keeps things moving smoothly throughout your organization. >>Yeah. I think such, such a huge opportunity as you just said, cause I forget the stats on how often we're interrupted with notifications between email texts, Slack, a sauna, Salesforce, the list goes on and on. So, you know, to put an AI layer between the person and all these systems that are begging for attention, and you've written a book on the attention economy, which is a whole nother topic, we'll say for another day, you know, it really begs, it really begs for some assistance because you know, you just can't get him picked, you know, every two minutes and really get quality work done. It's just not, it's just not realistic. And you know what? I don't think that's a feature that we're looking for. I agree. Totally. Alright, Tom. Well, thank you so much for your time. Really enjoyed the conversation. I gotta dig into the library. It's very long. So I might start at the attention economy. I haven't read that one in to me. I think that's the fascinating thing in which we're living. So thank you for your time and, uh, great to see you. >>My pleasure, Jeff. Great to be here. >>All right. Take care. Alright. He's Tom I'm Jeff. You are watching the continuing coverage of the biz ops manifesto and Vale. Thanks for watching the cube. We'll see you next time.

>>From around the globe. It's the cube with digital coverage, a BizOps manifesto unveiled brought to you by biz ops coalition. >>Hey, welcome back everybody. Jeff Frick here with the cube. Welcome back to our ongoing coverage of the biz ops manifesto. Unveil. Something has been in the works for a little while. Today's the formal unveiling, and we're excited to have three of the core of founding members of the manifesto authors of the manifesto. If you will, uh, joining us again, we've had them all on individually. Now we're going to have a great power panel first up. We're gab Mitt, Kirsten returning he's the founder and CEO of Tasktop mic. Good to see you again. Where are you dialing in from? >>Great to see you again, Jeff I'm dialing from Vancouver, >>We're Canada, Vancouver, Canada. One of my favorite cities in the whole wide world. Also we've got Tom Davenport come in from across the country. He's a distinguished professor and author from Babson college, Tom. Great to see you. And I think you said you're at a fun, exotic place on the East coast >>Realm of Memphis shoe sits on Cape Cod. >>Great to see you again and also joining surge Lucio. He is the VP and general manager enterprise software division at Broadcom surge. Great to see you again, where are you coming in from? >>Uh, from Boston right next to kickoff. >>Terrific. So welcome back, everybody again. Congratulations on this day. I know it's, it's been a lot of work to get here for this unveil, but let's just jump into it. The biz ops manifesto, what was the initial reason to do this? And how did you decide to do it in a kind of a coalition, a way bringing together a group of people versus just making it an internal company, uh, initiative that, you know, you can do better stuff within your own company, surge, why don't we start with you? >>Yeah, so, so I think we were at a really critical juncture, right? Many, um, large enterprises are basically struggling with their digital transformation. Um, in fact, um, many recognize that, uh, the, the business side, it collaboration has been, uh, one of the major impediments, uh, to drive that kind of transformation. And if we look at the industry today, many people are, whether we're talking about vendors or, um, you know, system integrators, consulting firms are talking about the same kind of concepts, but using very different language. And so we believe that bringing all these different players together, um, as part of the coalition and formalizing, uh, basically the core principles and values in a BizOps manifesto, we can really start to F could have a much bigger movement where we can all talk about kind of the same concepts and we can really start to provide, could have a much better support for large organizations to transform. Uh, so whether it is technology or services or, um, we're training, I think that that's really the value of bringing all of these players together, right. >>And Nick to you, why did you get involved in this, in this effort? >>So Ben close and follow the agile movement since it started two decades ago with that manifesto. >>And I think we got a lot of improvement at the team level, and I think as satisfies noted, uh, we really need to improve at the business level. Every company is trying to become a software innovator, uh, trying to make sure that they can adapt quickly and the changing market economy and what everyone's dealing with in terms of needing to deliver the customer sooner. However, agile practices have really focused on these metrics, these measures and understanding processes that help teams be productive. Those things now need to be elevated to the business as a whole. And that just hasn't happened. Uh, organizations are actually failing because they're measuring activities and how they're becoming more agile, how teams are functioning, not how much quickly they're delivering value to the customer. So we need to now move past that. And that's exactly what the that's manifested provides. Right, >>Right, right. And Tom, to you, you've been covering tech for a very long time. You've been looking at really hard challenges and a lot of work around analytics and data and data evolution. So there's a definitely a data angle here. I wonder if you could kind of share your perspective of what you got excited to, uh, to sign onto this manifesto. >>Sure. Well, I have, you know, for the past 15 or 20 years, I've been focusing on data and analytics and AI, but before that I was a process management guy and a knowledge management guy. And in general, I think, you know, we've just kind of optimized that to narrow a level, whether you're talking about agile or dev ops or ML ops, any of these kinds of ops oriented movements, we're making individual project, um, performance and productivity better, but we're not changing the business, uh, effectively enough. And that's the thing that appealed to me about the biz ops idea that we're finally creating a closer connection between what we do with technology and how it changes the business and provides value to it. >>Great. Uh, surge back to you, right? I mean, people have been talking about digital transformation for a long time and it's been, you know, kind of trucking along and then covert hit and it was instant lights, which everyone's working from home. You've got a lot more reliance on your digital tools, digital communication, uh, both within your customer base and your partner base, but also then your employees when you're, if you could share how that really pushed this all along. Right? Because now suddenly the acceleration of digital transformation is higher. Even more importantly, you got much more critical decisions to make into what you do next. So kind of your portfolio management of projects has been elevated significantly when maybe revenues are down, uh, and you really have to, uh, to prioritize and get it right. >>Yeah. Maybe I'll just start by quoting Satina Nello basically recently said that they're speeding the two years of digital preservation just last two months in any many ways. That's true. Um, but, but yet when we look at large enterprises, they're >>Still struggling with the kind of a changes in culture that they really need to drive to be able to disrupt themselves. And not surprisingly, you know, when we look at certain parts of the industry, you know, we see some things which are very disturbing, right? So about 40% of the personal loans today, or being, uh, origin data it's by fintechs, uh, of a like of Sophie or, uh, or a lending club, right? Not to a traditional brick and mortar for BEC. And so the, well, there is kind of a much more of an appetite and it's a, it's more of a survival type of driver these days. Uh, the reality is that's in order for these large enterprises to truly transform and engage with this digital transformation, they need to start to really align the business. And it, you know, in many ways, uh, make covered that agile really emerged from the core desire to truly improve software predictability between which we've really missed is all that we, we start to aligning the software predictability to business predictability and to be able to have continual sleep continuous improvement and measurement of business outcomes. So by aligning kind of these, uh, kind of inward metrics, that's, it is typically being using to business outcomes. We think we can start to really ELP different stakeholders within the organization to collaborate. So I think there is more than ever. There's an imperative to act now. Um, and, and resolves, I think is kind of the right approach to drive that transformation. Right. >>I want to follow up on the culture comment, uh, with Utah, because you've talked before about kind of process flow and process flow throughout a whore and an organization. And, you know, we talk about people process and tech all the time. And I think the tech is the easy part compared to actually changing the people the way they think. And then the actual processes that they put in place. It's a much more difficult issue than just the tech issue to get this digital transformation in your organization. >>Yeah. You know, I've always found that the soft stuff about, you know, the culture of the behavior, the values is the hard stuff to change and more and more, we, we realized that to be successful with any kind of digital transformation you have to change people's behaviors and attitudes. Um, we haven't made as much progress in that area as we might have. I mean, I've done some surveys suggesting that, um, most organizations still don't have data-driven cultures. And in many cases there is a lower percentage of companies that say they have that then, um, did a few years ago. So we're kind of moving in the wrong direction, which means I think that we have to start explicitly addressing that, um, cultural, behavioral dimension and not just assuming that it will happen if we, if we build a system, >>If we build it, they won't necessarily come. Right. >>Right. So I want to go to, to you Nick cause you know, we're talking about workflows and flow, um, and, and you've written about flow both in terms of, um, you know, moving things along a process and trying to find bottlenecks, identify bottlenecks, which is now even more important again, when these decisions are much more critical. Cause you have a lot less, uh, wiggle room in tough times, but you also talked about flow from the culture side and the people side. So I wonder if you can just share your thoughts on, you know, using flow as a way to think about things, to get the answers better. >>Yeah, absolutely. And I'll refer back to what Tom has said. If you're optimized, you need to optimize your system. You need to optimize how you innovate and how you deliver value to the business and the customer. Now, what we've noticed in the data, since that we've learned from customers, value streams, enterprise organizations, value streams, is that when it's taking six months at the end to deliver that value with the flow is that slow. You've got a bunch of unhappy developers, unhappy customers when you're innovating house. So high performing organizations we can measure at antenna flow time and dates. All of a sudden that feedback loop, the satisfaction, your developers measurably, it goes up. So not only do you have people context, switching glass, you're delivering so much more value to customers at a lower cost because you've optimized for flow rather than optimizing for these, these other approximate tricks that we use, which is how efficient is my adult team. How quickly can we deploy software? Those are important, but they do not provide the value of agility of fast learning of adaptability to the business. And that's exactly what the biz ops manifesto pushes your organization to do. You need to put in place this new operating model that's based on flow on the delivery of business value and on bringing value to market much more quickly than you were before. Right. >>I love that. And I'm gonna back to you Tom, on that to follow up. Cause I think, I don't think people think enough about how they prioritize what they're optimizing for, because you know, if you're optimizing for a versus B, you know, you can have a very different product that, that you kick out. And, you know, my favorite example is with Clayton Christianson and innovator's dilemma talking about the three inch hard drive, if you optimize it for power, you know, is one thing, if you optimize it for vibration is another thing and sure enough, you know, they missed it on the poem because it was the, it was the game console, which, which drove that whole business. So when you're talking to customers and we think we hear it with cloud all the time, people optimizing for a cost efficiency, instead of thinking about it as an innovation tool, how do you help them kind of rethink and really, you know, force them to, to look at the, at the prioritization and make sure they're prioritizing on the right thing is make just that, what are you optimizing for? >>Oh yeah. Um, you have one of the most important aspects of any decision or attempt to resolve a problem in an organization is the framing process. And, um, you know, it's, it's a difficult aspect to have the decision to confirm it correctly in the first place. Um, there, it's not a technology issue. In many cases, it's largely a human issue, but if you frame >>That decision or that problem incorrectly to narrowly say, or you frame it as an either or situation where you could actually have some of both, um, it, it's very difficult for the, um, process to work out correctly. So in many cases, I think we need to think more at the beginning about how we bring this issue or this decision in the best way possible before we charge off and build a system to support it. You know, um, it's worth that extra time to think, think carefully about how the decision has been structured. Right, >>Sir, I want to go back to you and talk about the human factors because as we just discussed, you can put it in great technology, but if the culture doesn't adopt it and people don't feel good about it, you know, it's not going to be successful and that's going to reflect poorly on the technology, even if that had nothing to do with it. And you know, when you look at the, the, the, the core values, uh, of the Bezos manifesto, you know, a big one is trust and collaboration, you know, learn, respond, and pivot. Wonder if you can share your thoughts on, on trying to get that cultural shift, uh, so that you can have success with the people, or excuse me, with the technology in the process and helping customers, you know, take this more trustworthy and kind of proactive, uh, position. >>So I think, I think at the ground level, it truly starts with the realization that we're all different. We come from different backgrounds. Uh, oftentimes we tend to blame the data. It's not uncommon my experiments that we spend the first 30 minutes of any kind of one hour conversation to debate the validity of the data. Um, and so, um, one of the first kind of, uh, probably manifestations that we've had or revelations as we start to engage with our customers is spoke just exposing, uh, high-fidelity data sets to different stakeholders from their different lens. We start to enable these different stakeholders to not debate the data. That's really collaborate to find a solution. So in many ways, when, when, when we think about kind of the types of changes we're trying to, to truly affect around data driven decision making, he told about bringing the data in context and the context that is relevant and understandable for, for different stakeholders, whether we're talking about an operator or develop for a business analyst. >>So that's, that's the first thing. The second layer I think, is really to provide context to what people are doing in their specific silo. And so I think one of the best examples I have is if you start to be able to align business KPI, whether you are counting, you know, sales per hour, or the engagements of your users on your mobile applications, whatever it is, you can start to connect that PKI to business KPI, to the KPIs that developers might be looking at, whether it is all the number of defects or velocity or whatever over your metrics that you're used to, to actually track you start to be able to actually contextualize in what we are, the effecting, basically a metric of that that is really relevant. And then what we see is that this is a much more systematic way to approach the transformation than say, you know, some organizations kind of creating some of these new products or services or initiatives, um, to, to drive engagements, right? >>So if you look at zoom, for instance, zoom giving away a it service to, uh, to education, he's all about, I mean, there's obviously a marketing aspect in there, but it's, it's fundamentally about trying to drive also the engagement of their own teams. And because now they're doing something for good and many organizations are trying to do that, but you only can do this kind of things in the limited way. And so you really want to start to rethink how you connect to, everybody's kind of a business objective fruit data, and now you start to get people to stare at the same data from their own lens and collaborate on all the data. Right, >>Right. That's a good, uh, Tom, I want to go back to you. You've been studying it for a long time, writing lots of books and getting into it. Um, why now, you know, what, why, why now are we finally aligning business objectives with, with it objectives? You know, why didn't this happen before? And, you know, what are the factors that are making now the time for this, this, this move with the, uh, with the biz ops? >>Well, and much of a past, it was sort of a back office related activity. And, you know, it was important for, um, uh, producing your paychecks and, uh, capturing the customer orders, but the business wasn't built around it now, every organization needs to be a software business, a data business, a digital business, the auntie has been raised considerably. And if you aren't making that connection between your business objectives and the technology that supports it, you run a pretty big risk of, you know, going out of business or losing out to competitors. Totally. So, um, and even if you're in, uh, an industry that hasn't historically been terribly, um, technology oriented customer expectations flow from, uh, you know, the digital native, um, companies that they work with to basically every industry. So you're compared against the best in the world. So we don't really have the luxury anymore of screwing up our it projects or building things that don't really work for the business. Um, it's mission critical that we do that well. Um, almost every time, I just want to fall by that, Tom, >>In terms of the, you've talked extensively about kind of these evolutions of data and analytics from artismal stage to the big data stage, the data economy stage, the AI driven stage and what I find diff interesting that all those stages, you always put a start date, you never put an end date. Um, so you know, is the, is the big data I'm just going to use that generically a moment in time finally here where we're, you know, off mahogany row with the data scientists, but actually can start to see the promise of delivering the right insight to the right person at the right time to make that decision. >>Well, I think it is true that in general, these previous stages never seemed to go away. The, um, the artisinal stuff is still being done, but we would like for less and less of it to be artisinal, we can't really afford for everything to be artisinal anymore. It's too labor and, and time consuming to do things that way. So we shift more and more of it to be done through automation and B to be done with a higher level of productivity. And, um, you know, at some point maybe we reached the stage where we don't do anything artisanally anymore. I'm not sure we're there yet, but we are, we are making progress. Right. >>Right. And Mick, back to you in terms of looking at agile, cause you're, you're such a student of agile. When, when you look at the opportunity with biz ops and taking the lessons from agile, you know, what's been the inhibitor to stop this in the past. And what are you so excited about? You know, taking this approach will enable. >>Yeah. I think both search and Tom hit on this is that in agile what's happened is that we've been measuring tiny subsets of the value stream, right? We need to elevate the data's there. Developers are working on these tools that delivering features that the foundations for for great culture are there. I spent two decades as a developer. And when I was really happy is when I was able to deliver value to customers, the quicker I was able to do that the fewer impediments are in my way, that quicker was deployed and running in the cloud, the happier I was, and that's exactly what's happening. If we can just get the right data, uh, elevated to the business, not just to the agile teams, but really this, these values of ours are to make sure that you've got these data driven decisions with meaningful data that's oriented around delivering value to customers. Not only these legacies that Tom touched on, which has cost center metrics. So when, from where for it being a cost center and something that provided email and then back office systems. So we need to rapidly shift to those new, meaningful metrics that are customized business centric and make sure that every development the organization is focused on those as well as the business itself, that we're measuring value. And that will help you that value flow without interruptions. >>I love that mic. Cause if you don't measure it, you can't improve on it and you gotta, but you gotta be measuring the right thing. So gentlemen, uh, thank you again for, for your time. Uh, congratulations on the, uh, on the unveil of the biz ops manifesto and bringing together this coalition, uh, of, of, uh, industry experts to get behind this. And, you know, there's probably never been a more important time than now to make sure that your prioritization is in the right spot and you're not wasting resources where you're not going to get the ROI. So, uh, congratulations again. And thank you for sharing your thoughts with us here on the cube. >>Thank you. >>Alright, so we had surge Tom and Mick I'm. Jeff, you're watching the cube. It's a biz ops manifesto unveil. Thanks for watching. We'll see you next time >>From around the globe. It's the cube with digital coverage of biz ops manifesto unveiled brought to you by biz ops coalition. >>Hey, welcome back. Variety. Jeff Frick here with the cube. We're in our Palo Alto studios, and we'd like to welcome you back to our continuing coverage of biz ops manifesto unveil some exciting day to really, uh, kind of bring this out into public. There's been a little bit of conversation, but today's really the official unveiling and we're excited to have our next guest is share a little bit more information on it. He's Patrick tickle. He's a chief product officer for planned view. Patrick. Great to see you. >>Yeah, it's great to be here. Thanks for the invite. So why >>The biz ops manifesto, why the biz ops coalition now when you guys have been at it, it's relatively mature marketplace businesses. Good. What was missing? Why, why this, why this coalition? >>Yeah. So, you know, again, why is, why is biz ops important and why is this something that I'm, you know, I'm so excited about, but I think companies as well, right? Well, no, in some ways or another, this is a topic that I've been talking to the market and our customers about for a long time. And it's, you know, I really applaud this whole movement. Right. And, um, it resonates with me because I think one of the fundamental flaws, frankly, of the way we have talked about technology and business literally for decades, uh, has been this idea of, uh, alignment. Those who know me, I occasionally get off on this little rant about the word alignment, right. But to me, the word alignment is, is actually indicative of the, of the, of the flaw in a lot of our organizations and biz ops is really, I think now trying to catalyze and expose that flaw. >>Right. Because, you know, I always say that, you know, you know, alignment implies silos, right. Instantaneously, as soon as you say there's alignment, there's, there's obviously somebody who's got a direction and other people that have to line up and that kind of siloed, uh, nature of organizations then frankly, the passive nature of it. Right. I think so many technology organizations are like, look, the business has the strategy you guys need to align. Right. And, and, you know, as a product leader, right. That's where I've been my whole career. Right. I can tell you that I never sit around. I almost never use the word alignment. Right. I mean, whether, you know, I never sit down and say, you know, the product management team has to get aligned with dev, right. Or the dev team has to get aligned with the delivery and ops teams. I mean, what I say is, you know, are we on strategy, right? >>Like we've, we have a strategy as a, as a full end to end value stream. Right. And that there's no silos. And I mean, look, every on any given day we got to get better. Right. But the context, the context we operate is not about alignment. Right. It's about being on strategy. And I think I've talked to customers a lot about that, but when I first read the manifesto, I was like, Oh yeah, this is exactly. This is breaking down. Maybe trying to eliminate the word alignment, you know, from a lot of our organizations, because we literally start thinking about one strategy and how we go from strategy to delivery and have it be our strategy, not someone else's that we're all aligning to. And I, and it's a great way to catalyze that conversation that I've, it's been in my mind for years, to be honest. Right. >>So, so much to unpack there. One of the things obviously, uh, stealing a lot from, from dev ops and the dev ops manifesto from 20 years ago. And, and as I look through some of the principles and I looked through some of the values, which are, you know, really nicely laid out here, you know, satisfy customer, do continuous delivery, uh, measure, output against real results. Um, the ones that, that jumps out though is really about, you know, change, change, right? Requirements should change frequently. They do change frequently, but I'm curious to get your take from a, from a software development point, it's easy to kind of understand, right. We're making this widget and our competitors, beta widget plus X, and now we need to change our plans and make sure that the plus X gets added to the plan. Maybe it wasn't in the plan, but you talked a lot about product strategy. So in this kind of continuous delivery world, how does that meld with, I'm actually trying to set a strategy, which implies the direction for a little bit further out on the horizon and to stay on that while at the same time, you're kind of doing this real time continual adjustments because you're not working off a giant PRD or MRD anymore. >>Yeah, yeah, totally. Yeah. You know, one of the terms, you know, that we use internally a lot and even with my customers, our customers is we talk about this idea of rewiring, right. And I think, you know, it's kind of a, now an analogy for transformation. And I think a lot of us have to rewire the way we think about things. Right. And I think at Planview where we have a lot of customers who live in that, you know, who operationalize that traditional PPM world. Right. And are shifting to agile and transforming that rewire is super important. And, and to your point, right, it's, you've just, you've got to embrace this idea of, you know, just iterative getting better every day and iterating, iterating, iterating as opposed to building annual plans or, you know, I get customers occasionally who asked me for two or three year roadmap. >>Right. And I literally looked at them and I go, there's no, there's no scenario where I can build a two or three year roadmap. Right. You, you, you think you want that, but that's not, that's not the way we run. Right. And I will tell you the biggest thing that for us, you know, that I think is matched the planning, uh, you know, patents is a word I like to use a lot. So the thing that we've like, uh, that we've done from a planning perspective, I think is matched impedance to continuous delivery is instituting the whole program, implement, you know, the program, increment planning, capabilities, and methodologies, um, in the scaled agile world. Right. And over the last 18 months to two years, we really have now, you know, instrumented our company across three value streams. You know, we do quarterly PI program increment 10 week planning, you know, and that becomes, that becomes the Terra firma of how we plan. >>Right. And it's, what are we doing for the next 10 weeks? And we iterate within those 10 weeks, but we also know that 10 weeks from now, we're gonna, we're gonna adjust iterate again. Right. And that shifting of that planning model to, you know, to being as cross-functional is that as that big room planning kind of model is, um, and also, uh, you know, on that shorter increment, when you get those two things in place, also the impedance really starts to match up, uh, with continuous delivery and it changes, it changes the way you plan and it changes the way you work. Right? >>Yeah. Their thing. Right. So obviously a lot of these things are kind of process driven, both within the values, as well as the principles, but there's a whole lot, really about culture. And I just want to highlight a couple of the values, right? We already talked about business outcomes, um, trust and collaboration, uh, data driven decisions, and then learn, respond and pivot. Right. A lot of those are cultural as much as they are process. So again, is it the, is it the need to really kind of just put them down on paper and, you know, I can't help, but think of, you know, the hammer and up the, a, the thing in the Lutheran church with it, with their manifesto, is it just good to get it down on paper? Because when you read these things, you're like, well, of course we should trust people. And of course we need an environment of collaboration and of course we want data driven decisions, but as we all know saying it and living, it are two very, very different things. >>Yeah. Good question. I mean, I think there's a lot of ways to bring that to life you're right. And just hanging up, you know, I think we've all been through the hanging up posters around your office, which these days, right. Unless you're going to hang a poster in everybody's home office. Right. You can't even, you can't even fake it that you think that might work. Right. So, um, you know, you really, I think we've attacked that in a variety of ways. Right. And you definitely have to, you know, you've got to make the shift to a team centric culture, right. Empowered teams, you know, that's a big deal. Right. You know, a lot of, a lot of the people that, you know, we lived in a world of quote, unquote work. We lived in a deep resource management world for a long, long time, and right. >>A lot of our customers still do that, but, you know, kind of moving to that team centric world is, uh, is really important and core to the trust. Um, I think training is super important, right. I mean, we've, you know, we've internally, right. We've trained hundreds employees over the last a year and a half on the fundamentals really of safe. Right. Not necessarily, you know, we've had, we've had teams delivering in scrum and the continuous delivery for, you know, for years, but the scaling aspect of it, uh, is where we've done a lot of training investment. Um, and then, you know, I think a leadership has to be bought in. Right. You know? And so when we pie plan, you know, myself and Cameron and the other members of our leadership, you know, we're NPI planning, you know, for, for four days. Right. I mean, it's, it's, you've got to walk the walk, you know, from top to bottom and you've got to train on the context. Right. And then you, and then, and, and then once you get through a few cycles where you've done a pivot, right. Or you brought a new team in, and it just works, it becomes kind of this virtuous circle where he'll go, man, this really works so much better than what we used to do. Right. >>Right. The other really key principle to this whole thing is, is aligning, you know, the business leaders and the business prioritization, um, so that you can get to good outcomes with the development and the delivery. Right. And we know again, and kind of classic dev ops to get the dev and the production people together. So they can, you know, quickly ship code that works. Um, but adding the business person on there really puts, puts a little extra responsibility that they, they understand the value of a particular feature or particular priority. Uh, they, they can make the, the, the trade offs and that they kind of understand the effort involved too. So, you know, bringing them into this continuous again, kind of this continuous development process, um, to make sure that things are better aligned and really better prioritize. Cause ultimately, you know, we don't live in an infinite resources situation and people gotta make trade offs. They gotta make decisions as to what goes and what doesn't go in for everything that goes. Right. I always say you pick one thing. Okay. That's 99 other things that couldn't go. So it's really important to have, you know, this, you said alignment of the business priorities as well as, you know, the execution within, within the development. >>Yeah. I think that, you know, uh, you know, I think it was probably close to two years ago. Forester started talking about the age of the customer, right. That, that was like their big theme at the time. Right. And I think to me what that, the age of the customer actually translates to and Mick, Mick and I are both big fans of this whole idea of the project, the product shift, mixed book, you know, it was a great piece on a, you're talking to Mick, you know, as part of the manifesto is one of the authors as well, but this shift from project to product, right? Like the age of the customer, in my opinion, the, the, the embodiment of that is the shift to a product mentality. Right. And, and the product mentality in my opinion, is what brings the business and technology teams together, right? >>Once you, once you're focused on a customer experience, that's delivered through a product or a service that's when I that's, when I started to go with the alignment problem goes away, right. Because if you look at software companies, right, I mean, we run product management models, you know, with software development teams, customer success teams, right. That, you know, the software component of these products that people are building is obviously becoming bigger and bigger, you know, in an, in many ways, right. More and more organizations are trying to model themselves over as operationally like software companies. Right. Um, they obviously have lots of other components in their business than just software, but I think that whole model of customer experience equaling product, and then the software component of product, the product is the essence of what changes that alignment equation and brings business and teams together because all of a sudden, everyone knows what the customer's experiencing. Right. And, and that, that, that makes a lot of things very clear, very quickly. >>Right. I'm just curious how far along this was as a process before, before covert hit, right. Because serendipitous, whatever. Right. But th the sudden, you know, light switch moment, everybody had to go work from home and in March 15th compared to now, we're in October, and this is going to be going on for a while, and it is a new normal and whatever that whatever's going to look like a year from now, or two years from now is TBD, you know, had you guys already started on this journey cause again, to sit down and actually declare this coalition and declare this manifesto is a lot different than just trying to do better within your own organization. >>Yeah. So we had started, uh, you know, w we definitely had started independently, you know, some, some, you know, I think people in the community know that, uh, we, we came together with a company called lean kit a handful of years ago, and I give John Terry actually one of the founders leaned to immense credit for, you know, kind of spearheading our cultural change and not, and not because of, we were just going to be, you know, bringing agile solutions to our customers, but because, you know, he believed that it was going to be a fundamentally better way for us to work. Right. And we kind of, you know, when we started with John and built, you know, out of concentric circles of momentum and, and we've gotten to the place where now it's just part of who we are, but, but I do think that, you know, COVID has, you know, um, I think pre COVID a lot of companies, you know, would, would adopt, you know, the, you would adopt digital slash agile transformation. >>Um, traditional industries may have done it as a reaction to disruption. Right. You know, and in many cases, the disruption to these traditional industries was, I would say a product oriented company, right. That probably had a larger software component, and that disruption caused a competitive issue or a customer issue that caused companies and tried to respond by transforming. I think COVID, you know, all of a sudden flatten that out, right. We literally all got disrupted. Right. And, and so all of a sudden, every one of us is dealing with some degree of market uncertainty, customer uncertainty, uh, and also know none of us were insulated from the need to be able to pivot faster, deliver incrementally, you know, and operate in a different, completely more agile way, uh, you know, post COVID. Right. Yeah. That's great. >>So again, a very, very, very timely, you know, a little bit of serendipity, a little bit of, of planning. And, you know, as, as with all important things, there's always a little bit of luck and a lot of hard work involved. So a really interesting thank you for, for your leadership, Patrick. And, you know, it really makes a statement. I think when you have a bunch of leaderships across an industry coming together and putting their name on a piece of paper, uh, that's aligned around us some principles and some values, which again, if you read them who wouldn't want to get behind these, but if it takes, you know, something a little bit more formal, uh, to kind of move the ball down the field, and then I totally get it and a really great work. Thanks for, uh, thanks for doing it. >>Oh, absolutely. No. Like I said, the first time I read it, I was like, yeah, like you said, this is all, this all makes complete sense, but just documenting it and saying it and talking about it moves the needle. I'll tell you as a company, you gotta, we're pushing really hard on, uh, you know, on our own internal strategy on diversity inclusion. Right? And, and like, once we wrote the words down about what, you know, what we aspire to be from a diversity and inclusion perspective, it's the same thing. Everybody reads the words and goes, why wouldn't we do this? Right. But until you write it down and kind of have again, a manifesto or a Terrafirma of what you're trying to accomplish, you know, then you can rally behind it. Right. As opposed to it being something that's, everybody's got their own version of the flavor. Right. And I think it's a very analogous, you know, kind of, uh, initiative, right. And, uh, and this happening, both of those things, right. Are happening across the industry these days. Right. >>And measure it too. Right. And measure it, measure, measure, measure, get a baseline. Even if you don't like to measure, even if you don't like what the, even if you can argue against the math, behind the measurement, measure it, and at least you can measure it again and you can, and you've got some type of a comp and that is really the only way to, to move it forward. Well, Patrick really enjoyed the conversation. Thanks for, uh, for taking a few minutes out of your day. >>It's great to be here. It's an awesome movement and we're glad >>That'd be part of it. All right. Thanks. And if you want to check out the biz ops, Manifesta go to biz ops, manifesto.org, read it. You might want to sign it. It's there for you. And thanks for tuning in on this segment will continuing coverage of the biz op manifesto unveil here on the cube. I'm Jeff, thanks for watching >>From around the globe. It's the cube with digital coverage of biz ops manifesto unveiled brought to you by biz ops coalition. >>Hey, welcome back, everybody Jeffrey here with the cube. We're coming to you from our Palo Alto studios. And welcome back to this event is the biz ops manifesto unveiling. So the biz ops manifesto and the biz ops coalition had been around for a little while, but today's the big day. That's kind of the big public unveiling or excited to have some of the foundational people that, you know, have put their, put their name on the dotted, if you will, to support this initiative and talk about why that initiative is so important. And so the next guest we're excited to have is dr. Mick Kirsten. He is the founder and CEO of Tasktop mic. Great to see you coming in from Vancouver, Canada, I think, right? Yes. Thank you. Absolutely. I hope your air is a little better out there. I know you had some of the worst air of all of us, a couple, a couple of weeks back. So hopefully things are, uh, are getting a little better and we get those fires under control. Yeah. >>Things have cleared up now. So yeah, it's good. It's good to be close to the U S and it's going to have the Arabic cleaner as well. >>Absolutely. So let's, let's jump into it. So you you've been an innovation guy forever starting way back in the day and Xerox park. I was so excited to do an event at Xerox park for the first time last year. I mean, that, that to me represents along with bell labs and, and some other, you know, kind of foundational innovation and technology centers, that's gotta be one of the greatest ones. So I just wonder if you could share some perspective of getting your start there at Xerox park, you know, some of the lessons you learned and what you've been able to kind of carry forward from those days. >>Yeah. I was fortunate to join Xerox park in the computer science lab there at a very early point in my career, and to be working on open source programming languages. So back then in the computer science lab, where some of the inventions around programming around software development teams, such as object oriented programming, and a lot of what we had around really modern programming levels constructs, those were the teams I have the fortune of working with, and really our goal was. And of course there's as, as you know, uh, there's just this DNA of innovation and excitement and innovation in the water. And really it was the model back then was all about changing the way that we work, uh, was looking at for how we could make it 10 times easier to write code. But this is back in 99. And we were looking at new ways of expressing, especially business concerns, especially ways of enabling people who are, who want to innovate for their business to express those concerns in code and make that 10 times easier than what that would take. >>So we create a new open source programming language, and we saw some benefits, but not quite quite what we expected. I then went and actually joined Charles Stephanie, that former to fucking Microsoft who was responsible for, he actually got Microsoft word as a spark and into Microsoft and into the hands of bill Gates on that company. I was behind the whole office suite and his vision. And then when I was trying to execute with, working for him was to make PowerPoint like a programming language, make everything completely visual. And I realized none of this was really working in that there was something else, fundamentally wrong programming languages, or new ways of building software. Like let's try and do with Charles around intentional programming. That was not enough. >>That was not enough. So, you know, the agile movement got started about 20 years ago, and we've seen the rise of dev ops and really this kind of embracing of, of, of sprints and, you know, getting away from MRDs and PRDs and these massive definitions of what we're going to build and long build cycles to this iterative process. And this has been going on for a little while. So what was still wrong? What was still missing? Why the BizOps coalition, why the biz ops manifesto? >>Yeah, so I basically think we nailed some of the things that the program language levels of teams can have effective languages deployed soften to the cloud easily now, right? And at the kind of process and collaboration and planning level agile two decades, decades ago was formed. We were adopting and all the, all the teams I was involved with and it's really become a self problem. So agile tools, agile teams, agile ways of planning, uh, are now very mature. And the whole challenge is when organizations try to scale that. And so what I realized is that the way that agile was scaling across teams and really scaling from the technology part of organization to the business was just completely flawed. The agile teams had one set of doing things, one set of metrics, one set of tools. And the way that the business was working was planning was investing in technology was just completely disconnected and using a whole different set of advisors. >>Interesting. Cause I think it's pretty clear from the software development teams in terms of what they're trying to deliver. Cause they've got a feature set, right. And they've got bugs and it's easy to, it's easy to see what they deliver, but it sounds like what you're really honing in on is this disconnect on the business side, in terms of, you know, is it the right investment? You know, are we getting the right business ROI on this investment? Was that the right feature? Should we be building another feature or should we building a completely different product set? So it sounds like it's really a core piece of this is to get the right measurement tools, the right measurement data sets so that you can make the right decisions in terms of what you're investing, you know, limited resources. You can't, no one has unlimited resources and ultimately have to decide what to do, which means you're also deciding what not to do. And it sounds like that's a really big piece of this, of this whole effort. >>Yeah. Jeff, that's exactly it, which is the way that the agile team measures their own way of working is very different from the way that you measure business outcomes. The business outcomes are in terms of how happy your customers are, but are you innovating fast enough to keep up with the pace of a rapidly changing economy, rapidly changing market. And those are, those are all around the customer. And so what I learned on this long journey of supporting many organizations transformations and having them try to apply those principles of agile and dev ops, that those are not enough, those measures technical practices, those measured sort of technical excellence of bringing code to the market. They don't actually measure business outcomes. And so I realized that it really was much more around having these entwined flow metrics that are customer centric and business centric and market centric where we need it to go. Right. >>So I want to shift gears a little bit and talk about your book because you're also a bestselling author, a project, a product, and, and, and you, you brought up this concept in your book called the flow framework. And it's really interesting to me cause I know, you know, flow on one hand is kind of a workflow and a process flow and, and you know, that's how things get done and, and, and embrace the flow. On the other hand, you know, everyone now in, in a little higher level existential way is trying to get into the flow right into the workflow and, you know, not be interrupted and get into a state where you're kind of at your highest productivity, you know, kind of your highest comfort, which flow are you talking about in your book or is it a little bit about, >>Well, that's a great question. It's not what I get asked very often. Just to me, it's absolutely both. So that the thing that we want to get to, we've learned how to master individual flow. That is this beautiful book by me, how he teaches me how he does a beautiful Ted talk by him as well about how we can take control of our own flow. So my question with the book with project replies, how can we bring that to entire teams and really entire organizations? How can we have everyone contributing to a customer outcome? And this is really what if you go to the biz ops manifesto, it says, I focus on outcomes on using data to drive whether we're delivering those outcomes rather than a focus on proxy metrics, such as, how quickly did we implement this feature? No, it's really how much value did the customer go to the feature and how quickly did you learn and how quickly did you use that data to drive to that next outcome? >>Really that with companies like Netflix and Amazon have mastered, how do we get that to every large organization, every it organization and make everyone be a software innovator. So it's to bring that co that concept of flow to these entwined value streams. And the fascinating thing is we've actually seen the data. We've been able to study a lot of value streams. We see when flow increases, when organizations deliver value to a customer faster, developers actually become more happy. So things like the employee net promoter scores rise, and we've got empirical data for this. So the beautiful thing to me is that we've actually been able to combine these two things and see the results in the data that you increase flow to the customer. Your developers are more happy. >>I love it, right, because we're all more, we're all happier when we're in the flow and we're all more productive when we're in the flow. So I, that is a great melding of, of two concepts, but let's jump into the, into the manifesto itself a little bit. And, you know, I love that, you know, took this approach really of having kind of four key values and then he gets 12 key principles. And I just want to read a couple of these values because when you read them, it sounds pretty brain dead. Right? Of course. Right. Of course you should focus on business outcomes. Of course you should have trust and collaboration. Of course you should have database decision making processes and not just intuition or, you know, whoever's the loudest person in the room, uh, and to learn and respond and pivot. But what's the value of actually just putting them on a piece of paper, because again, this is not this, these are all good, positive things, right? When somebody reads these to you or tells you these are sticks it on the wall, of course. But unfortunately of course isn't always enough. >>No. And I think what's happened is some of these core principles originally from the agile manifesto two decades ago, uh, the whole dev ops movement of the last decade of flow feedback and continue learning has been key. But a lot of organizations, especially the ones that are undergoing digital transformations have actually gone a very different way, right? The way that they measure value in technology and innovation is through costs for many organizations. The way that they actually are looking at that they're moving to cloud is actually as a reduction in cost. Whereas the right way of looking at moving to cloud is how much more quickly can we get to the value to the customer? How quickly can we learn from that? And how quickly can we drive the next business outcome? So really the key thing is, is to move away from those old ways of doing things, a funny projects and cost centers, uh, to actually funding and investing in outcomes and measuring outcomes through these flow metrics, which in the end are your fast feedback and how quickly you're innovating for your customer. >>So these things do seem, you know, very obvious when you look at them. But the key thing is what you need to stop doing to focus on these. You need to actually have accurate realtime data of how much value your phone to the customer every week, every month, every quarter. And if you don't have that, your decisions are not driven on data. If you don't know what your boggling like is, and this is something that in decades of manufacturing, a car manufacturers, other manufacturers, master, they always know where the bottom back in their production processes. You ask a random CIO when a global 500 company where their bottleneck is, and you won't get a clear answer because there's not that level of understanding. So let's, you actually follow these principles. You need to know exactly where you fall. And I guess because that's, what's making your developers miserable and frustrated around having them context, which on thrash. So it, the approach here is important and we have to stop doing these other things, >>Right? There's so much there to unpack. I love it. You know, especially the cloud conversation, because so many people look at it wrong as, as, as a cost saving device, as opposed to an innovation driver and they get stuck, they get stuck in the literal and the, and you know, I think at the same thing, always about Moore's law, right? You know, there's a lot of interesting real tech around Moore's law and the increasing power of microprocessors, but the real power, I think in Moore's laws is the attitudinal change in terms of working in a world where you know that you've got all this power and what you build and design. I think it's funny to your, your comment on the flow and the bottleneck, right? Cause, cause we know manufacturing, as soon as you fix one bottleneck, you move to your next one, right? You always move to your next point of failure. So if you're not fixing those things, you know, you're not, you're not increasing that speed down the line, unless you can identify where that bottleneck is or no matter how many improvements you make to the rest of the process, it's still going to get hung up on that one spot. >>That's exactly it. And you also make it sound so simple, but again, if you don't have the data driven visibility of where that bottom line is, and these bottlenecks are adjusted to say defense just whack them. All right. So we need to understand is the bottleneck because our security reviews are taking too long and stopping us from getting value for the customer. If it's that automate that process. And then you move on to the next bottleneck, which might actually be that deploying yourself into the cloud. It's taking too long. But if you don't take that approach of going flow first, rather than again, that sort of cost reduction. First, you have to think of the approach of customer centricity and you only focused on optimizing costs. Your costs will increase and your flow will slow down. And this is just one of these fascinating things. >>Whereas if you focus on getting closer to the customer and reducing your cycles out on getting value, your flow time from six months to two weeks or two, one week or two event, as we see with the tech giants, you actually can both lower your costs and get much more value for us to get that learning loop going. So I think I've, I've seen all these cloud deployments and one of the things happened that delivered almost no value because there was such big bottlenecks upfront in the process and actually the hosting and the AP testing was not even possible with all of those inefficiencies. So that's why going float us rather than costs when we started our project versus silky. >>I love that. And, and, and, and it, it begs repeating to that right within the subscription economy, you know, you're on the hook to deliver value every single month because they're paying you every single month. So if you're not on top of how you're delivering value, you're going to get sideways because it's not like they pay a big down payment and a small maintenance fee every month. But once you're in a subscription relationship, you know, you have to constantly be delivering value and upgrading that value because you're constantly taking money from the customer. So it's such a different kind of relationship than kind of the classic, you know, big bang with a maintenance agreement on the back end really important. Yeah. >>And I think in terms of industry shifts that that's, it that's, what's catalyzed. This industry shift is in this SAS and subscription economy. If you're not delivering more and more value to your customers, someone else's, and they're winning the business, not you. So, one way we know is to delight our customers with great user experience as well. That really is based on how many features you delivered or how much, how much, how many quality improvements or scalar performance improvements we delivered. So the problem is, and this is what the business manifesto, as well as the flow frame of touch on is if you can't measure how much value you deliver to a customer, what are you measuring? You just backed again, measuring costs, and that's not a measure of value. So we have to shift quickly away from measuring costs to measuring value, to survive. And in the subscription economy, >>We could go for days and days and days. I want to shift gears a little bit into data and, and a data driven decision making a data driven organization cause right day has been talked about for a long time, the huge big data meme with, with Hadoop over, over several years and, and data warehouses and data lakes and data oceans and data swamps. And you can go on and on and on. It's not that easy to do, right? And at the same time, the proliferation of data is growing exponentially. We're just around the corner from, from IOT and five G. So now the accumulation of data at machine scale, again, is this gonna overwhelm? And one of the really interesting principles, uh, that I wanted to call out and get your take right, is today's organizations generate more data than humans can process. So informed decisions must be augmented by machine learning and artificial intelligence. I wonder if you can, again, you've got some great historical perspective, um, reflect on how hard it is to get the right data, to get the data in the right context, and then to deliver it to the decision makers and then trust the decision makers to actually make the data and move that down. You know, it's kind of this democratization process into more and more people and more and more frontline jobs making more and more of these little decisions every day. >>Yeah. I definitely think the front parts of what you said are where the promises of big data have completely fallen on their face into the swamps as, as you mentioned, because if you don't have the data in the right format, you've cannot connect, collected that the right way you want it, that way, the right way you can't use human or machine learning on it effectively. And there've been the number of data where, how has this in a typical enterprise organization and the sheer investment is tremendous, but the amount of intelligence being extracted from those is, is, is a very big problem. So the key thing that I've noticed is that if you can model your value streams, so you actually understand how you're innovating, how you're measuring the delivery of value and how long that takes, what is your time to value through these metrics like full time? >>You can actually use both the intelligence that you've got around the table and push that down as well, as far as getting to the organization, but you can actually start using that those models to understand and find patterns and detect bottlenecks that might be surprising, right? Well, you can detect interesting bottlenecks when you shift to work from home. We detected all sorts of interesting bottlenecks in our own organization that were not intuitive to me that have to do with, you know, more senior people being overloaded and creating bottlenecks where they didn't exist. Whereas we thought we were actually an organization that was very good at working from home because of our open source roots. So the data is highly complex. Software value streams are extremely complicated. And the only way to really get the proper analysts and data is to model it properly and then to leverage these machine learning and AI techniques that we have. But that front part of what you said is where organizations are just extremely immature in what I've seen, where they've got data from all their tools, but not modeled in the right way. Right, right. >>Right. Well, all right. So before I let you go, you know, let's say you get a business leader. He, he buys in, he reads the manifesto, he signs on the dotted line and he says, Mick, how do I get started? I want to be more aligned with the, with the development teams. I know I'm in a very competitive space. We need to be putting out new software features and engage with our customers. I want to be more data-driven how do I get started? Well, you know, what's the biggest inhibitor for most people to get started and get some early wins, which we know is always the key to success in any kind of a new initiative. >>Right? So I think you can reach out to us through the website, uh, for the manifesto. But the key thing is just, it's definitely set up it's to get started and to get the key wins. So take a product value stream. That's mission critical if it'd be on your mobile and web experiences or part of your cloud modernization platform where your analytics pipeline, but take that and actually apply these principles to it and measure the end to end flow of value. Make sure you have a value metric that everyone is on the same page on, but the people on the development teams that people in leadership all the way up to the CEO, and one of the, where I encourage you to start is actually that end to end flow time, right? That is the number one metric. That is how you measure it, whether you're getting the benefit of your cloud modernization, that is the one metric that when the people I respect tremendously put into his cloud for CEOs, the metric, the one, the one way to measure innovation. So basically take these principles, deploy them on one product value stream measure, Antonin flow time, uh, and then you'll actually be well on your path to transforming and to applying the concepts of agile and dev ops all the way to, to the, to the way >>You're offering model. >>Well, Mick really great tips, really fun to catch up. I look forward to a time when we can actually sit across the table and, and get into this. Cause I just, I just love the perspective and, you know, you're very fortunate to have that foundational, that foundational base coming from Xerox park and they get, you know, it's, it's a very magical place with a magical history. So to, to incorporate that into, continue to spread that well, uh, you know, good for you through the book and through your company. So thanks for sharing your insight with us today. >>Thanks so much for having me, Jeff. Absolutely. >>All right. And go to the biz ops manifesto.org, read it, check it out. If you want to sign it, sign it. They'd love to have you do it. Stay with us for continuing coverage of the unveiling of the business manifesto on the cube. I'm Jeff. Rick. Thanks for watching. See you next time >>From around the globe. It's the cube with digital coverage, a biz ops manifesto unveiled brought to you by biz ops coalition. >>Hey, welcome back. You're ready. Jeff Frick here with the cube for our ongoing coverage of the big unveil. It's the biz ops manifesto manifesto unveil. And we're going to start that again from the top three And a Festo >>Five, four, three, two. >>Hey, welcome back everybody. Jeff Frick here with the cube come to you from our Palo Alto studios today for a big, big reveal. We're excited to be here. It's the biz ops manifesto unveiling a thing's been in the works for a while and we're excited to have our next guest. One of the, really the powers behind this whole effort. And he's joining us from Boston it's surge, Lucio, the vice president, and general manager enterprise software division at Broadcom surge. Great to see you. >>Hi, good to see you, Jeff. Glad to be here. >>Absolutely. So you've been in this business for a very long time. You've seen a lot of changes in technology. What is the biz ops manifesto? What is this coalition all about? Why do we need this today and in 2020? >>Yeah. So, so I've been in this business for close to 25 years, right? So about 20 years ago, the agile manifesto was created. And the goal of the agile manifesto was really to address the uncertainty around software development and the inability to predict the efforts to build software. And, uh, if you, if you roll that kind of 20 years later, and if you look at the current state of the industry of the product, the project management Institute, estimates that we're wasting about a million dollars, every 20 seconds in digital transformation initiatives that do not deliver on business results. In fact, we were recently served a third of the, a, a number of executives in partnership with Harvard >>Business review and 77% of those executives think that one of the key challenges that they have is really the collaboration between business and it, and that that's been kind of a case for, uh, almost 20 years now. Um, so the, the, the key challenge that we're faced with is really that we need a new approach. And many of the players in the industry, including ourselves have been using different terms, right? Some are being, are talking about value stream management. Some are talking about software delivery management. If you look at the site, reliability engineering movement, in many ways, it embodies a lot of these kind of concepts and principles. So we believed that it became really imperative for us to crystallize around, could have one concept. And so in many ways, the, a, the BizOps concept and the BizOps manifesto are bringing together a number of ideas, which has been emerging in the last five years or so, and, and defining the key values and principles to finally help these organizations truly transform and become digital businesses. And so the hope is that by joining our forces and defining public key principles and values, we can help the industry, uh, not just, uh, by, you know, providing them with support, but also tools and consulting that is required for them to truly achieve the kind of transformation that everybody's taking. >>Right. Right. So COVID now we're six months into it, approximately seven months into it. Um, a lot of pain, a lot of bad stuff still happening. We've got a ways to go, but one of the things that on the positive side, right, and you've seen all the memes and social media is, is a driver of digital transformation and a driver of change. Cause we had this light switch moment in the middle of March, and there was no more planning. There was no more conversation. You've suddenly got remote workforces, everybody's working from home and you got to go, right. So the reliance on these tools increases dramatically, but I'm curious, you know, kind of short of, of the beginnings of this effort in short of kind of COVID, which, you know, came along unexpectedly. I mean, what were those inhibitors because we've been making software for a very long time, right? The software development community has, has adopted kind of rapid change and, and iterative, uh, delivery and, and sprints, what was holding back the connection with the business side to make sure that those investments were properly aligned with outcomes. >>Well, so, so you have to understand that it is, is kind of a its own silos. And traditionally it has been treated as a cost center within large organizations and not as a value center. And so as a result, kind of a, the traditional dynamic between it and the business is basically one of a kind of supplier up to kind of a business. Um, and you know, if you go back to, uh, I think you'll unmask a few years ago, um, basically at this concept of the machines to build the machines and you went as far as saying that, uh, the, the machines or the production line is actually the product. So, uh, meaning that the core of the innovation is really about, uh, building, could it be engine to deliver on the value? And so in many ways, you know, we, we have missed on this shift from, um, kind of it becoming this kind of value center within the enterprises and end. >>He talks about culture. Now, culture is a, is a sum total of behaviors. And the reality is that if you look at it, especially in the last decade, uh, we've agile with dev ops with, um, I bring infrastructures, uh, it's, it's way more volatile today than it was 10 years ago. And so the, when you start to look at the velocity of the data, the volume of data, the variety of data to analyze the system, um, it's, it's very challenging for it to actually even understand and optimize its own processes, let alone, um, to actually include business as sort of an integral part of kind of a delivery chain. And so it's both kind of a combination of, of culture, um, which is required, uh, as well as tools, right? To be able to start to bring together all these data together, and then given the volume of variety of philosophy of the data. Uh, we have to apply some core technologies, which have only really, truly emerged in the last five to 10 years around machine learning and analytics. And so it's really kind of a combination of those freaks, which are coming together today, truly out organizations kind of get to the next level. Right, >>Right. So let's talk about the manifesto. Let's talk about, uh, the coalition, uh, the BizOps coalition. I just liked that you put down these really simple, you know, kind of straightforward core values. You guys have four core values that you're highlighting, you know, business outcomes, over individual projects and outputs, trust, and collaboration, oversight, load teams, and organizations, data driven decisions, what you just talked about, uh, you know, over opinions and judgment and learned, respond and pivot. I mean, surgery sounds like pretty basic stuff, right? I mean, aren't, isn't everyone working to these values already. And I think he touched on it on culture, right? Trust and collaboration, data driven decisions. I mean, these are fundamental ways that people must run their business today, or the person that's across the street, that's doing it. It's going to knock them out right off their block. >>Yeah. So that's very true. But, uh, so I'll, I'll mention an hour survey. We did, uh, I think about six months ago and it was in partnership with, uh, with, uh, an industry analyst and we serve at a, again, a number of it executives to understand only we're tracking business outcomes. I'm going to get the software executives, it executives we're tracking business outcomes. And the, there were less than 15% of these executives were actually tracking the outcomes of the software delivery. And you see that every day. Right? So in my own teams, for instance, we've been adopting a lot of these core principles in the last year or so, and we've uncovered that 16% of our resources were basically aligned around initiatives, which are not strategic for us. Um, I take another example, for instance, one of our customers in the, uh, in the airline industry and Harvard, for instance, that a number of, uh, um, that they had software issues that led to people searching for flights and not returning any kind of availability. >>And yet, um, you know, the it teams, whether it's operation software environments were completely oblivious to that because they were completely blindsided to it. And so the connectivity between kind of the inwards metrics that RT is using, whether it's database time, cycle time, or whatever metric we use in it are typically completely divorced from the business metrics. And so at its core, it's really about starting to align the business metrics with the, the, the software delivery chain, right? This, uh, the system, which is really a core differentiator for these organizations. It's about connecting those two things and starting to, um, infuse some of the agile culture and principles. Um, that's emerged from the software side into the business side. Um, of course the lean movement and other movements have started to change some of these dynamics on the business side. And so I think this, this is the moment where we are starting to see kind of the imperative to transform. Now, you know, Covina obviously has been a key driver for that. The, um, the technology is right to start to be able to weave data together and really kind of, uh, also the cultural shifts, uh, Prue agile through dev ops through, uh, the SRE movement, uh frulein um, business transformation, all these things are coming together and that are really creating kind of the conditions for the BizOps manifestor to exist, >>Uh, Clayton Christianson, great, uh, Harvard professor innovator's dilemma might steal my all time. Favorite business books, you know, talks about how difficult it is for incumbents to react to, to disruptive change, right? Because they're always working on incremental change cause that's what their customers are asking for. And there's a good ROI when you talk about, you know, companies not measuring the right thing. I mean, clearly it has some portion of their budget that has to go to keeping the lights on, right. That that's always the case, but hopefully that's an ever decreasing percentage of their total activity. So, you know, what should people be measuring? I mean, what are kind of the new metrics, um, in, in biz ops that drive people to be looking at the right things, measuring the right things and subsequently making the right decisions, investment decisions on whether they should do, you know, move project a along or project B. >>So there, there are only two things, right? So, so I think what you're talking about is portfolio management, investment management, right. And, um, which, which is a key challenge, right? Um, in my own experience, right? Uh, driving strategy or a large scale kind of software organization for years, um, it's very difficult to even get kind of a base data as to who is doing what, uh, um, I mean, some of our largest customers we're engaged with right now are simply trying to get a very simple answer, which is how many people do I have and that specific initiative at any point in time and just tracking that information is extremely difficult. So, and, and again, back to a product project management Institute, um, they're, they've estimated that on average, it organizations have anywhere between 10 to 20% of their resources focused on initiatives, which are not strategically aligned. >>So that's one dimension on portfolio management. I think the key aspect though, that we are really keen on is really around kind of the alignment of a business metrics to the it metrics. Um, so I'll use kind of two simple examples, right? And my background is around quality. And so I've always believed that fitness for purpose is really kind of a key, um, uh, philosophy if you will. And so if you start to think about quality as fitness for purpose, you start to look at it from a customer point of view, right. And fitness for purpose for core banking application or mobile application are different, right? So the definition of a business value that you're trying to achieve is different. Um, and so the, and yet, if you look at our, it, operations are operating, they were using kind of a same type of, uh, kind of inward metrics, uh, like a database of time or a cycle time, or what is my point of velocity, right? >>And, uh, and so the challenge really is this inward facing metrics that it is using, which are divorced from ultimately the outcome. And so, you know, if I'm, if I'm trying to build a poor banking application, my core metric is likely going to be uptime, right? If I'm trying to build a mobile application or maybe your social mobile app, it's probably going to be engagement. And so what you want is for everybody across it, to look at these metric, and what's hard, the metrics within the software delivery chain, which ultimately contribute to that business metric and some cases cycle time may be completely irrelevant, right? Again, my core banking app, maybe I don't care about cycle time. And so it's really about aligning those metrics and be able to start to differentiate, um, the key challenges you mentioned, uh, around the, the, um, uh, around the disruption that we see is, or the investors is the dilemma now is really around the fact that many it organizations are essentially applying the same approaches of, for innovation, right, for basically scrap work, then they would apply to kind of over more traditional projects. And so, you know, there's been a lot of talk about two-speed it, and yes, it exists, but in reality are really organizations, um, truly differentiating, um, all of the operate, their, their projects and products based on the outcomes that they're trying to achieve. And this is really where BizOps is trying to affect. >>I love that, you know, again, it doesn't seem like brain surgery, but focus on the outcomes, right. And it's horses for courses, as you said, this project, you know, what you're measuring and how you define success, isn't necessarily the same as, as on this other project. So let's talk about some of the principles we've talked about the values, but, you know, I think it's interesting that, that, that the BizOps coalition, you know, just basically took the time to write these things down and they don't seem all that, uh, super insightful, but I guess you just gotta get them down and have them on paper and have them in front of your face. But I want to talk about, you know, one of the key ones, which you just talked about, which is changing requirements, right. And working in a dynamic situation, which is really what's driven, you know, this, the software to change in software development, because, you know, if you're in a game app and your competitor comes out with a new blue sword, you've got to come out with a new blue sword. >>So whether you had that on your Kanban wall or not. So it's, it's really this embracing of the speed of change and, and, and, and making that, you know, the rule, not the exception. I think that's a phenomenal one. And the other one you talked about is data, right? And that today's organizations generate more data than humans can process. So informed decisions must be generated by machine learning and AI, and, you know, in the, the big data thing with Hadoop, you know, started years ago, but we are seeing more and more that people are finally figuring it out, that it's not just big data, and it's not even generic machine learning or artificial intelligence, but it's applying those particular data sets and that particular types of algorithms to a specific problem, to your point, to try to actually reach an objective, whether that's, you know, increasing the, your average ticket or, you know, increasing your checkout rate with, with, with shopping carts that don't get left behind and these types of things. So it's a really different way to think about the world in the good old days, probably when you got started, when we had big, giant, you know, MRDs and PRDs and sat down and coded for two years and came out with a product release and hopefully not too many patches subsequently to that. >>It's interesting. Right. Um, again, back to one of these surveys that we did with, uh, with about 600, the ITA executives, and, uh, and, and we, we purposely designed those questions to be pretty open. Um, and, and one of them was really role requirements and, uh, and it was really a wrong kind of what do you, what is the best approach? What is your preferred approach towards requirements? And if I remember correctly over 80% of the it executives set that the best approach they'll prefer to approach is for requirements to be completely defined before software development starts. Let me pause there where 20 years after the agile manifesto, right? And for 80% of these idea executives to basically claim that the best approach is for requirements to be fully baked before salt, before software development starts, basically shows that we still have a very major issue. >>And again, our hypothesis in working with many organizations is that the key challenge is really the boundary between business and it, which is still very much contract based. If you look at the business side, they basically are expecting for it deliver on time on budget, right. But what is the incentive for it to actually delivering all the business outcomes, right? How often is it measured on the business outcomes and not on an SLA or on a budget type criteria. And so that, that's really the fundamental shift that we need to, we really need to drive up as an industry. Um, and you know, we, we talk about kind of this, this imperative for organizations to operate that's one, and back to the innovator's dilemma. The key difference between these larger organization is, is really kind of a, if you look at the amount of capital investment that they can put into pretty much anything, why are they losing compared to, um, you know, startups? What, why is it that, uh, more than 40% of, uh, personal loans today or issued not by your traditional brick and mortar banks, but by, um, startups? Well, the reason, yes, it's the traditional culture of doing incremental changes and not disrupting ourselves, which Christiansen covered at length, but it's also the inability to really fundamentally change kind of a dynamic picture. We can business it and, and, and partner right. To, to deliver on a specific business outcome. Right. >>I love that. That's a great, that's a great summary. And in fact, getting ready for this interview, I saw you mentioning another thing where, you know, the, the problem with the agile development is that you're actually now getting more silos because you have all these autonomous people working, you know, kind of independently. So it's even a harder challenge for, for the business leaders to, to, to, as you said, to know, what's actually going on, but, but certainly I w I want to close, um, and talk about the coalition. Um, so clearly these are all great concepts. These are concepts you want to apply to your business every day. Why the coalition, why, you know, take these concepts out to a broader audience, including your, your competition and, and the broader industry to say, Hey, we, as a group need to put a stamp of approval on these concepts, values, these principles. >>So, first I think we, we want, um, everybody to realize that we are all talking about the same things, the same concepts. I think we were all from our own different vantage point, realizing that, um, things after change, and again, back to, you know, whether it's value stream management or site reliability engineering, or biz ops, we're all kind of using slightly different languages. Um, and so I think one of the important aspects of BizOps is for us, all of us, whether we're talking about, you know, consulting agile transformation experts, uh, whether we're talking about vendors, right, provides kind of tools and technologies, or these large enterprises to transform for all of us to basically have kind of a reference that lets us speak around kind of, um, in a much more consistent way. The second aspect is for, to me is for, um, these concepts to start to be embraced, not just by us or trying, or, you know, vendors, um, system integrators, consulting firms, educators, thought leaders, but also for some of our old customers to start to become evangelists of their own in the industry. >>So we, our, our objective with the coalition needs to be pretty, pretty broad. Um, and our hope is by, by starting to basically educate, um, our, our joint customers or partners, that we can start to really foster these behaviors and start to really change, uh, some of dynamics. So we're very pleased at if you look at, uh, some of the companies which have joined the, the, the, the manifesto. Um, so we have vendors and suggest desktop or advance, or, um, uh, PagerDuty for instance, or even planned view, uh, one of my direct competitors, um, but also thought leaders like Tom Davenport or, uh, or cap Gemini or, um, um, smaller firms like, uh, business agility, institutes, or agility elf. Um, and so our, our goal really is to start to bring together, uh, thought leaders, people who have been LP, larger organizations do digital transformation vendors, were providing the technologies that many of these organizations use to deliver on these digital preservation and for all of us to start to provide the kind of, uh, education support and tools that the industry needs. Yeah, >>That's great surge. And, uh, you know, congratulations to you and the team. I know this has been going on for a while, putting all this together, getting people to sign onto the manifesto, putting the coalition together, and finally today getting to unveil it to the world in a little bit more of a public, uh, opportunity. So again, you know, really good values, really simple principles, something that, that, uh, shouldn't have to be written down, but it's nice cause it is, and now you can print it out and stick it on your wall. So thank you for, uh, for sharing this story. And again, congrats to you and the team. Thank you. Appreciate it. My pleasure. Alrighty, surge. If you want to learn more about the biz ops, Manifesta go to biz ops manifesto.org, read it, and you can sign it and you can stay here for more coverage. I'm the cube of the biz ops manifesto unveiled. Thanks for watching. See you next time >>From around the globe. It's the cube with digital coverage of this ops manifesto unveiled and brought to you by >>This obstacle volition. Hey, welcome back, everybody Jeffrey here with the cube. Welcome back to our ongoing coverage of the biz ops manifesto unveiling. It's been in the works for awhile, but today's the day that it actually kind of come out to the, to the public. And we're excited to have a real industry luminary here to talk about what's going on, why this is important and share his perspective. And we're happy to have from Cape Cod, I believe is Tom Davenport. He's a distinguished author and professor at Babson college. We could go on, he's got a lot of great titles and, and really illuminary in the area of big data and analytics Thomas. Great to see you. >>Thanks Jeff. Happy to be here with you. >>Great. So let's just jump into it, you know, and getting ready for this. I came across your LinkedIn posts. I think you did earlier this summer in June and right off the bat, the first sentence just grabbed my attention. I'm always interested in new attempts to address longterm issues, uh, in how technology works within businesses, biz ops. What did you see in biz ops, uh, that, that kind of addresses one of these really big longterm problems? >>Well, yeah, but the longterm problem is that we've had a poor connection between business people and it people between business objectives and the, it solutions that address them. This has been going on, I think since the beginning of information technology and sadly it hasn't gone away. And so biz ops is a new attempt to deal with that issue with a, you know, a new framework, eventually a broad set of solutions that increase the likelihood that will actually solve a business problem with an it capability. >>Right. You know, it's interesting to compare it with like dev ops, which I think a lot of people are probably familiar with, which was, you know, built around, uh, agile software development and a theory that we want to embrace change that that changes. Okay. And we want to be able to iterate quickly and incorporate that. And that's been happening in the software world for, for 20 plus years. What's taken so long to get that to the business side, because as the pace of change has changed on the software side, you know, that's a strategic issue in terms of execution, the business side that they need now to change priorities. And, you know, there's no PRDs and MRDs and big, giant strategic plans that sit on the shelf for five years. That's just not the way business works anymore. It took a long time to get here. >>Yeah, it did. And, you know, there had been previous attempts to make a better connection between business and it, there was the so called strategic alignment framework that a couple of friends of mine from Boston university developed, I think more than 20 years ago, but you know, now we have better technology for creating that linkage. And the, you know, the idea of kind of ops oriented frameworks is pretty pervasive now. So I think it's time for another serious attempt at it. >>And do you think doing it this way, right. With the, with the BizOps coalition, you know, getting a collection of, of, of kind of likeminded individuals and companies together, and actually even having a manifesto, which we're making this declarative statement of, of principles and values, you think that's what it takes to kind of drive this kind of beyond the experiment and actually, you know, get it done and really start to see some results in, in, uh, in production in the field. >>I think certainly no one vendor organization can pull this off single handedly. It does require a number of organizations collaborating and working together. So I think our coalition is a good idea and a manifesto is just a good way to kind of lay out what you see as the key principles of the idea. And that makes it much easier for everybody to understand and act on. >>I, I think it's just, it's really interesting having, you know, having them written down on paper and having it just be so clearly articulated both in terms of the, of the values as well as, as the, uh, the principles and the values, you know, business outcomes matter trust and collaboration, data-driven decisions, which is the number three of four, and then learn, respond and pivot. It doesn't seem like those should have to be spelled out so clearly, but, but obviously it helps to have them there. You can stick them on the wall and kind of remember what your priorities are, but you're the data guy. You're the analytics guy, uh, and a big piece of this is data and analytics and moving to data driven decisions. And principle number seven says, you know, today's organizations generate more data than humans can process and informed decisions can be augmented by machine learning and artificial intelligence right up your alley. You know, you've talked a number of times on kind of the mini stages of analytics. Um, and how has that evolved over over time, you know, as you think of analytics and machine learning, driving decisions beyond supporting decisions, but actually starting to make decisions in machine time. What's that, what's that thing for you? What does that make you, you know, start to think, wow, this is this going to be pretty significant. >>Yeah. Well, you know, this has been a longterm interest of mine. Um, the last generation of AI, I was very interested in expert systems. And then, um, I think, uh, more than 10 years ago, I wrote an article about automated decision-making using what was available then, which was rule-based approaches. Um, but you know, this addresses an issue that we've always had with analytics and AI. Um, you know, we, we tended to refer to those things as providing decision support, but the problem is that if the decision maker didn't want their support, didn't want to use them in order to make a decision, they didn't provide any value. And so the nice thing about automating decisions, um, with now contemporary AI tools is that we can ensure that data and analytics get brought into the decision without any possible disconnection. Now, I think humans still have something to add here, and we often will need to examine how that decision is being made and maybe even have the ability to override it. But in general, I think at least for, you know, repetitive tactical decisions, um, involving a lot of data, we want most of those, I think to be at least, um, recommended if not totally made by an algorithm or an AI based system. And that I believe would add to, um, the quality and the precision and the accuracy of decisions and in most organizations, >>No, I think, I think you just answered my next question before I, before I asked it, you know, we had dr. Robert Gates on the former secretary of defense on a few years back, and we were talking about machines and machines making decisions. And he said at that time, you know, the only weapon systems, uh, that actually had an automated trigger on it were on the North Korea and South Korea border. Um, everything else, as you said, had to go through a sub person before the final decision was made. And my question is, you know, what are kind of the attributes of the decision that enable us to more easily automated? And then how do you see that kind of morphing over time, both as the data to support that as well as our comfort level, um, enables us to turn more and more actual decisions over to the machine? >>Well, yeah, as I suggested we need, um, data and the data that we have to kind of train our models has to be high quality and current, and we need to know the outcomes of that data. You know, um, most machine learning models, at least in business are supervised. And that means we need to have labeled outcomes in the, in the training data. But I, you know, um, the pandemic that we're living through is a good illustration of the fact that, that the data also have to be reflective of current reality. And, you know, one of the things that we're finding out quite frequently these days is that, um, the data that we have do not reflect, you know, what it's like to do business in a pandemic. Um, I wrote a little piece about this recently with Jeff cam at wake forest university, we call it data science quarantined, and we interviewed with somebody who said, you know, it's amazing what eight weeks of zeros will do to your demand forecast. We just don't really know what happens in a pandemic. Um, our models maybe have to be put on the shelf for a little while and until we can develop some new ones or we can get some other guidelines into making decisions. So I think that's one of the key things with automated decision making. We have to make sure that the data from the past and that's all we have of course, is a good guide to, you know, what's happening in the present and the future as far as we understand it. >>Yeah. I used to joke when we started this calendar year 2020, it was finally the year that we know everything with the benefit of hindsight, but I turned down 20, 20 a year. We found out we actually know nothing and everything and thought we knew, but I want to, I want to follow up on that because you know, it did suddenly change everything, right? We've got this light switch moment. Everybody's working from home now we're many, many months into it, and it's going to continue for a while. I saw your interview with Bernard Marr and you had a really interesting comment that now we have to deal with this change. We don't have a lot of data and you talked about hold fold or double down. And, and I can't think of a more, you know, kind of appropriate metaphor for driving the value of the biz ops when now your whole portfolio strategy, um, these to really be questioned and, and, you know, you have to be really, uh, well, uh, executing on what you are, holding, what you're folding and what you're doubling down with this completely new environment. >>Well, yeah, and I hope I did this in the interview. I would like to say that I came up with that term, but it actually came from a friend of mine. Who's a senior executive at Genpact. And, um, I, um, used it mostly to talk about AI and AI applications, but I think you could, you could use it much more broadly to talk about your entire sort of portfolio of digital projects. You need to think about, well, um, given some constraints on resources and a difficult economy for a while, which of our projects do we want to keep going on pretty much the way we were and which ones are not that necessary anymore? You see a lot of that in AI, because we had so many pilots, somebody told me, you know, we've got more pilots around here than O'Hare airport and, and AI. Um, and then, but the ones that involve doubled down, they're even more important to you. They are, you know, a lot of organizations have found this out, um, in the pandemic on digital projects, it's more and more important for customers to be able to interact with you, um, digitally. And so you certainly wouldn't want to cancel those projects or put them on hold. So you double down on them and get them done faster and better. Right, >>Right. Uh, another, another thing that came up in my research that, that you quoted, um, was, was from Jeff Bezos, talking about the great bulk of what we do is quietly, but meaningfully improving core operations. You know, I think that is so core to this concept of not AI and machine learning and kind of the general sense, which, which gets way too much buzz, but really applied right. Applied to a specific problem. And that's where you start to see the value. And, you know, the, the BizOps, uh, manifesto is, is, is calling it out in this particular process. But I'd love to get your perspective as you know, you speak generally about this topic all the time, but how people should really be thinking about where are the applications where I can apply this technology to get direct business value. >>Yeah, well, you know, even talking about automated decisions, um, uh, the kind of once in a lifetime decisions, uh, the ones that, um, ag Lafley, the former CEO of Procter and gamble used to call the big swing decisions. You only get a few of those. He said in your tenure as CEO, those are probably not going to be the ones that you're automating in part because, um, you don't have much data about them. You're only making them a few times and in part, because, um, they really require that big picture thinking and the ability to kind of anticipate the future, that the best human decision makers, um, have. Um, but, um, in general, I think where they, I, the projects that are working well are, you know, what I call the low hanging fruit ones, the, some people even report to it referred to it as boring AI. >>So, you know, sucking data out of a contract in order to compare it to a bill of lading for what arrived at your supply chain companies can save or make a lot of money with that kind of comparison. It's not the most exciting thing, but AI, as you suggested is really good at those narrow kinds of tasks. It's not so good at the, at the really big moonshots, like curing cancer or, you know, figuring out well what's the best stock or bond under all or even autonomous vehicles. Um, we, we made some great progress in that area, but everybody seems to agree that they're not going to be perfect for quite a while, and we really don't want to be driving around on, um, and then very much unless they're, you know, good and all kinds of weather and with all kinds of pedestrian traffic and you know, that sort of thing, right? >>That's funny you bring up contract management. I had a buddy years ago, they had a startup around contract management and I've like, and this was way before we had the compute power today and cloud proliferation. I said, you know, how can you possibly build software around contract management? It's language, it's legal, ease. It's very specific. And he's like, Jeff, we just need to know where's the contract. And when does it expire? And who's the signatory. And he built a business on those, you know, very simple little facts that weren't being covered because their contracts are in people's drawers and files and homes. And Lord only knows. So it's really interesting, as you said, these kind of low hanging fruit opportunities where you can extract a lot of business value without trying to, you know, boil the ocean. >>Yeah. I mean, if you're Amazon, um, uh, Jeff Bezos thinks it's important to have some kind of billion dollar project. And he even says it's important to have a billion dollar failure or two every year. But I think most organizations probably are better off being a little less aggressive and, you know, sticking to, um, what AI has been doing for a long time, which is, you know, making smarter decisions based on, based on data. >>Right? So Tom, I want to shift gears one more time before, before we let you go on, on kind of a new topic for you, not really new, but you know, not, not a, the vast majority of, of your publications and that's the new way to work, you know, as, as the pandemic hit in mid March, right. And we had this light switch moment, everybody had to work from home and it was, you know, kind of crisis and get everybody set up. Well, you know, now we're five months, six months, seven months. A number of companies have said that people are not going to be going back to work for a while. And so we're going to continue on this for a while. And then even when it's not what it is now, it's not going to be what it was before. So, you know, I wonder, and I know you, you, uh, you teased, you're working on a new book, you know, some of your thoughts on, you know, kind of this new way to work and, and, and the human factors in this new, this new kind of reality that we're kind of evolving into, I guess. >>Yeah. I missed was an interest of mine. I think, um, back in the nineties, I wrote an article called, um, a coauthored, an article called two cheers for the virtual office. And, you know, it was just starting to emerge. Then some people were very excited about it. Some people were skeptical and, uh, we said two cheers rather than three cheers because clearly there's some shortcomings. And, you know, I keep seeing these pop up. It's great that we can work from our homes. It's great that we can, most of what we need to do with a digital interface, but, um, you know, things like innovation and creativity, and certainly, um, uh, a good, um, happy social life kind of requires some face to face contact every now and then. And so I, you know, I think we'll go back to an environment where there is some of that. >>Um, we'll have, um, times when people convene in one place so they can get to know each other face to face and learn from each other that way. And most of the time, I think it's a huge waste of people's time to commute into the office every day and to jump on airplanes, to, to, um, give every little, um, uh, sales call or give every little presentation. Uh, we just have to really narrow down what are the circumstances where face to face contact really matters. And when can we get by with digital? You know, I think one of the things in my current work I'm finding is that even when you have AI based decision making, you really need a good platform in which that all takes place. So in addition to these virtual platforms, we need to develop platforms that kind of structure the workflow for us and tell us what we should be doing next, then make automated decisions when necessary. And I think that ultimately is a big part of biz ops as well. It's not just the intelligence of an AI system, but it's the flow of work that kind of keeps things moving smoothly throughout your organization. >>I think such, such a huge opportunity as you just said, cause I forget the stats on how often we're interrupted with notifications between email texts, Slack, a sauna, Salesforce, the list goes on and on. So, you know, to put an AI layer between the person and all these systems that are begging for attention, you've written a book on the attention economy, which is a whole nother topic, we'll say for another day, you know, it, it really begs, it really begs for some assistance because you know, you just can't get him picked, you know, every two minutes and really get quality work done. It's just not, it's just not realistic. And you know what? I don't think that's a feature that we're looking for. >>I agree. Totally >>Tom. Well, thank you so much for your time. Really enjoyed the conversation. I got to dig into the library. It's very long. So I might start at the attention economy. I haven't read that one. And to me, I think that's the fascinating thing in which we're living. So thank you for your time and, uh, great to see you. >>My pleasure, Jeff. Great to be here. >>All right. He's Tom I'm Jeff. You are watching the continuing coverage of the biz ops manifesto and Vail. Thanks for watching the cube. We'll see you next time.

>>from around the globe. It's the Cube with digital coverage of biz ops Manifesto unveiled. Brought to you by biz ops Coalition. Hey, welcome back your body, Jeffrey here with the Cube. Welcome back to our ongoing coverage of the busy ops manifesto unveiling its been in the works for a while. But today is the day that it actually kind of come out to the to the public. And we're excited to have a real industry luminary here to talk about what's going on, Why this is important and share his perspective. And we're happy to have from Cape Cod, I believe, is Tom Davenport. He is a distinguished author on professor at Babson College. We could go on. He's got a lot of great titles and and really illuminate airy in the area of big data and analytics. Thomas, great to see you. >>Thanks, Jeff. Happy to be here with you. Great. >>So let's just jump into it, you know, and getting ready for this. I came across your LinkedIn post. I think you did earlier this summer in June and right off the bat, the first sentence just grabbed my attention. I'm always interested in new attempts to address long term issues, Uh, in how technology works within businesses. Biz ops. What did you see in biz ops? That that kind of addresses one of these really big long term problems? >>Well, yeah. The long term problem is that we've had a poor connection between business people and I t people between business objectives and the i t. Solutions that address them. This has been going on, I think, since the beginning of information technology, and sadly, it hasn't gone away. And so busy ops is new attempt to deal with that issue with a, you know, a new framework. Eventually a broad set of solutions that increase the likelihood that will actually solve a business problem with a nightie capability. >>Right. You know, it's interesting to compare it with, like, Dev ops, which I think a lot of people are probably familiar with, which was, you know, built around a agile software development and the theory that we want to embrace change that that changes okay on. We wanna be able to iterate quickly and incorporate that, and that's been happening in the software world for for 20 plus years. What's taking so long to get that to the business side because the pace of change is change on the software side. You know, that's a strategic issue in terms of execution on the business side that they need now to change priorities. And, you know, there's no P R D S and M R. D s and big giant strategic plans that sit on the shelf for five years. That's just not the way business works anymore. Took a long time to get here. >>Yeah, it did. And, you know, there have been previous attempts to make a better connection between business and i t. There was the so called strategic alignment framework that a couple of friends of mine from Boston University developed, I think more than 20 years ago. But, you know, now we have better technology for creating that linkage. And the, you know, the idea of kind of ops oriented frameworks is pretty pervasive now. So I think it's, um you know, time for another serious attempt at it, >>right? And do you think doing it this way right with the bizarre coalition, you know, getting a collection of of kind of like minded individuals and companies together and actually even having a manifesto which were making this declarative statement of principles and values. You think that's what it takes to kind of drive this, you know, kind of beyond the experiment and actually, you know, get it done and really start to see some results in, in in production in the field. >>I think certainly no one vendor organization can pull this off single handedly. It does require a number of organizations collaborating and working together. So I think a coalition is a good idea, and a manifesto is just a good way to kind of lay out. What you see is the key principles of the idea, and that makes it much easier for everybody. Toe I understand and act on. >>Yeah, I I think it's just it's really interesting having, you know, having them written down on paper and having it just be so clearly articulated both in terms of the of the values as well as as the the principles and and the values, you know. Business outcomes, matter, trust and collaboration, data driven decisions, which is the number three or four and then learn, responded pivot. It doesn't seem like those should have to be spelled out so clearly. But obviously it helps to have them there. You can stick them on the wall and kind of remember what your priorities are. But you're the data guy. You're the analytics guy. Yeah, And a big piece of this is data analytics and moving to data driven decisions. And principle number seven says, you know, today's organizations generate more data than humans can process. And informed decisions can be augmented by machine learning and artificial intelligence right up your alley. You know, you've talked a number of times on kind of the many stages of analytics. Onda. How has that's evolved over over time? You know, it is You think of analytics and machine learning driving decisions beyond supporting decisions, but actually starting to make decisions in machine time. What's that? What's that think for you? What does that make you? You know, start to think Wow, this is This is gonna be pretty significant. >>Yeah, well, you know, this has been a long term interest of mine. Um, the last generation of a I I was very interested in expert systems. And then e think more than 10 years ago, I wrote an article about automated decision making using, um, what was available then, which is rule based approaches. But, you know, this address is an issue that we've always had with analytics and ai. Um, you know, we tended Thio refer to those things as providing decision support. The problem is that if the decision maker didn't want their support, didn't want to use them in order to make a decision, they didn't provide any value. And so the nice thing about automating decisions with now contemporary ai tools is that we can ensure that data and analytics get brought into the decision without any possible disconnection. Now, I think humans still have something to add here, and we often will need to examine how that decision is being made and maybe even have the ability to override it. But in general, I think, at least for, you know, repetitive tactical decisions, um, involving a lot of data. We want most of those I think, to be at least, um, recommended, if not totally made by analgesic rhythm or an AI based system, and that, I believe would add to the quality and the precision and the accuracy of decisions. And in most organizations, >>you know, I think I think you just answered my next question before I Before I asked it. You know, we had Dr Robert Gates on the former secretary of Defense on a few years back, and we were talking about machines and machines making decisions, and he said at that time, you know, the only weapon systems that actually had an automated trigger on it, We're on the North Korean South Korea border. Um, everything else that you said had to go through some person before the final decision was made. And my question is, you know what are kind of the attributes of the decision that enable us that more easily automated? And then how do you see that kind of morphing over time both as the the data to support that as well as our comfort level, Um, enables us to turn mawr mawr actual decisions over to the machine? >>Well, yeah, I suggested we need data, and the data that we have to kind of train our models has to be high quality and current, and we need to know the outcomes of the that data. You know, most machine learning models, at least in business, are supervised, and that means we need tohave labeled outcomes in the in the training data. But you know, the pandemic that we're living through is a good illustration of the fact that the data also have to be reflective of current reality. And, you know, one of the things that were finding out quite frequently these days is that the data that we have a do not reflect you know what it's like to do business in a pandemic. I wrote a little piece about this recently with Jeff Cam at Wake Forest University. We call it Data Science Quarantined and it we interviewed somebody who said, You know, it's amazing what eight weeks of zeros will do to your demand forecast. We just don't really know what happens in a pandemic. Our models may be have to be put on the shelf for a little while and until we can develop some new ones or we can get some other guidelines into making decisions. So I think that's one of the key things with automated decision making. We have toe make sure that the data from the past and you know that's all we have, of course, is a good guide toe. You know what's happening in the present and in the future, as far as we understand it. >>Yeah, I used to joke when we started this calendar year 2020 was finally the year that we know everything with the benefit of hindsight. But it turned out 2020 the year we found out we actually know nothing and everything >>we thought we d >>o. But I wanna I wanna follow up on that because, you know, it did suddenly change everything, right? We got this light switch moment. Everybody's working from home now. We're many, many months into it, and it's going to continue for a while. I saw your interview with Bernard Marr and you had a really interesting comment that now we have to deal with this change. We don't have a lot of data and you talked about hold, fold or double down, and And I can't think of, um or, you know, kind of appropriate metaphor for driving the value of the biz ops. When now your whole portfolio strategy, um, needs to really be questioned. And, you know, you have to be really well executing on what you are holding. What you're folding and what you're doubling down with this completely new environment? >>Well, yeah, And I hope I did this in the interview. I would like to say that I came up with that term, but it actually came from a friend of mine was a senior executive at gen. Packed, and I used it mostly to talk about AI and AI applications, but I think you could You could use it much more broadly to talk about your entire sort of portfolio. Digital projects you need to think about. Well, um, given some constraints on resource is and a difficulty economy for a while. Which of our projects do we wanna keep going on Pretty much the way we were for and which ones, um, are not that necessary anymore. You see a lot of that in a I because we had so many pilots. Somebody told me, You know, we've got more pilots around here than O'Hare Airport in a I, um and then the the ones that involve double down there, even mawr Important to you, they are. You know, a lot of organizations have found this out in the pandemic on digital projects. It's more and more important for customers to be ableto interact with you digitally. And so you certainly wouldn't want toe cancel those projects or put them on hold. So you double down on them, get them done faster and better. >>Another. Another thing I came up in my research that that you quoted um, was was from Jeff. Bezos is talking about the great bulk of what we do is quietly but meaning fleeing, improving core operations. You know, I think that is so core to this concept of not AI and machine learning and kind of the general sense, which which gets way too much buzz but really applied, applied to a specific problem. And that's where you start to see the value. And, you know, the biz ops manifesto is calling it out in this particular process. But I just love to get your perspective. As you know, you speak generally about this topic all the time, but how people should really be thinking about where the applications where I can apply this technology to get direct business value. >>Yeah, well, you know, even talking about automated decisions, um, the kind of once in a lifetime decisions, uh, the ones that a G laugh. Li, the former CEO of Proctor and Gamble, used to call the big swing decisions. You only get a few of those, he said. In your tenure as CEO, those air probably not going to be the ones that you're automating in part because you don't have much data about them. Your you know, only making them a few times and in part because they really require that big picture thinking and the ability to kind of anticipate the future that the best human decision makers have. Um, but in general, I think where they I The projects that are working well are you know what I call the low hanging fruit ones? The some people even report to refer to it as boring A. I so you know, sucking data out of a contract in order to compare it Thio bill of lading for what arrived at your supply chain. Companies can save or make a lot of money with that kind of comparison. It's not the most exciting thing, but a I, as you suggest, is really good at those narrow kinds of tasks. Um, it's not so good at the at the really big Moonshots like curing cancer or, you know, figuring out well, what's the best stock or bond under all circumstances or even autonomous vehicles. We made some great progress in that area, but everybody seems to agree that they're not gonna be perfect for quite a while. And we really don't wanna be driving around on, um in that very much, unless they're, you know, good and all kinds of weather and with all kinds of pedestrian traffic. And you know that sort of thing, right? >>That's funny. Bring up contract management. I had a buddy years ago. They had a startup around contract management, and I'm like and this was way before we had the compute power today and cloud proliferation. I said, You know how How could you possibly built off around contract management? It's language. It's legalese. It's very specific. He's like Jeff. We just need to know where's the contract and when does it expire? And who's the signatory? And he built a business on those you know, very simple little facts that weren't being covered because their contracts from people's drawers and files and homes and Lord only knows so it's really interesting as you said. These kind of low hanging fruit opportunities where you could extract a lot of business value without trying to, you know, boil the ocean. >>Yeah, I mean, if you're Amazon, Jeff Bezos thinks it's important toe have some kind of billion dollar projects, and he even says it's important to have a billion dollar failure or two every year. But I think most organizations probably are better off being a little less aggressive and, you know, sticking to what a I has been doing for a long time, which is, you know, making smarter decisions based on based on data. >>Right? So, Tom, I want to shift gears one more time before before you let Ugo on on kind of a new topic for you, not really new, but you know, not not the vast majority of your publications. And that's the new way toe work, you know, as as the pandemic hit in mid March, right? And we had this light switch moment. Everybody had to work from home, and it was, you know, kind of crisis and get everybody set up. Well, you know, now we're five months, six months, seven months. A number of companies have said that people are not gonna be going back to work for a while, and so we're going to continue on this for a while, and then even when it's not what it is now, it's not gonna be what it was before. So, you know, I wonder and I know you, you tease. You're working on a a new book, you know, some of your thoughts on, you know, kind of this new way, uh, toe work and and and the human factors in this new, this new kind of reality that we're kind of evolving into, I guess, >>Yeah, this was an interest of mine. I think. Back in the nineties, I wrote an article called a co authored an article called Two Cheers for the Virtual Office. And, you know, it was just starting to emerge than some people were very excited about it. Some people were skeptical, and we said to cheers rather than three cheers because clearly there's some shortcomings and, you know, I keep seeing these pop up. It's it's great that we can work from our homes. It's great that we can accomplish most of what we need to do with a digital interface, but you know, things like innovation and creativity and certainly, um a A good, um, happy social life kind of requires some face to face contact every now and then. And so you know, I think we'll go back to an environment where there is some of that. Um, will have, um, time when people convene in one place so they can get to know each other face to face and learn from each other that way. And most of the time, I think it's a huge waste of people's time to commute into the office every day and toe jump on airplanes. Thio, Thio, give every little sales call or give every little presentation we just have to really narrow down. What are the circumstances, where face to face contact really matters and when can we get by with digital? You know, I think one of the things in my current work on finding is that even when you have AI based decision making, you really need a good platform in which that all takes place. So in addition to these virtual platforms, we need to develop platforms that kind of structure the workflow for us and tell us what we should be doing next and make automated decisions when necessary. And I think that ultimately is a big part of biz ops as well. It's not just the intelligence of an AI system, but it's the flow of work that kind of keeps things moving smoothly throughout your organization. Yeah, >>I think such such a huge opportunity as you just said, because I forget the stats on how often were interrupted with notifications between email text, slack asana, salesforce The list goes on and on. So, you know, t put an AI layer between the person and all these systems that are begging for attention. And you've written a you know, a book on the attention economy, which is a whole nother topic will say for another day. You know, it really begs. It really begs for some assistance because, you know, you just can't get him picked, you know, every two minutes and really get quality work done. It's just not it's just not realistic. And you know what? I don't think that's the future that we're looking for. >>Great. Totally. Alright, >>Tom. Well, thank you so much for your time. Really enjoyed the conversation. I got to dig into the library. It's very long song. I might started the attention economy. I haven't read that one in to me. I think that's the fascinating thing in which we're living. So thank you for your time. And, uh, great to see you. >>My pleasure, Jeff. Great to be here. >>All right, take care. Alright. East, Tom. I'm Jeff. You are watching the continuing coverage of the biz ops manifesto. Unveil. Thanks for watching the Cube. We'll see you next time.

>>From Miami beach, Florida. It's the queue covering a cryonics global cyber summit 2019 brought to you by Acronis. >>Okay. Welcome back everyone. This is the cubes coverage here at the Chronis global cyber summit 2019 I'm John furrier, host to the cube. We're Miami beach at the Fontainebleau hotel with a second day. Excited to have this next guest on Christian Garcia, senior vice president of finance and administration at the chauffeur housing ShipIt housing Institute of technology. Did they get it right? Almost right. housing. welcome back. Welcome to the cube. Good to see you. Good to see you. Thanks for having me here. This is a really cool story because you guys are doing something very entrepreneurial, right, with education, right. Okay. Inspired by the founder of a Chronis. Exactly as well. He's got. He's made a lot of money in his day, so he's doing some good things with it. Um, but this is an interesting opportunity for you to take a minute to explain what this Institute stands for. >>It's sit for short. >> Yeah, so sat actually as a name Schaffhausen Institute of technology. So we are actually starting up a university in Schaffhausen in Schaffhausen. These a beautiful tiny CD in Switzerland, 30 minutes or 30 minutes from the Zurich airport, which is the biggest airport in Switzerland, uh, close to Germany at the border with Germany. And uh, so that's kind of your, in the center of Europe and that's where we plan to have our main campus. Now let me tell you this story. How about the vision about target, his vision on these, on this project? Um, he, he said that, you know, uh, he needs to have skills in 10 to 15 years time that nowadays at the institutions that do not do not, do not bring, um, there is the need of computer scientists that are not enough computer scientists and we are having emergent technologies and these is something that provides us with tremendous opportunities, which we cannot even imagine nowadays what type of opportunities and to be on the forefront there. >>That's why we want to found these are, we have founded the Schaffhausen Institute of technology. >> Chef housing is a technology just for share. The day was just two months ago, couple months ago. It was two months ago where we, where we have started up the legal structure and now we are really laying the foundation. We have to find some that are kind of secured for for the next 12 to 18 months. And um, we are, you know, defining the strategic advisory board. We are setting up the curriculum for our students. And so it's everything up and running and to be defined. So risk is right at the creation present at creation. We are talking about this as a, this is the origination story. Exactly. Of the shelf house in Institute of technology. Exactly. What's the vision? >>I mean obviously getting skills for jobs that are our century, our time that's having been teaching in universities and before I get back. But is it about being open and what's the vision is just Switzerland is going to be global. Can you just share, what do you guys are thinking? >>Sure, absolutely. So basically what we are trying to do is to design a curriculum in um, computer science and physics because we think that computer science or present the software in physics represents the hardware. And these two things need to be combined in a entrepreneurial mindset or with an entrepreneurial mindset, which means that we also want to foster the transformation process and the anti entrepreneurship. Now, let me go back to the software path. Uh, our curriculum will cover, um, software engineering, cybersecurity. That's why we are here today. Uh, the curriculum we also cover, um, on the physics part. On the hardware part, we'll cover, uh, quantum technologies, uh, quantum physics and also new materials. Um, and these will be kind of the foundation that will build the curriculum for students, computer scientists to have physics and physics to have computer science in their curriculum so that at some point in time they can come together and to research together. >>This is the digital transformation that we're talking about. The, the intersection and the confluence of physical reality. A world that we live in, whether it's a baseball game or a soccer match to the digital culture, they're not mutually exclusive anymore and they're together. And then the impact is profound. I can only imagine. IOT, industrial, IOT, airplanes, cars, electricity, electronic batteries, all these things, correct. It's software and digital. And physical material. Exactly that you guys are thinking. >>Exactly. Exactly that and actually also considering the industry, talking to the industry, talking to chief information technology officers around the world to understand what they need are and what type of they believe of skills are needed in in 10 to 15 years time. And that's what we want to build up now to get >>well you guys car gotta go, you gotta go faster because there's jobs now. There's thousands of jobs right now in cybersecurity. There's thousands and thousands of jobs for provision and cloud computing. Amazon educate. We talked to them all the time. They just can't get the word out fast enough that Hey, if you're unemployed there's no excuse for being unemployed. Write down there's so many new jobs. But because someone didn't go to the linear school and exactly know go step by step over the years and now you can level up very quickly. Exactly for certification. But you guys are taking a much more bigger idea around real kind of masters level. Is that what it is? Undergraduate masters level? What's the level of, actually we, we, we are starting >>out with this university and we have already students that are at our or with our partner universities currently in Singapore with NUS. And we then move to Karnak and Molly here in the U S um, in order to have it, we'll do a degree. So that's a unique opportunity to already start up with some presence, uh, in, in education. And uh, you ultimately, they will be then acquired. So we hope by, by, by, by the industry and the were terrific. Elon Musk is in there somewhere innovating with who knows what's next out there and he's around. And next Sergei is out there too. A exactly. Exactly. So just look at our, at our home page, look at the curriculum, which we are currently defining now. Eh, that would be, that would be great on sit.org take me through how it works. I know you're just starting, but as you guys look at the world, I mean, first of all, I can see, I can see the attractiveness of a dual degree. >>Yeah. Because most kids get bored in college. They're freelancing anyway. They're learning on their own. I get that. But I can S so I want, so as you guys start building it out, what's going on? What's going, how's it work? What are you guys doing? You're recruiting tickets through the, the factory of work that needs to get done, if you will. What's the workflows look like? What's happening right now? So currently, I mean, we are talking about the university because we, we have students and we will have students and we weren't to have the best talents, uh, globally available. And that's why we are building institution that attracts those talents. And these is kind of the first priority to have, do I have the talents to get the tens to get students come to, to, to sit? And obviously the second part is he said, well, talking to the CEOs and Tito was in to understand what are the needs in 10 to 15 years as an outcome of this digital transformation. >>I mean, the world is computerized. Uh, as you just mentioned before, there are not enough computer scientists currently available. So four out of five companies in Switzerland direction also globally are lacking. Uh, of computer scientists and they understand, you know, at what the digital transformation means. And that's something that we really try to understand as well to build it up the curriculum. What's the timeline of starting with students? Is you right away? Do you have a location? Is there a building, I mean, give us a timeline. When did classes start? When you start bringing people in? Is it happening now? I mean, absolutely. So, so actually currently we are, we are hunting at, at uh, at some campus locations, looking at some campus locations, each a thousand where our main campus will be, will be located. Um, at the, at the, at the same time we are really building buildings structure. >>So we are appointing the strategic advisory board will be, we twill direct, eh, the curriculum of the university. Um, and, and which is represented already by, uh, very, um, great scientists. One of them, the president of the strategic advisory board being professor Dr. Noble selloff, which is a Nobel prize winner. And which actually brings in that, that new ma new material, um, science in our physics curriculum. So that's another thing that we are currently trying to do to build up that governance appropriate components. And third element that we are looking at is also to attract uh, industries and companies that sponsor the students. And that's actually an attractive ecosystem that we are trying to build up to combine science education and also entrepreneurship in business. In order to foster that, which means that we are looking at the campus, we are setting up a research center and I'm talking about two or three years down the line, the research center and then also a tech park where we can commercialize the innovation that the science green Springs in. >>So all in all we really aim to have a closed ecosystem and self sustaining ecosystem. Hopefully that we are going to establish. It's a really big idea. Congratulations. It's bold. It's and it's relevant. Absolutely. So I got to ask you the question, how do you finance all this? Who's paying for it? So tell us how do we get funded? It's very important. Otherwise we pull in, start up with such a tremendous pace. Uh, actually the vision is, is from Sergei Velo self, uh, founder and CEO of Acronis. Um, he, he's, Hey has actually secured the initial founding of the institution and now really we need to have more partners on board in order to make this self sustaining education edge educational system system as sustainable as you are going to be tuition base or scholarship based. Have you guys thought about that? Um, in terms of students it would be tuition-based ah, that's a classical classical model or at least at least in Switzerland and obviously to get the industry sponsoring students in order to also down the line employee them later on. >>That would be the idea situation. Nice vision for Sergei and nice gesture. But you've got to look at what his business is doing. They created a category called cyber protection. Extending the benefit to him is more candidates know physics edge. So why not? This is a great vision. Absolutely the win-win. Absolutely. And we all believe in that the entire, um, you know, stand up team believe in that vision. That's where we are here and building up this institution. Well when you need to go global will be in Silicon Valley and waiting for you guys to come there and collaborate with us there. I hope. I hope that because we want to compliment each other. As I mentioned, computer scientists, our need is globally and obviously also in the Silicon Valley and why not? I think the collaboration aspect is going to be a big part of the growth as you guys get >>settled in on the the first use case in Shevon housing. Exactly. You know, and get that built out, but I think with digital technologies, I think there'll be a great collaboration, bring some good talent in as faculty and advisors and exactly get the flywheel going except congratulations. Thanks for coming on. The key, the education game is changing with modernization of a global impact of technology for good. You're seeing the landscape of innovation hit education. This is another great example of it. Super proud. The interview. Thanks for coming on and sharing the insights. The world continues to evolve. Of course, the cube is, they're watching every turn. I'm John Feria here in Miami beach for the Crohn's global cyber summit. 2019 deck with more coverage after this short break.

>> from Burlingame, California It's the Cube covering Suma logic Illuminate 2019. Brought to You by Sumer Logic. >> Hey, welcome back, everybody. Jeffrey here with the Cube worth, assume a logic illuminate 2019 of it. It's at the Hyatt Regency San Francisco airport. About 809 100 people are second year. It's a 30 year of the event, excited to be here and watch it grow. We've seen a bunch of these things grow from little to bigger over a number of years, and it's always funded kind of beer for the zenith. We're excited to do it by our next guest. She's an analyst. It's Nancy Goering, senior analyst for 4 51 research. Nancy, great to see you. >> Thank you for having me. >> Absolutely so first off, Just kind of impressions of the event here. >> Yeah, good stuff. You know, like he's definitely trying to, you know, get on top of some of the big trends. You know, The big news here was their new Cooper nineties monitoring, also obviously kind of staying on the the leading edge of the cloud. Native Technologies. >> It's it's amazing how fast it's growing, you know, doing some research for this. Then I found some of your stuff out on the Internet and just one quote. I think it's from years ago, but just for people to kind of understand the scale, I think, he said, Google was launching four billion containers a week. Twitter had 12,000. Service is uber 4000. Micro service is Yelp and Justin 25 million data points per minute. I think this is like a two or three year old presentation. I mean, the scale in which the data is moving is astronomical. >> Yeah, well, I mean, if you think of Google launching four billion containers every week, they're collecting a number of different data points about a container spinning up about the operation of that container while it's alive about the container spinning down. So it's not even just four billion pieces of data. It's, you know, multiply that by 10 20 or many more. So, yeah, So the volume of operations dated that people are faced with is just, you know, out of this world, and some of that is beginning to get abstracted away, terms of what you need to look at. So, you know, Kubernetes is an orchestration engine so that's helping move things around. You still need to collect that data to inform automation tools, right? So even if you was, even if humans aren't really looking at it, it's being used to drive automation, right? It still has to be collected, >> right, And they're still configurations and settings and and dials. And it seems like a lot of the breaches that we hear about today are people just miss configuring something on us. It's human error. And so how do we kind of square the circle? Because the date is only growing. The quantity sources, the complexity, Yeah, the lack of structure. And that's before we had a I ot And now we got edge devices and they're all reporting in from from home. Yeah, crazy problem. It's >> really, I think, driving a lot of the investments in the focus and more sophisticated analytics, right? So that's why you're hearing a lot more about machine learning. And a I in this space is because humans can't just look at that huge volume >> of data and >> figure out what it means. So the development of machine learning tools, for instance, is gonna pull out a piece of data that's important. Here is the anomaly. This is the thing you should be paying attention to. Andi, obviously getting increasingly sophisticated, right? In terms of correlating data from different parts of your infrastructure in order to yet make sense of it, >> right? And then, Oh, by the way, they're all made up of micro service is a literal interconnected in AP eyes. The third party providers. Yeah. I mean, the complexity is ridicu >> and then, you know, and I've been actually thinking and talking a lot recently about organizational issues within companies that exacerbate some of these challenges. So you mentioned Micro Service is so ah, lot of times, you know, you've got Dev ops groups and an individual Dev Ops group is responsible for a or multiple. Micro service is right. They're all running, sort of autonomous. They're doing their own thing, right? So they could move quickly. But is there anybody overseeing the application that's made up of maybe 1000 Micro Service's? And in some cases, the answer is no. And so it may look like all the Micro Service's are operating well, but the user experience actually is not good, and no one really notices until the user starts complaining. So it's like things start. You know, you have to think about organizational things. Who's responsible for that, right? You know, if you're on a Dev ops team and your job has been to support the certain service's and not the whole, like who's responsible for the whole application and that's it's a challenge, it's something. Actually, in our surveys, we're hearing from people that they're looking for people that skill set, someone who understands how to look at Micro Service's as they work together to deliver a service, right? It's it's a It's a pain point. Shouldn't >> the project the product manager for that application would hopefully have some instances abilities to kind of what they're trying to optimize for? >> In some cases, they're not technical enough, right? A product manager doesn't necessarily have the depth to know that, or they're not used to using the types of tools that the Dev Ops team or the operations team would use to track the performance of an application. So sometimes it's just a matter of having the right tooling in front of them, >> and then even the performance I was like What do you optimizing four you optimized for security up the mind thing for speed are optimizing for yeah, you can optimize for everything if you got a stack rank order at some point in time. So that would also then drive in a different prioritization or the way that you look at those doctorsservices performance. Yeah, interesting. It's another big topic that comes up often is the vision of a single pane of glass in You know, I can't help but think is in my work day. You know how often I'm tabbing between, you know, sales force and email and slack and asana and, um, a couple of browsers air open. I mean, it's it's it's bananas, you know, it's no longer just that that email is the only thing that's open on my desk all day and only imagine the Dev Ops world. No, we saw just crazy complexity around again, managing all the micro service's of the AP eyes. So what's kind of the story? What are you seeing in kind of the development of that? And there's so many vendors now, and so many service is yeah, it's not just we're just gonna put in HB open view, and that's the standard, and that's what we're all right on. >> So if you're looking at it from the lens of of monitoring or observe ability or performance. Traditionally, you had different tools that looked at, say, different layers of a service, so you had a tool that was looking at infrastructure. Was your infrastructure monitoring tool. You had an application performance monitoring tool. You might have a network performance monitoring tool. You might have point tools that are looking just at the data base layer. But as things get more complicated, Azadliq ations are getting much more complex. Looking at that data in a silo tool tends to obscure the bigger picture. You don't understand when you're looking at the's separate tools how some piece of infrastructure might be impacting the application, for instance. And so the idea is to bring all of that operations data about the performance of an application in tow. One spot where you can run again, these more sophisticated analytics so that you can understand the relationship between the different layers of the application stack also horizontally, right? So how micro service's that are dependent on each other? How one micro service might be impacting the performance of another. So that's conceptually the idea behind having a single pane of glass. Now the execution can happen in a bunch of different ways, so you can have one vendor. There are vendors that are growing horizontally, so they're collecting data across the stack. And there's other vendors that are positioning themselves as that sort of central data repositories, so they may not directly collect all of that data. But they might in just some data that another monitoring vendor has collected. So there's an end. You know, there's there's always going to be good arguments for best of breed tools, right? So, you know, in most cases, businesses are not going to settle on just one monitoring tool that does it all. But that's conceptually the reason, right, and you want to bring all of this data together. However you get it, however, it's being collected so that you can analyze it and understand that big picture performance of a complicated application, >> right? But then, even then, as you said, you don't even want, you're not really monitoring the application performance per se. You're just waiting for the you're waiting for some of those needles to fall out of the haystack because you just you just can't get that much stuff. And you know, it's where do you focus your priority? You know what's most critical? What needs attention now. And if without a machine to help kind of point you in the right direction, you're gonna have a hard time finding that needle. >> And there's a lot of different approaches that are beginning to develop. So one is this idea of SL owes or service level objectives. And so, for instance, a really common service level objective that teams are looking at is Leighton. See, So this Leighton see of the service should never drop under whatever ah 100 milliseconds. And and if it does, I want to be alerted. And also if it drops below that objective for a certain amount of time, that can actually help you as a team. Allocate, resource is so if you're not living up to that service level objective, maybe you should shift some people's time toe working on improving the application instead of developing a new feature, right? So it can really help you prioritize your time because you know what? There was a time when people in operations teams or Dev. Ops teams had a really hard time, and they still d'oh figuring out which problems are important because you've always people always have a lot of performance problems going on. So which do you focus your time on? And it's been pretty opaque. It's hard to see. Is this performance impacting the bottom line of my business? Is this impacting? You know, my customers? Are we losing business over this? Like that's That's a really common question that people I can't answer, right? So there you people are beginning to develop these approaches to try to figure out how to prioritize work on performance problems. It's >> interesting because the other one that and some of you mentioned before is kind of this post incident review instead of a post boredom. And, you know, you talked about culture and words matter, and I think that's a really interesting take because it's it's it implies we're gonna learn, and we're gonna go forward. It's dead. Um, yeah, you know, we're gonna yell at each other and someone's gonna get blamed. That's exactly it. And we're going to move on. So, you know, how is that kind of evolved in. And how does that really help organizations do a better job? >> There's, I mean, there's there's much more of a focus on setting aside time to do that kind of analysis, right? So look at how we're performing as a team. Look at how we responded to an incident so that you can find ways that you can do better next time and some of that Israel tactical right? It's tweaking alerts. Did we not get an alert? You know, did we not even know this problem was happening? So maybe you build new alerts or sport get rid of a bunch of alerts that did nothing. You know, there's there's a lot you can learn on again to To your point, I think part of the reason people have started calling in a post Incident review instead of a postmortem is because yet you don't want that to be a session where people are feeling like Blaine. You know, this is my fault. I screwed up. I spent way too long on this, so I >> had to >> set things out properly. It's it's meant to be productive. Let's find the weak points and fill them right. Fill those gaps. >> It's funny you had another. There's another thing I found where you were talking about not not necessarily the Post Borden, but you know, people, people being much more proactive, much more, you know, thoughtful as to how they are going to take care of these things. And it is really more of a social cultural change unnecessarily. The technical piece that culture pieces. So so >> it is and especially, you know, right now there's a lot of focus on on tooling and that can cause some, you know, interesting issues. So, you know, especially in an organization that has really adopted Dev ops practices like the idea of a Dev Ops team is that it's very autonomous. They do what they do, what they need to do right to move fast and to get the job done. And that often includes choosing your own tools, but that that has created a number of problems, especially in monitoring. So if you have 100 Dev ops teams and they all have chosen their own, monitoring tools like this is not efficient, so it's not. It's not a good idea because those tools aren't talking to each other, even though they're micro service's that are dependent on each other. It's inefficient. From a business perspective. You've got all these relationships with vendors, and in some cases, with a single vendor, you might have 50 instances of the same monitoring tool that you know you have 50 accounts with them, like that's just totally inefficient. And then you've got people on a Dev ops, an individual, all the all the individual Dev ops teams have a person who's supposed to be the resident expert in these tools, like maybe you should share that knowledge across. But my point is, you get into the situation where you have hundreds of monitoring tools, sometimes 40 50 monitoring tools. You realize that's a problem. How do you address that problem? Because you're gonna have to go out and tell people you can't use this tool that you love. That helps you do your job that you chose. And so again, this whole cultural question comes out like, How do you manage that transition in a way that's gonna be productive? >> Thea other one that you brought up that was interesting is where the the sport team basically tells the business team you only have X number of incidents. We're gonna give you a budget. Yeah, exceed the budget. We're not going to help you. It's a really different way to think about prioritization. I >> don't necessarily think that's a great approach, but I mean, there was somebody who did that, but I think it's kind of it's kind of >> an interesting thing. And you talked about it in that. I think it was one of your presentations or speeches where, you know, it makes you kind of rethink. You know, why do we have so many incidents? Yeah, and there shouldn't be that many incidents, and maybe some of the responsibility should be shifted to think about why in the how and is more of a systemic problem than a feature problem or a bug, right? It's a broken code. So again, I think there's so many kind of cultural opportunities to rethink this. In a world of continuous development, continuous publishing and continuous pushing out of new code. Yeah, yeah, sure. All right. Nancy will. Thanks for taking a few minutes, and it's really great to talk to you. Thanks >> for having me. >> Alright. She's Nancy. I'm Jeff. You're watching the Cube where it's Uma Logic illuminate 2019. Thanks for watching. We'll see next time

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

>> Narrator: From Burlingame, California, it's theCUBE. Covering Sumo Logic Illuminate 2019. Brought to you by Sumo Logic. >> Hey, welcome back, everybody, Jeff Frick here with theCUBE. We're at Sumo Logic Illuminate 2019. It's at the Hyatt Regency San Francisco Airport. We're excited to be back. It's our second year, so third year of the show, and really, one of the key tenants of this whole event is the report. It's the fourth year of the report. It's The Continuous Intelligence Report, and here to tell us all about it is the VP of Product Marketing, Kalyan Ramanathan. He's, like I said, VP, Product Management of Sumo Logic. Great to see you again. >> All right, thank you, Jeff. >> What a beautiful report. >> Absolutely, I love the cover and I love the data in the report even more. >> Yeah, but you cheat, you cheat. >> How come? >> 'Cause it's not a survey. You guys actually take real data. >> Ah, that's exactly right, exactly right. >> No, I love them, let's jump into it. No, it's a pretty interesting fact, though, and it came out in the keynote that this is not a survey. Tell us how you get the data. >> Yeah, I mean, so as you already know, Sumo Logic is a continuous intelligence platform. And what we do is to help our customers manage the operations and security of the mission critical application. And the way we do that is by collecting machine data from our customers, and many of our customers, we have two thousand, our customers, they're all running modern applications in the cloud, and when we collect this machine data, we can grade insights into how are these customers building their applications, how are these customers running and securing their application, and that insight is what is reflected in this report. And so, you're exactly right, this is not a survey. This is data from our customers that we bring into our system and then what we do is really treat things once we get this data into our system. First and foremost, we completely anonymize this data. So, we don't-- >> I was going to say Let's make sure we have to get that out. >> Yes, absolutely, so we don't have any customer references in this data. Two, we genericize this data. So, we're not looking for anomalies. We are looking for broad patterns, broad trends that we can apply across all of our customers and all of these enterprises that are running modern mission critical applications in the cloud. And then three, we analyze ten weeks to Sunday. We look at these datas, we look at what stands out in terms of good sample sizes, and that's what we reflect in this report. >> Okay, and just to close a loop on that, are there some applications that you don't include? 'Cause they're just legacy applications that're running on the cloud that doesn't give you good information, or you're basically taking them all in? >> Yeah, it's a good point, I mean we collect all data and we collect all applications, so we don't opt-in applications or out applications for that matter because we don't care about it. But what we do look for is significant sample size because we want to make sure that we're not talking about onesie-twosie applications here or there. We're looking for applications that have significant eruption in the cloud and that's what gets reflected in this report. >> Okay, well, let's jump into it. We don't have time to go through the whole thing here now, but people can get it online. They can download their own version and go through it at their leisure. Biggest change from last year as the fourth year of the report. >> Yeah, I mean, look, there are three big insights that we see in this report. The first one is, while we continue to see AWS rule in the cloud and that's not surprising at all, we're starting to see pretty dramatic adoption of multi-cloud technologies. So, two years ago, we saw a smidgen of multi-cloud in this report. Now, we have seen almost a 50% growth year over year in terms of multi-cloud adoption amongst enterprises who are in the cloud, and that's a substantial jump albeit from a smaller baseline. >> Do you have visibility if those are new applications or are those existing ones that are migrating to different platforms? Are they splitting? Do you have any kind of visibility into that? >> Yeah, I mean, it's an interesting point, and part of this is very related to the growth of Kubernetes that we also see in this report. What ypu've seen is that, in AWS itself, Kubernetes adoption has gone up significantly, what's even more interesting is that, as you think about multi-cloud adoption, we see a lot of Kubernetes, Kubernetes as the platform that is driving this multi-cloud adoption. There is a very interesting chart in this report on page nine. Obviously, I think you guys can see this if they want to download the report. If you're looking at AWS only, we see one in five customers are adopting Kubernetes. If you're looking at AWS and GCP, Google Cloud Platform, we see almost 60% of our customers are adopting Kubernetes. Now, when you put in AWS-- >> One in five at AWS, 60% we got Google, so that means four out of five at GCP are using Kubernetes and bring that average up. >> And then, if you look at AWS, Azure, and GCP, now you're talking about the creme de la creme customers who want to adopt all three clouds, it's almost 80% adoption of Kubernetes, so what it tells you is that Kubernetes has almost become this new Linux in the cloud world. If I want to deploy my application across multiple clouds, guess what, Kubernetes is that platform that enables me to deploy my application and then port it and re-target it to any other cloud or, for that matter, even an on-prem environment. >> Now, I mean, you don't see motivation behind action, but I'm just curious how much of it is now that I have Kubernetes. I can do multi-cloud or I've been wanting to do multi-cloud, and now that I have Kubernetes, I have an avenue. >> Yeah, it started another question. What's the chicken and what's the egg right here? My general sense, and we've debated this endlessly in our company, our general sense has been that the initiative to go multi-cloud typically comes top down in an organization. It's usually the CIO or the CSO who says, you know what, we need to go multi-cloud. And there are various reasons to go multi-cloud, some of which you heard in our keynote today. It could be for more reliability, it could be for more choice that you may want, it could be because you don't want to get logged into any one cloud render, so that decision usually comes top down. But then, now, the engineering teams, the ops teams have to support that decision, and what these engineering teams and these ops teams have realized is that, if they deploy Kubernetes, they have a very good option available now to port their applications very easily across these various cloud platforms. So, Kubernetes, in some sense, is supporting the top down decision to go multi-cloud which is something that is shown in spades as a result of this report. >> So, another thing that jumped out at me, or is there another top trend you want to make sure we cover before we get in some of those specifics? >> I mean we can talk to-- >> Yeah, one of them, one of them that jumped out at me was Docker. The Docker adoption. So, Docker was the hottest thing since sliced bread about four years ago, and is the shade of Kubernetes, not that they're replacements for one another specifically, but it definitely put a little bit of appall in the buzz that was the Docker, yet here, the Docker utilization, Docker use is growing year over year. 30%! >> I'll be the first one to tell you that Docker adoption has not stalled at all. This is shown in the report. It's shown in customers that we talk to. I mean, everyone is down the path of containerizing their application. The value of Docker is indisputable. That I get better agility, that I get better portability with Docker cannot be questioned. Now, what is indeed happening is that everyone who is deploying Docker today is choosing a orchestration technology and that orchestration technology happens to be Kubernetes. Again, Kubernetes is the king of the hill. If I'm deploying Docker, I'm deploying Kubernetes along with it. >> Okay, another one that jumped out at me, which shouldn't be a big surprise, but I'm a huge fan of Andy Jassy, we do all the AWS shows, and one of always the shining moments is he throws up the slide, he's got the Customer slide. >> There you go. >> It's the Services slide which is, in like, 2.6 font across a 100-foot screen that fills Las Vegas, and yet, your guys' findings is that it's really: the top ten applications are the vast majority of the AWS offerings that are being consumed. >> Yep, not just that. It's that the top services in AWS are the infrastructure-as-a-service services. These are the core services that you need if you have to build an application in AWS. You need ECDO, I need Esri, I need identity access management. Otherwise, I can't even log into AWS. So, this again goes back to that first point that I was making was that multi-cloud adoption is top of mind for many, many customers right now. It's something that many enterprises think of, and so, if I want to indeed be able to port my application from AWS to any other environment, guess what I should be doing? I shouldn't be adopting every AWS service out there because if I frankly adopted all these AWS services, the tentacles of the cloud render are just so that I will not be able to port away from my cloud render to any other cloud service out there. So, to a certain extent, many of the data points that we have in this report support the story that enterprises are becoming more conscious of the cloud platform choices that they are making. They want to at least keep an option of adopting the second or the third cloud out there, and they're consciously, therefore choosing the services that they are building their applications with. >> So, another hot topic, right? Computer 101 is databases. We're just up the road from Oracle. Oracle OpenWorld's next week. A lot of verbal jabs between Oracle and some of the cloud providers on the databases, et cetera. So, what do the database findings come back as? >> I mean, look at the top four databases: Redis, MySQL, Postgres, Mongo. You know what's common across them? They're all open-source. They're all open-source database, so if you're building your application, find standard components that you can then build your application on, whether it's a community that you can then take and move to any other cloud that you want to. That's takeaway number one. Takeaway number two, look at where Oracle is in this report. I think they're the eighth database in the cloud. I actually talked to a few customers of ours today. >> Now, are you sampling from Oracle's cloud? Is that a dataset? >> No, this is-- >> Yes, right, okay. So, I thought I want to make sure. >> And, if AWS is almost the universe of cloud today, we can debate at some bids, but it is close enough, I'd say, it tells you where Oracle is in this cloud universe, so our friends at Redwood City may talk about cloud day in and day out, but it's very clear that they're not making much of intent in the cloud at this point. >> And then, is this the first year the rollup of the type of database that NoSQL exceeded relational database? >> No, I mean, we've been doing this for the last two years, and it's very clear that NoSQL is ahead of SQL in the cloud, and I think the way we think about it is primarily because, when you are re-architecting your applications in the cloud, the cloud gives you a timeline, it gives you an opportunity to reconsider how you build out your data layer, and many of our customers are saying NoSQL is the way to go. The scalability demands, the reliability demands, so if my application was such that I now have the opportunity to rethink and redo my data layer, and frankly, NoSQL is winning the game. >> Right, it's winning big time. Another big one: serverless, Lambda. Actually, I'm kind of surprised it took so long to get to Lambda 'cause we've been going to smaller atomic units of compute, store, and networking for so, so long, but it sounds like, looks like we're starting to hit some critical mass here. >> Yeah, I mean, look, Lambda's ready for primetime. I mean we have seen that tipping point out here. Almost one in three customers of ours are using Lambda in production environments. And then, if you cast a wider net, go beyond production and even look at dev tests, what we see is that almost 60% of Sumo Logic's customers, and if you look at 2,000 customers, that's a pretty big sample size. Almost 60% of enterprises are using Lambda in some way, shape, or form. So, I think it's not surprising that Lambda is getting used quite well in the enterprise. The question really is: what are these people doing with Lambda? What's the intent behind the use of Lambda? And that's where I think we have to do some more research. My general sense, and I think it's shared widely within Sumo Logic, is that Lambda's still at the edges of the application. It's not at the core of the application. People are not building your mission critical application on Lambda yet because I think that that paradigm of thinking about event-driven application is still a little foreign to many organizations, so I think it'll take a few more years for an entire application to be built on Lambda. >> But you would think, if it's variable demand applications, whether that's a marketing promotion around the Super Bowl or running the books at the end of the month, I guess it's easy enough to just fire up the servers versus doing a pure Lambda at this point in time, but it seems like a natural fit. >> If you're doing the utility type application and you want to start it and you want to kill it and not use it after an event has come and gone, absolutely, Lambda's the way to go. The economics of Lambda. Lambda absolutely makes sense. Having said that, I mean, if you're to build a true mission critical application that you're going to be keeping on for a while to come, I'm not seeing a lot of that in Lambda yet, but it's definitely getting there. I mean we have lots of customers who are building some serious stuff on Lambda. >> Well, a lot of great information. It's nice to have the longitudinal aspect as you do this year over year, and again, we're glad you're cheating 'cause you're getting good data. >> (chuckles) >> (laughs) You're not asking people questions. >> Yeah, I mean, I'd like to finish out by saying this is a report that Sumo Logic builds every year, not because we want to sell Sumo Logic. It's because we want to give back to our community. We want our community to build great apps. We want them to understand how their peers are building some amazing mission critical apps in the cloud and so, please download this report, learn from how your peers are doing things, and that's our only intent and goal from this report. >> Great, well, thanks for sharing the information and a great catch-up, nice event. >> All right, thank you very much, Jeff. >> All right, he's Kalyan, I'm Jeff. You're watching theCUBE. We're at Sumo Logic Illuminate 2019. Thanks for watching, we'll see you next time. (upbeat electronic music)

>> Narrator: From Burlingame, California, it's theCUBE, covering Sumo Logic Illuminate 2019! Brought to you by Sumo Logic. >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're at the Sumo Logic Illuminate 2019 event. It's at the Hyatt Regency San Francisco Airport, about eight hundred, nine hundred people, our second year. It's the third year of the event. Excited to be here and watch it grow. We've seen a bunch of these things grow from little to big over a number of years and it's always fun to kind of be here for the zenith. We're excited to be joined by our next guest, she's an analyst. It's Nancy Gohring, Senior Analyst for 451 Research. Nancy, great to see you. >> Thank you, thanks for having me. >> Absolutely. So first off, just kind of impressions of the event here. >> Yeah, good stuff, you know? Definitely trying to, you know, get on top of some of the big trends, you know, the big news here was their new Kubernetes monitoring tool. So obviously kind of staying on the leading edge of the cloud-native technologies. >> It's amazing how fast it's growing, you know. Doing some research for this event, I found some of your stuff out on the internet, and just one quote, I think it's from years ago, but just for people to kind of understand the scale, I think you said Google was launching four billion containers a week, Twitter had twelve thousand services, Uber four thousand microservices, Yelp ingesting twenty-five million data points per minute, and I think this is a two or three year old presentation, I mean, the scale in which the data is moving is astronomical. >> Yeah, well if you think of Google launching four billion containers every week, they're collecting a number of different data points about a container spinning up, about the operation of that container while it's alive, about the container spinning down. So it's not even just four billion pieces of data, it's, you know, multiply that by ten or twenty or many more. So yeah, so the volume of operations data that people are faced with, is just, you know out of this world. And some of that is beginning to get abstracted away in terms of what you need to look at so you know Kubernetes is an orchestration engine so that's helping move thing around. You still need to collect that data to inform automation tools, right, so even humans aren't really looking at it, it's being used to drive automation. >> Right. >> It still has to be collected. >> Right. And there's still configurations and settings and dials and it seems like a lot of the breaches that we hear about today are just people misconfiguring something on AWS >> Yeah, it's human error. >> It's human error. And so how do we kind of square the circle cause the data's only growing the quantity, the sources, the complexity, the lack of structure and that's before we add IOT and now we have edge devices and they're all reporting in from home. >> Yeah >> Crazy problems. >> It's really, I think, driving a lot of the investments and the focus in more sophisticated analytics, right, so that's why you're hearing a lot more about machine learning and AI in this space. It's because humans can't just look at that huge volume of data and figure out what it means. So, the development of machine learning tools, for instance, is going to pull out a piece of data that's important. Like, here's the anomaly, this is the thing you should be paying attention to. And then obviously getting increasingly sophisticated, right, in terms of correlating data from different parts of your infrastructure in order to make sense of it. >> Right. And then, oh, by the way, they're all made up of microservices that are all interconnected and API is the third party providers >> Yeah. >> I mean the complexity is ridiculous. >> Yeah, and then, you know, and I've been actually thinking and talking a lot recently about organizational issues within companies that exacerbates some of these challenges. So you mentioned microservices. So, a lot of times, you know, you've got DevOps groups and an individual DevOps group is responsible for a, or multiple, microservices, right. They're all running sort of autonomous. They're doing their own thing, right, so that they can move quickly. But is there anybody overseeing the application that's made up of maybe a thousand microservices? And in some cases the answer is "no". And so it may look like all the microservices are operating well, but the user experience actually is not good. And no one really notices until the user starts complaining. So, it's like things start, you know you have to think about organizational things. Who's responsible for that, right? If you're on a DevOps team and your job as been to support these certain services and not the whole, like, who's responsible for the whole application? >> Right. >> And that's, it's a challenge. It's something, actually, in our surveys, we're hearing from people that they're looking for people, that skill set, someone who understands how to look at microservices as they work together to deliver a service, right, it's a pain point. >> Shouldn't the project, or the product manager for that application would hopefully have some visibilities to kind of what they're trying to optimize for. >> In some cases they're not technical enough, right, a product manager doesn't necessarily have the depth to know that. Or they're not used to using tools that the DevOps team or the operations team would use to track the performance of an application. >> Right. >> So sometimes it's just a matter of having the right tooling in front of them >> And then even the performance. It's like, what are you optimizing for? Are you optimizing for security? Are you optimizing for speed? Are you optimizing for... >> Experience... >> You can't optimize for everything. You've got to stack rank order at some point in time, so that would also then drive in a different prioritization or the way that you look at those microservices' performance. >> Yeah, yeah. >> Interesting. So another big topic that comes up often is the vision of a single pane of glass. And, you know, I can't help but think as in my work day how often I'm tabbing between you know, sales force, and email, and slack, and Asana, and a couple of browsers are open. I mean, it's bananas, you know. It's no longer just that email is the only thing that's open on my desk all day. >> Yeah. >> And then you can only imagine the DevOps world that we saw just crazy complexity around, again, managing all the microservices, the APIs, so what kinds of, sort of, what are you seeing in kind of the development of that? And there's so many vendors now, and so many services. >> Yeah. >> It's not just, we're just going to put in HP open view and that's the standard and that's what we're all on. >> So if you're looking at it from the lens of monitoring or observability or performance, traditionally you had different tools that looked at, say, different layers of a service. So you had a tool that was looking at infrastructure - it was your infrastructure monitoring tool. You had an application performance monitoring tool. You might have a network performance monitoring tool. You might have point tools that are looking just at the data base layer. But as things get more complicated, as applications are getting much more complex, looking at that data in a silo tool tends to obscure the bigger picture. You don't understand when you're looking at the separate tools how some piece of infrastructure might be impacting the application, for instance. And so, the idea is to bring all of that operations data about the performance of an application into one spot where you can run, again, these more sophisticated analytics so that you can understand the relationship between the different layers of the application stack, also horizontally, right, so, how microservices that are dependent on eachother how one microservice might be impacting the performance of another, so that's conceptually the idea behind having a single pane of glass. Now the execution can happen in a bunch of different ways. So you can have one vendor, there are vendors that are growing horizontally, so they're collecting data across the stack. There's other vendors that are positioning themselves as that sort of central data repository. So they may not directly collect all of that data, but they might ingest some data that another monitoring vendor has collected. So, there's, and, you know, there's always going to be good arguments for best of breed tools right, so, you know, in most cases, businesses are not going to settle on just one monitoring tool that does it all. But that's conceptually the reason, right, is you want to bring all of this data together however you get it, however it's being collected, so that you can analyze it and understand that "big picture" performance of a complicated application. >> Right. But then, even then, as you said, you don't even want to, you're not really monitoring the application performance per se, you're just waiting for the, you're waiting for some of those needles to fall out of the haystack, cause you just, you just can. There's so much stuff. And you know, it's where do you focus your priority. You know, what's most critical, what needs attention now. >> (Nancy) Yeah. >> And if, without a machine to help kind of, point you in the right direction, you're going to have a hard time finding that needle. >> Yeah, and there's a lot of different approaches that are beginning to develop. And one is this idea of SLO's, or Service Level Objectives. And so, for instance a really common Service Level Objective that teams are looking at is latency. So, the latency of the service should never drop under whatever- a hundred milliseconds, and if it does, I want to be alerted. And also, if it drops below that objective for a certain amount of time that can actually help you as a team allocate resources. So, if you're not living up to that Service Level Objective, maybe you should shift some people's time to working on improving the application instead of developing a new feature. Right? >> (Jeff) Right. >> So it can really help you prioritize your time because you know what? There was a time, people in operations teams, or DevOps teams, had a really hard time, and they still do, figuring out which problems are important. 'Cause you've always, people always have a lot of performance problems going on. So which do you focus your time on? And it's been pretty opaque. It's hard to see, is this performance impacting the bottom line in my business? Is this impacting, you know, my customers? Are we losing business over this? Like, that's, that's a really common question that people can't answer. >> Right. >> So, yeah, people are beginning to develop these approaches to try to figure out how to prioritize work on performance problems. >> It's interesting 'cause the other one that you've mentioned before, kind of this post incident review instead of a post mortem and you know, you talked about culture, and "words matter" >> (Nancy) Yeah. >> And I think that's a really interesting take because it's, it implies, we're going to learn, and we're going to go forward as opposed to "it's dead". >> (Linda) Yeah. >> And, you know, we're going to yell at eachother, and someone's going to get blamed... >> (Linda) That's exactly it... >> And we're going to move on. So, you know, how has that kind of evolved and how does that really help organizations do a better job? >> There's, I mean, there's much more of a focus on setting aside time to do that kind of analysis, right? So look at how we're performing as a team. Look at how we responded to an incident so that you can find ways that you can do better next time. And some of that is real tactical, right, it's tweaking alerts. Did we not get an alert? You know, did we not even know this problem was happening? So maybe you build new alerts or get rid of a bunch of alerts that did nothing. You know, there's a lot you can learn and again, to your point, I think part of the reason people have started calling it a post incident review instead of a post mortem is because, yeah, you don't want that to be as session where people are feeling like blame, you know, this is my fault, I screwed up, I spent way too long on this, or I hadn't set things up properly. It's meant to be productive. >> Right. >> Let's find the weak points and fill them. Right? Fill those gaps. >> It's funny you had another, there was another thing I found, you were talking about not, not necessarily the post mortem but, you know, people being much more pro-active, much more, you know, thoughtful as to how they are going to take care of these things. And it is really more of a social, cultural change than necessarily the technical piece. That culture piece is so, so important. >> It is, and especially, you know, right now there's a lot of focus on tooling and that can cause some, you know, interesting issues. So you know, especially in an organization that has really adopted DevOps practices like, the idea of a DevOps team is that it's very autonomous. They do what they need to do, right, to move fast and to get the job done and that often includes choosing your own tools. But that has created a number of problems especially in monitoring. So if you have a hundred DevOps teams and they all have chosen their own monitoring tools, like, this is not efficient. So it's not a good idea because those tools aren't talking to each other, even though they're microservices that are dependent on each other. It's inefficient from a business perspective. You've got all these relationships with vendors and in some cases with a single vendor. You might have fifty instances of the same monitoring tool that, you know, you have fifty accounts with them. Like that's just totally inefficient. And then you've got people on a DevOps and individual, all the individual DevOps teams have a person who's supposed to be the resident expert in these tools, like, maybe you should share that knowledge across... But my point is you get into this situation where you have hundreds of monitoring tools. Sometimes forty, fifty monitoring tools. You realize that's a problem. How do you address that problem? 'Cause you're going to have to go out and tell people you can't use this tool that you love, that helps you do your job, that you chose. So again this whole cultural question comes up. Like, how do you manage that transition in a way that's going to be productive? >> The other one that you brought up that was interesting was where the support team basically tells the business team you only have X-number of incidents, we're going to give you a budget. (laughs) >> Yeah. >> If you exceed the budget we're not going to help you. It's a really different way to think about prioritization... >> Yeah, I don't necessarily think that's a great approach. I mean there was somebody who did that but like... >> But I think its kind of, it's kind of an interesting thing. And you talked about it in that I think it was one of your presentations or speeches where, you know, it makes you kind of re-think, you know, why do we have so many incidents? >> Yeah. >> And there shouldn't be that many incidents. And maybe some of the responsibility should be shifted to think about why, and the how, and is it more of a systemic problem than a feature problem, or a bug, or... >> Right >> A piece of broken code, so again I think there's so many, kind of, cultural opportunities to re-think this, in this world of continuous development, continuous publishing, continuous pushing out of new code. >> Yeah, yeah. For sure. (laughs) >> Alright Nancy, well thanks for taking a few minutes and it was really great to talk to you. >> Thanks for having me. >> Alright, she's Nancy, I'm Jeff. You're watching theCUBE, where it's Sumo Logic Illuminate 2019. Thanks for watching We'll see you next time (electonic music)

>> from Burlingame, California It's the Cube covering Suma logic Illuminate 2019. Brought to You by Sumer Logic >> Hey, welcome back, everybody. Jeffrey here with the Cube were at the higher Regency San Francisco Airport at Suma Logic, Illuminate, 2019 were here last year for our first time. It's a 30 year the show. It's probably 809 100 people around. 1000 packed house just had the finish. The keynote. And we're really excited to have our first guest of the day. Who's been here since the very beginning is Bruno Critic, the founding VP of product and strategy for Suma Logic, you know, great to see you. Likewise. Thank you. So I did a little homework and you're actually on the cube aws reinvent, I think 2013. Wow. How far has the cloud journey progressed? Since efforts? I think it was our first year at reinvented as well. >> That's the second year agreement, >> right? So what? What an adventure. You guys made a good bet six years ago. Seems to be paying off pretty well. >> It really has been re kind of slipped out that the cloud is gonna be a real thing. Put all of our bats into it and have been executing ever since. And I think we were right. They think it is no longer a question. Is this cloud thing gonna be re alarm enterprise gonna adopt it? It's just how quickly and how much. >> Right? Right. But we've seen kind of this continual evolution, right? Was this jump into public cloud? Everybody jumped in with both feet, and now they're pulling back a little bit. But now really seen this growth of the hybrid cloud Big announcement here with Antos and Google Cloud Platform and in containers. And, you know, the rise of doctor and the rise of kubernetes. So I don't know, a CZ. You look a kind of the evolution. A lot of positive things kind of being added to the ecosystem that have helped you guys in your core mission. >> That's right. Look, you know, five years ago, which is such a short time, But yet instead of the speed of the technology adoption and change, you know it's in It's in millennia. What's happened over the last few years is technology stocks have changed dramatically. We've gone from okay, we can host some v ems in the cloud and put some databases in the cloud. So we're now building micro service's architecture, leveraging new technologies like Kubernetes like Serverless Technologies and all the stuff And, you know, some one of the fastest growing technologies that's being adopted by some village custom base, actually the fastest kubernetes and also the fastest customer segment growing customer segments. ImmuLogic is multi clog customers, basically that sort of desire by enterprise to build choice into their offerings. Being able to have leverage over the providers is really coming to fruition right now, >> right? But the multi cloud almost it makes a lot of sense, right, because we're over and over. You want to put your workload in the environment that supposed appropriate for the workload. It kind of. It kind of flipped the bid. It was no longer. Here's your infrastructure. What kind of APs can you build on it? Now here's my app. Where should it run that maybe on Prem it may be in a public cloud. It may be in a data center, so it's kind of logical that we've come into this this hybrid cloud world that said, Now you've got a whole another layer of complexity that that's been added on. And that's really been a big part of the rise of kubernetes. >> That's right. And so, as you're adopting service's that are not equal, right, you have to create a layer that insulate you from those. Service is if you look a tw r continues intelligence report that we just announced today. You will also see that how customers and enterprise are adopting cloud service is is they're essentially adopting the basic and core compute storage network, and database service is there's a long, long tail of service that are very infrequently adopted. And that is because enterprise they're looking for a way to not get to lock Tintin into anyone. Service provider kubernetes Give them Give them that layer of insulation with in thoughts and other technologies like that, you are now able to seamlessly manage all those workloads rather there on your on premise in AWS in G C. P. In azure or anywhere else, >> right? So there's so much we can unpack. You're one of the things I want to touch on which you talked about six years ago, but it's even more thing appropriate. Today is kind of this scale this exponential growth of data on this exponential scale of complexity. And we, as people, has been written about by a lot of smart people, and I, we have a real hard time. Is humans with exponential growth. Everything's linear. Tow us. So as you look at this exponential growth and now we're trying to get insights. Now we've got a I ot and this machine a machine data, which is a whole another multiple orders of magnitude. You can't work in that world with a single painted glass with somebody looking at a dashboard that's trying to find a yellow light that's earned it. I'm going to go read. You don't have analytics. Your hose. >> That's right. This is no longer world of Ding dong lights, right? You can just like to say, Okay, red, green, yellow. The as sort of companies go digital right? Which is driving this growth in data, you know? Ultimately, that data is governed by Moore's law. Moore's law says machines are gonna be able to do twice as much every 18 to 24 months. Well, that guess what? They're gonna tell you what they're doing twice as much. Every 18 to 24 months, and that is an exponential growth rate, right? The challenge that is, budgets don't grow at that rate, either, right? So budgets are not exponentially growing. So how do you cope with the onslaught of this data? And if you're running a digital service, right, if you're serving your customers digital generating revenue through digital means, which is just about every industry. At this point in time, you must get that data because if you don't get the data, you can't run your business. This data is useful not just in operations and security. It's useful for general business abuse, useful in marketing and product management in sales and their complexity. And the analytics required to actually make sense of that data and serve it to the right constituency in the business is really hard. And that has been whatever we have been trying to solve, including this economics of machine. Dad and me talked about it today. Keynote. We're trying t bend the cost curve >> Moore's law >> yet delivered analytics that the enterprise can leverage to really not just operate an application but run their business >> right. So let's talk about this concept of observe ability. You've written box about it. When you talk to people about observe ability, what should they be thinking about? How are you defining it? Why is it important? >> It's great question, So observe ability right now is being defined as a technique right. The simplest way to think about it is people think, observe a witty I need to have these three data sets and I have observed ability. And then you have to ask yourself a question. First of all, what is Observe ability and why does it matter? I think there's a a big misconception in the market how people adopt this is that they think, observe abilities the end. But it isn't observe. Ability is the means of achieving a goal. And what we like to talk about is what is the goal? Observe, observe ability right now. Observe abilities talked about strictly in the devil up space, right? Basically, how am I going to get obs Erv City into an application? And it's maybe runtime how it's running, whether it's up and performance. The challenge with that is that is a pigeon pigeon hole view off, observe ability, observe ability. If you think about it, we talk about objectives during observe ability. Operability tau sa two ns Sorry could be up time in performance. Well, guess what a different group like security observe. Ability is not getting breached. Understanding your compliance posture. Making sure that you are compliant with with regular to re rules and things like that observe ability to a business person to a product manager who's who owns a P N. L. On some product is how are my users using this product powers my application being adopted where users having trouble. What are they and where's the user experience? Poor right? So all of this data is multifaceted and multi useful as multi uses and observing Tow us. Is his objectives driven? If you don't know what your object it is, observe. Ability is just a tool. >> I love that, you know, because it falls under this thing We talked about off the two, which is, you know, there's data, right, and then there's information in the data and then, but it is a useful information because it has to be applied to something that's right in and of itself. It has no value, and what you're talking about really is getting the right data to the right person at the right time, which kind of stumbled into another area, which is how do you drive innovation in an organization? In one of the simple concepts is democratization. Get more people more than data more than tools to manipulate the data. Then piano manager is gonna make a different decision based on different visibility than Security Person or the Dev Ops person. So how is how is that evolving? Where do you see it going? Where was it in the past? And you know, I think he made it interesting or remain made. Interesting thing in the keynote where you guys let your software be available to everyone. And there was a lot of people talking about giving Maur. People Maur access to the tools and more of the data so that they can start to drive this innovation >> abuse of an example of one of the one of the sort of aspects of when we talk about continued continues intelligence. What do we mean? So this concept of agile development didn't evolve because people somehow thought, Hey, why don't we just try to push court production all the time? Break stuff all the time. What's the What's the reason why that came about? It did not come about because somehow somebody decided so better. Software development model It's because cos try to innovate faster, so they they wanted Toa accelerate. How they deliver digital product and service is to their customers. And what's facilitates that delivery cycle is the feedback loop. They get out of their data. They push code early. They observed the data. They understand what it's telling them about how their customers are using their products, and service is what products are working with or not. And they're quickly baking that feedback back into their development cycles into the business business cycles. To make better Prada effectively, it evolved as a as a tool to differentiate and out innovate the competition. And that's to a large degree one of the ways that you deliver the right inside to the right group to improve your business right. And so this is applicable across all use cases in order pot. All departments are on the company, but that's just one example of how you think of this continuous innovation, continuous data from to use analytics and don't >> spend two years doing an M r d and another two years doing a P R d and then another to your shift >> When you when you actually ship it. Half of the assumptions that you made two years ago already all the main along, right? So now you've gotta go. You've wasted half of your development time, and you've only released half of the value that you could have other, >> right? Right. And your assumptions are not gonna be correct, right? You just don't know until you get that >> you think over time, like two years of kubernetes with a single digits percentage adoption technology and soon was customer base. Now it's 1/3 right? Right? Which means no things have changed. If I had made an assumption as of two years ago on communities, I would have no way wouldn't have done this announcement, >> right? Right. >> But we did it in an interactive mode and re benefit from that continuous information continues intelligence that we do in our own >> right, right? We fed Joe and the boys on lots of times so that it's a pretty interesting how fast that came and how it really kind of over took. Doctor has informed they contain it. Even the doctor, according to reporters. Still getting a Tana Tana traction >> and it's >> working in conjunction with communities. Communities allows you to manage those containers right, And Dr Containers are always part of the ecosystem. And so it's, you know, you know, it's like the management layer and the actual container layer, >> right? So as you look forward to give you the last word, you know, as we're really kind of getting into the SIA Teague World and five G's coming just around around the corner, which is gonna have a giant impact on an industrial I ity and this machine a machine communications, what are some of your priorities? What are you looking, you know, kind of a little bit down the road and keeping an eye on >> interesting question. You know, we used to think about I ot as is the new domain. We should think about I or tea. And maybe we need to build a solution for right. It turns out our biggest customers, customers and the way that I have personally reframed my thinking about Iris is the following Computational capacity is ubiquitous. Now, what used to be a modern application 345 years ago was something that your access to your laptop or three or mobile app, and maybe you're a smart watch Now the computation that you interface with runs in your doorbell, you know, in a light switch in your light bulbs and how's it runs everywhere runs in your shoe because when you're around, it talks to your phone to tell you how many steps you've taken, all the stuff right? Essentially, enterprises building application to serve their customers are simply pushing computation farther and farther into our being, like everywhere. There's now I, P Networks, CP use memory and all of those distributed computers are now running the applications that are serving us in our lives, right? And to me, that's what I ot is. It's just an extension off what the digital service is our and we interface with does, and it so happens that when you push computation farther and farther into our lives, you get more and more computers participating. You get more data, and many of our largest customers are essentially ingesting their full stack of iron devices to serve their customers >> right crazy future and you know, it just kind of this continual Adam ization to of computer store and memory. Well, Bruno, hopefully it will not be six years before we see you again. Congrats on the conference. And thanks for taking a few minutes. Absolutely. All right. He's Bruno. I'm Jeff. You're watching the Cube where? It's suma logic illuminate at the Hyatt Regency seven square port. Thanks for watching. We'll see you next time.

>> from Burlingame, California It's the Cube covering Suma logic illuminate 2019. Brought to you by Sumer Logic >> Hey, welcome back there. Ready Geoffrey here with the Cube where it's suma logic illuminate 2019. We're here >> at the Hyatt Regency San Francisco Airport is about 809 100 people packed house in the keynote earlier this afternoon. Really excited tohave. The guy that was >> running the whole show was running the whole show here for this company. He's remain Sayer, >> the president and CEO of To Malachi Remain great to see you again. You too. Thanks. Absolutely. So 30 year. The show Second year of us being here. Wonder if you could just kind of reflect on how this thing is growing. >> Yeah. I mean, I think it's really a testament to the community more so than sumo, and we've seen a lot of growth naturally, because of where customers are with their own adoption of technologies such as cloud, but also transformations that they're going through like digital transformation, cloud transformation so naturally that allows for more audience of people to attend conference like this. Because this is not a sales marketing conference. This is a user conference. And as evidenced by the fact that 60 plus percent of the content is users themselves in the community present. >> Right? And you talked about the theme is really this intelligence gap, which, which was really a key piece of the key note. And it's interesting because talking about data in huge amounts of data flow, exponential growth and types of data, flow of data, sources of data and your data is just data until it turns into information. And then if it turns into good information, that actually could maybe turn into some intelligence and some action that you can do something with. But there's no person that has the ability to manage the data flows now that we're starting to see. So you guys are really coming at that at the core? You've been at it for a long time. You made some great early on bets being cloud native and now really starting to see the benefits as this exponential growth of data just hits everybody >> you're spot on, I think, um, you know, maybe to add to that, I think the challenge that we see despite the tsunami of data growth, is that a lot of organizations still struggle because the lacked ability to be able to share the insights and intelligence they glean from this data. So a lot of things we spoke about the key note today was the whole notion of the intelligence gap that exists. And that's predicated on the fact that you know, we're all going through some sort of transformation or migration or business model change. And with that comes five challenges that we talked about with respect to continues intelligence we internally has actually referred to as a challenge of minding the gap of intelligence trap because we need to help our customers become intelligent and collaborate, communicate much more effectively by virtue of what we've become that what we've become is that trusted partner, that data steward that is sitting on all this valuable insights that we need to be able provide continuously to our community of users. >> Right, if you talked about it really out along three different metrics, right, the operations metrics, which is probably what people think of top of mine security metric on then, as well as the business metric. And, you know, we had a Robert Parker on earlier from smart thing Samsung Smart Things, and he made an interesting comment that they are pervasive users of Suma logic within the company, which I thought was really interesting because everyone's chasing innovation. How do you get innovative? I think one of the core ways, as you give more people more access to more data and the tools to actually do something with it. That seems to be a big piece of the of the smart thing story. And that's really a big part of your guys. Messaging. >> Yeah, I mean, I think unlike other vendors who have restrictions on adoption and usage on or charging by user model, you know, we're trying to make sure we tear those silos down on one of the nature's by nature. One of things you have to do is provide ubiquitous access, and second thing you have to do is built to dress all different types of data so you can get value for all those users and ubiquitous access. And so you hear about that through not just smart things, but a lot of other customers and partners that are here today because that's unlike the old models, >> right? Right. It's interesting, right? Minds, we backed you know, 97 97 98 99 when first started seeing people build Web applications. And they had all these pricing models based on, you know, cores and CP use because it was based on how many employees were inside the inside the walls and would have access to the applications. And they try to apply this to to a public Web page. It doesn't work. Still see some of that nasty legacy stuff, though, >> right? And would now it was 20 years later. So you made >> a big announcement today about really changing your pricing model. Two more fit the realities of the world in which we live. >> Yeah, look on the surface. Why it seems revolutionary. It's not. It's evolutionary for sumo. It's something we've been doing since we first started. For example, we always provided a service that charges an average for the month, not for the penalty. You're going over a day we didn't charge for user's because that's antiquated model. More importantly, we actually provide in an economic model all along the mere the business model of all these companies. So the more you ingest and use the lower your cost become not more right. And so the things we announced today is a further commitment that we have been making to the community and effectively taken the headache away from them because he looked at these other tools, for example, that provide observe ability for monitoring or for security. You have to go calculate, count the licenses. You have to go look at the number data point for a minute. You have to look at the number nodes and who wants to manage software you want to manage Service's. And so what we've done has really taken the next license taken existing licensing mall that we have to the next level and providing a credit based system so that you can flex and choose what you want to use in a given day and give a month and given Pierre recycle across a new suite of packing ages or a suite of products that we brought to market >> right or whatever, whatever you are optimizing for that particular day. That particular moment, that particular business >> but also ties or something you mentioned earlier it it actually helps tear down those silos that other vendors air creating because it provides ubiquitous access to all users for all different types of data, right? And instead of trying to keep those silos and separation that exists, that further challenges intelligence gap that we're seeing in intelligence. Economy, >> right, Right. What? Another great slide. I thought earlier in the keynote was given by Anheuser Busch, and he talked about his security infrastructure and all different layers of security in the solution that he has for, you know, front kind of front door and fishing, etcetera, etcetera. But the great thing is, you basically crossed all those applications stack and and it's a pretty interesting position for you guys to be in to be able to integrate with all these other kind of point solutions that make up parts of the puzzle and to bring it all back and to still have kind of this one ubiquitous Data Analytics platform to go on and do stuff with that. >> Yeah, I mean, I think it's truth be told, something we've been doing for a long time. I think the visual that you saw there is the challenged a lot of our customers have, and specifically they have these silos >> of >> endpoint or firewall or email or whatever else, and it could only make sense of it by leveraging the monitoring of those silos to an intelligence platform like sumo. And so the same thing that you saw in security with Anheuser Busch being able to leverage the silos into intelligence platform for security. We see in the monitoring space for developers and operations team so they'll have silo tools. But observe ability, is not it. You need continuous reliability, and therefore you need to be able to take all those different types of dead and signals, just like you saw on security for the different types of infrastructure and applications that your manager aging and provide an intelligence based system and service, not a monitoring based on the system of service. >> Right? Another big trend that's happening. You guys were riding this wave and you're Jennifer up from from Google Cloud and she she had the same presentation on Antos. I think at the Google Cloud platform, someone earlier today, you know the Mo Mentum behind Hybrid Cloud as kind of the whipsaw. You know, it's all jump into public and then let's not jump in and its hybrid and its multi. The fact of the matter is, everything's going to work supposed to be, which is its workloads Pacific and the works load should run where the workload should run Really a great moment, um, for you guys to be ableto leverage because regardless of where the work flows running based on where it should run, I need to see it in a unified front. Back at the back of the ranch. >> Have a Jeff. I think this is what we saw even last year when we put the continuous intelligence report out, then let alone the changes we saw this year. For example, we saw Container Technologies moved from development to production last year in north of two ex growth. Now we're seeing orchestration technologies like Kubernetes more than two Ex Growth. And what's driving the multi cloud common that you made is because the customers want flexibility and choice of where those work clothes run. Historically, they have been able to do that until now. Leveraging contain orchestration, technology that builds an abstraction layer from the eye. Astor infrastructure is a service later, and obviously a testament to what Google's been doing with an throws in the partnership we have with them. Tow develop and integrate things for anthros. Ston service mesh. >> Yeah. So what's next? What do you looking for? I can't believe we're almost done with 2019. It still shocks me every time I flipped a calendar. >> What? Your priorities going forward? >> Another great event. 2020 year of insight and all knowledge. What we're saying we're gonna be, >> uh >> you >> know, we started down this journey before the market was there, and I think the unique position and fortunate position that we're in right now is Maura, Maura, that market opportunities to us and the community's getting more powerful and stronger day by day and year by year. So we're very early innings of this honestly. And so what do we see? Going forward to your question is a lot of the execution of our strategy that we set out a while ago to build the only continuous intelligence platform. And more importantly, the new category of software called into continues intelligence. That's really mirroring the OMB operating model and economic model of every single digital business that needs to thrive, not just survive >> right in an era of exponential growth data, complexity, sources, types, which is ah, good place to be all right. Well, we're mean. I know you're super busy. Thanks for taking a few minutes. And congratulations on a great show for sure. All right, >> ease remain. I'm Jeff. You're watching the Q word. Suma logic illuminate 2019. >> Thanks for watching. We'll see you next time.

>> Narrator: From Burlingame, California, it's the Cube, covering Sumo Logic Illuminate 2019. Brought to you by Sumo Logic. >> Hey welcome back everybody! Jeff Frick here with the Cube, we're at the Sumo Logic Illuminate conference, it's at the Hyatt San Francisco Airport. About 700, 800 people, full house in the keynote earlier today, all about operational process monitoring, all this crazy data is being kicked out of the Cloud and IoT and all these crazy next-gen applications. We're excited to have a very close friend of mine, CEO of a very hot company, Kamal Shah, the CEO of StackRox. Kamal, great to see you! >> Thank you, and great to be here, Jeff! >> Absolutely! So for folks that aren't familiar with StackRox, give us the overview. >> Sure, so in a nutshell, we do Kubernetes Security, and so as we've heard all day today, enterprises are deploying microservices, containers, Kubernetes, and we do security for your cloud data infrastructure. >> So how does security work for Kubernetes versus security for other things? >> Yeah, so the use cases for security, or the mission for the security team is the same, right? You got to harden your environment to prevent the bad guys from getting in. >> And, you have to make sure, despite your best efforts, if somebody does break in, then you catch them before they do any damage, right? But the how you do security has to evolve for the cloud data stack, right? It has to understand the containers are immutable affirm all infrastructure, you have to understand that it's not just about the container, but it's also about the orchestrator, and specifically Kubernetes, and it's also about making sure that you seamlessly integrate with dev ops processes, automation and workflow. So it requires a fundamentally different approach to security than traditional security tools. >> So you know, we talk a lot about the increasing attack area that's offered by IoT, right? And increasing attack area that's offered by all those API's and all these interconnected applications, but I've never heard anyone really talk about containers or orchestration as kind of a new attack surface. Did we just stop paying attention? Is that something you're seeing happen? >> Yeah it's something that is starting to emerge, and we've seen some high-profile breachers at a large next generation electric car company, and a large shopping site where misconfigurations led to security breaches in the Kubernetes' environment, and Kubernetes' ecosystem also did a Cube security audit, and so I think we're going to start to hear a lot more, because there's more and more applications are being deployed in production. It's creating a new attack area, and as the old saying goes, the predators go where there's food in the system. >> And so if you're not proactive about it, I think it's going to really hurt as you deploy containers in Kubernetes. >> Right, so we hear over and over and over again about breaches because people misconfigure stuff. That just seems to happen, whether it's a database or this, that, and the other. And I think we can pretty much safely assume everyone's going to get breached if they haven't got breached already, 'cause we hear about it all the time. How do you catch them fast, limit the damage and try not to have too much vulnerabilities? >> Exactly, so the use cases for what we do at Kubernetes are the same. Right? Its vulnerability management, it's configuration management, and we just did a study around the state of container in Kubernetes security and misconfigeration was the number one concern. Because the reality is that Kubernetes, there are a lot of knobs. And each knob has multiple options, so if you're not careful you can really misconfigure your environment and make it so much easier for attackers. >> Right, right. >> And it's precisely what happened at the two examples I sighted earlier. So a misconfigerations is important, runtime security is important, and also compliance. Let's not forget about compliance, right. You have to make sure that you meet your PCI, HIPAA, NIST, and CIS benchmark standards for this cloud native stock. >> So what we're seeing is that these are all becoming very, very important and as a result, it's increasing awareness as Kubernetes gets more prominent. >> Right, and then they are creating and tearing down hundreds, thousands, millions of these things at a nidicolous pace. >> I mean exactly. Kubernetes came out of Google, they open sourced it, and it's really what allows you to deploy, manage, containers at scale. Apparently, they manage hundreds of millions of container a day using Kubernetes, it's incredible. >> Jeff: Oh yeah, I saw a statistic that Google launches 4 billion containers per week. That was from a presentation, actually from a 451 analyst from like 2 years ago. So one can only imagine the scale. >> We are also seeing not quite 4 billion containers per week, but we are seeing thousands, and tens of thousands of containers at scale at companies everywhere. They are all deployed in production, and now they are waking up to security. The good news here is that they are waiting for breaches to happen before they solve the problem. There's still a lack of awareness, and what Sumo Logic has done today with the announcement around continued intelligence for Kubernetes just increases the awareness around, hey we have to solve observability, which is logs, metrics, and tracing, which is what Sumo does, and security for your cloud native infrastructures. >> Yeah, I mean the automation is so important, right? You can't do any of this stuff with this exponential growth of data, exponential growth of pushes, of new code releases. There's so many pieces in this, so automation is a huge piece of the puzzle. >> Automation is paramount and with this new infrastructure there aren't enough security people to solve this. So security has to become everybody's responsibility. And the only way we are going to solve this is to automate it. It also has to integrate with your DebOps processes and automation and work flows. If you don't, then the DebOps body is going to reject the security organ, right? So it has to be seamless in the way you deploy it. >> It's interesting you say that because we go to RSA, forty thousand people, more vendor than you can count, it bulges Moscone to the absolute edges. Everyone says over and over that security has to be baked in the entire process from beginning to end, it's not a bolt on and can never be successful as a bolt on. So it surprises me to hear you say that still a lot of people are kind of behind the curve. >> Well I mean if you think about I, even though they say that, right? In a traditional model of the application you go to spend 6 months building it and then you can go spend a couple of weeks or month hardening and putting security around it. But when you are launching applications every 6 hours, you can spend 6 days addressing security, so it has to be built in. And speaking of RSA, if you recall, last year the big talk at RSA was around AI, right. Everything was AI driven security. My prediction, my bold prediction for this RSA is it's going to be all around Kubernetes security. >> Yeah, well it's applied AI. Applied AI for Kubernetes. >> Exactly. >> And that's what you need. I always feel for the SISO just walking the floor at RSA going, "Where do I begin? I mean where do I spend my money, how do I prioritize?" It's kind of like an insurance problem. You can't insure to the nth degree. You got to have a budget, but how do you deploy your assets? It's got to be super, super confusing. >> It really is. I think what your seeing is that SISO's are relying on their DEV and IT ops teams, right? They are partnering with the VP of platform, the VP of infrastructure, the VP engineering, because when you think about this new world security is really, the ownership of security is now shifting from the information's security teams to DevOps teams. So security teams still drive policy, and they still want to make sure they do the trust and verify, but the implementation of the security is now being owned by DevOps teams. So its a big cultural shift that's going on in organizations today. SISO's have to realize that it's no longer just them, but they have to partner with their DevOps counterparts to effectively address security for this cloud native stock. >> Right, so tell us a little bit about the relationship with Sumo. How do the applications work together? What's the solution look like when the 2 solutions are brought together. >> So Sumo has been a great partner. We have several joint customers. The simplest way to think about this is that Sumo does observability for Kubernetes, so that's logs, metrics, and tracing, and we do security from Kubernetes. We are the yin to their yang. What we do is we have taken all the intelligence we get from security and we feed it into the Sumo dashboard. Sumo customers get a single pane of glass, not just for the observability data, but also for their security violations, weather its for vulnerability, weathers it's for configuration or if it's for runtime threats, right? You get it all in one single place. >> Right. So I just want to get your take on kind of this rise of the momentum behind Hybrid Cloud that we've seen recently. Big announcement at Google Cloud show, with Anthos. Big announcement between VMware and Amazon. It always kind of swings back and forth. It was all in to public cloud and now there's a little bit of a pullback in Hybrid, but that's terrific for you. The fact of the matter is workload should run where they should run, they don't really care it's what's appropriate. Horses for courses, right? >> Precisely so, we see the shift from public cloud to Multi-cloud, and then from Multi-cloud to Hybrid cloud. The underlying infrastructure that makes that a reality are containers and Kubernetes, right? And that's why we've seen this tremendous momentum on Kubernetes. What we are seeing is customers that want to give their Dev teams that flexibility to pick their favorite cloud, or to do it on premises, their private clouds. But they want to make it in a single security solution that gets integrated no matter where you run your infrastructure and that's integrated back to your Sumo dashboard. So you have visibility across all Dev teams, all your application infrastructure, regardless of where they are running. There is one security standard that gets implemented. That is really, that's the future. You don't want to be beholden to a one claw provider, you want flexibility, you want choice. Kubernetes allows you to do that. >> Well and the whole thing becomes more autotomized, right, with autonomic memory, autonomic compute, autonomic store, throw that on an IoT and Edges and now you're starting to distribute all those pieces all over the place, which is going to happen. >> Kamal: It is going to happen for sure. >> All right, looking forward I can't believe we're almost through 2019, it still shocks me everyday I look at the calendar, but what are some of your priorities looking forward? What are you guys working on? What do you see coming down the pipe? >> Yes, so you touches on a couple of these. So today, is a lot of talk around Kubernete. We are seeing Kubernetes also get deployed in IoT and edge devices, we are also seeing they are being used to manage serve-less infrastructure. So we are going to continue to evolve as Kubernetes evolves. The other big trend that we are seeing in the market today is around service mesh. People talk a lot about Istio and Linkerd and using service mesh as your policy framework to drive consistent policies across applications, so that's another area where we are innovating very rapidly and that will become, I think, more and more real in enterprise deployments over 2020. >> Well, congratulations Kamal to you and the team. I think you picked a good horse to ride on, I should say ship, right, with Kubernetes. Thanks for taking a few minutes. >> No, thank you for having me. I can officially say now that I've checked off one of my professional bucket-list items, which is to be on the Cube with an old friend. So thank you for having me. >> Check that box man. All right, he's Kamal, I'm Jeff, you're watching the Cube. Were at Sumo Logic Illuminate from the Hyatt San Francisco Airport. Thanks for watching, see you next time.

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

>> Narrator: From Burlingame, California, it's theCUBE, covering Sumo Logic Illuminate 2019! Brought to you by Sumo Logic. >> Hey, welcome back everybody, Jeff Frick here with theCUBE. We're at Sumo Logic Illuminate at the Hyatt Regency, San Francisco Airport. Our second year here, about a thousand people, third year of the conference, a really good vibe. You know I think some of these cases where the marketers really come to Sumo Logic in terms of data and data monitoring, and there's so many applications that are business and security, and operations. We're excited to have our next guest. He is Lior Mechlovich. He's an architect at Informatica. Lior, great to see you. >> Great to see you, too. >> Absolutely, so you said you've been coming to this for a couple years, just kind of general impressions as it's grown. >> Sure, it's my third year, it's grown very nicely. Always exciting. I think there's a very nice vibe to this conference. I always learn new things so we've been with Sumo for more than four years now for Informatica. And excited as always. >> Yeah, and we've been covering the Informatica show. I think we've looked it up, since 2015 so, we've been doing a lot of work and you guys are right in the heart of this whole data thing, >> Right. >> And you been part of the kind of migration from pretty much pure on-prem, to Cloud. There's rush to public Cloud, and then now kind of this Hybrid model. So you kind of look at the data perspective you know, what's kind of your take as this thing has evolved over the last several years? >> Sure, so we have been around for 26 years. I think building a lot of on-pram, data platforms for being the enterprise Cloud data management that Informatica sells with basically getting your data inside our outside the organization from Clouds, on-pram, or whatever integration pattern you have and we decided four or five years ago to be a Cloud-first company and migrated most of our products to be on Cloud to provide them as a service. And for us, it was a huge journey, we needed to take some offering that we had in the Cloud, some products, and really revamp and building a new microscopic architecture and then slowly migrate all the customers. It took us over a year to make that. We currently run on all three Cloud providers. And really using Sumo mentoring tools to really understand the impact that we have on our customers during this migration. It was a very successful. They hardly noticed that-- >> Oh good. >> Only the nice UI, but they hardly noticed the problems. I mean we really changed a lot of things. >> What is some of the things you learned in that process that you can apply now with just some of your customers in terms of data migration and operating in a Cloud situation versus a traditional data center? >> Sure, so I would definitely highlight the need to be able to roll back and the need to always keep really good money to working it and understanding how the end user getting impacted. And so we really kept that in mind. Everything we do try do always do it side by side, and then when we migrate we're really sure that it is successful and there's no impact on the customer. So I think that's definitely too, harshly monitored everything and be able to roll back when you need to, because you will need to at some point. >> But the rollback is funny, because it use to be you had you know the release cadence was significantly slower than now. And now you've got all these kind of micro pushes that are going on multiple times a day. >> Yeah. >> So how does that impact kind of keeping that safety net? That rollback safety net? >> So it's interesting. So we actually don't deploy that many times a day. Where we can really impact the customer so we deploy the things that are not customer urgent impacting production more, but still the really heavy productions of the thrilling part of the customer; we try to minimize that and make it very customer aware okay. >> So basically they choose their own windows of maintenance and all that. But our customers again hospitals, all kinds of very important, then we are in charge of the data byte in those places. So we don't want to just push whatever we can. We really cannot take that, even a rollback of 1%, it can be very bad so we're a bit more conservative models of deployments, but actually that means we put a lot of effort in our monitoring. What is going on doing those deployments. >> Right. All right, so what are the big trends that happen? I mean containers have been around for awhile, but we really saw kind of the rise of containers in terms of the popular consciousness with Docker couple three or four years ago, and then a couple years ago the Cooper 90's coming in for the orchestration. From your point of view how had those things impacted your world, and how you do your job, and take care of your customers? >> Sure, so for us Cubernetics is really a great opportunity to standardize the way that we deploy across different products. So we have our platform, but we have also different products; different people across the globe. We're a very multi-globe organization, and to get a standard like Cubernetics to help us standardize to get more releases, more stable environments that really solves a lot of problems, because we had this migration that I talked about really left us with a lot of clusters across the globe, different time zones. It was really hard to standardize on the pipelines, and to deploy to really minimize the problems that we give to the end user at the end. >> So we really took that opportunity to use Cubernetics, to use containers to minimize the difference it has from the developer machine all the way to production. To automate the most we can so when it's really is excelling in this. Yeah, so that's where we really... took those containers apart. Today we are in migrating, so not all of that, but we truly see the benefits of standardization, of immutable infrastructure as that key component for us. >> This is just so great, because you have such a longitudinal point of view having been in. The company's been at it for awhile, and you've been at the company for awhile. So another topic I'd love to get your thought is just kind of this exponential explosion of data. I mean it would be curious not to know the numbers, but kind of the scale of data in which you guys are dealing with for you customers, and how that has changed over the last several years before you even really factor in IOT, and this next kind of machine to machine explosion? >> So we definitely see that explosion of data. It's not just the explosion. It's also the different types, and where data has been on-prem, now moving to Cloud. Where do people want to run off all those work loads? As of course a lot of feedback for us as well need to support all the Cloud providers when we use to do a lot of Hadoop on-prem, right? It's all changed now too. >> All the Cloud providers, the data it's theirs. So the data move, data locality is a big thing, Now we need to run all those things on the Cloud. So, I don't remember the exact numbers. I guess we're doing something of 2.5 billion transactions a month for like number of records that we serve. That being we usually just see more work loads, more people, more use cases for onboarding more data from Cloud applications. The data became more dispersed not just more data, but the sources has become like everybody needs to integrate Salesforce or Workday with their on-prem that gives unique opportunities for this kind of data. >> Well, it's funny when you talk about the workloads, because it always use to be, do you bring the workload to the data or the data to the workload, and a knock on the Cloud is that you got to get all the data into the Cloud, and pay for the transport of the data. And there's data gravity that said once you have it in a central location like that the opportunity to put applications against that data is much much higher than if you're bringing the data to the application. You see and how are customers taking advantage of that opportunity? >> So for sure we saw they did that move to the Cloud. When we started from on naked Cloud 10 years ago our entire model was hybrid, so we can stick around on-prem, because the data was on-prem, and since then our hybrid model that you still run both on-prem and on Cloud, you can see the change right? You can see more of our agents. We have an agent based architecture to really being deployed much more on easy 2's, on AKS or whatever to run those workloads in the Cloud. >> Right, but I would imagine the number of workloads applied to each data set now have increased significantly, because now it's in that central repository. >> Yes, and definitely you can see those data legs being built, and mostly in the Cloud. That gives unique opportunity. >> So just get your perspective after a couple days here. I know you haven't been here for a couple of days. We're just getting started at this show. What does Sumo Logic bring to you and your team? What does it enable you to do that you couldn't otherwise do? Why are you happy to be a customer of Sumo? >> Sure, so four and foremost it's the democratization of data. I really like to say that internally. In an organization that's spread across the globe, really sharing insides based on data, it's very important. When you have many R&D centers that can just send this summary; send the data and show people what they mean saves so much time, and so we use it across. We use the customer success, product management to understand feature being used, SRE's, developers. All of those really can communicate based on data. In this Microsoft Office tool you cannot do it without that. You cannot do it without linking, because the different products that we onboard on the platform will not be able to communicate effectively without that. So that's very important, and giving that landing pages dashboard templates for onboarded services to have this kind of standard to follow to monitor how to operate that's very important for us. >> That's great. Go ahead. I'm sorry I interrupted you. >> Sorry, and the key place that we brought Sumo in is basically for instant management. So how to understand when something doesn't work just to try to understand the blast radius, which products are impacted. We have a variety of products, so just in minutes we minimize that in four hours to minutes trying to understand what exactly is going on. Who's impacted to update the customer  and all that. >> I love the part you talked about the democratization, because again I talk about it all the time, and I'll talk about it again, but to drive innovation in a company I think such a key piece of it is to enable more people to have more information, and the tools to manipulate that information, so they see opportunities to make improvements here, there, and otherwise and it sounds like you guys are really using it for that. >> Definitely. Definitely. >> In this case. >> You know when you get some people that you never knew that even though we have a customer support guys that did some crazy dash wars that we had no idea it's possible even, and they really getting chance to work with customers better to really tell the customer, "Oh, you just did that and that. "Maybe you'll try this option." And we found that even communicating, and really minimize the time it takes for them to figure out what's going on that it's been really impactful. >> With no call to It to help (laughs). >> And it was never the intent, so we wanted to allow dev's and off's to operate, and all of a sudden you're getting customer support without even telling them. >> Good, well Lior thanks for sharing your story and really appreciate you taking the time. >> Thank you. >> All right, he's Lior. I'm Jeff. You're watching theCube. We are at Sumo Logic Illuminate 2019. Thanks for watching. We'll see you next time. (upbeat techno music)