(techy music) >> Hey, welcome back, everybody. Jeff Frick here with theCUBE, we're in the Palo Alto studios having a Cube Conversation. You know, we go out to all the events. We talk to a lot of executives and engineers, and developers, et cetera, but what we really like to do when the opportunity is here is talk to practitioners, people who are actually implementing the technology, putting it in play, trying to get a competitive advantage, and we're really excited to have our next guest. He's Steven McCaa, he is the senior director in user services and support at the Lending Club, Steven, great to see you. >> Thank you. >> So, for people that aren't familiar with the Lending Club, give us kind of the basic overview. >> Sure, we've got, so the two halves of business. One is perhaps you'd like a loan, restructure your debt or just some life changes like a wedding or something like that, so you could come to us for a personal loan. The other half of our business is for people who have money that they wish to invest in a different kind of vehicle, and so they invest in other people's debt, and it gives them a steady cash flow, because when the loans get paid back they get paid, and so we provide a marketplace for those two halves to meet. >> So, that's really what makes you different, because clearly there's lots of places that people can go get a loan, but I've never heard kind of that second half of the equation. >> [Steven] Yeah. >> So, what percentage of your capital comes from people participating on the supply side? >> So, almost our, well, all of our debt is designed to be sold on the marketplace. >> [Jeff] Oh, it is, okay. >> We invest almost, well, we invest a little bit of money just mainly as a float, but almost everything is for our investor population. >> That's so cool, and is it done in like a fund or how is it kind of structured, are you kind of buying into a portfolio of loans? >> So, when you go onto our platform you go in and you can see the type of customer that you wish to invest in, certain FICO score, certain geography, certain, you know, background and jobs, the reason why they're wanting a loan. And then you select some loans individually, but you're not buying the entire loan. Let's say someone wants $5,000. You're going to invest $25, $50 in that person and you're going to find 100 people like that to invest your money, so that way if someone does default, that does happen, you're not out your entire amount. >> Right, right, and does the transaction happen on demand or I put in whatever my amount is I want to put on your platform. I put my profile in and then you basically parcel it out as those customers come in? >> Yeah, so basically what's happening is when you go on the platform you're seeing people that have already applied and we have basically approved, and you are funding their loan. So, you have a few days to decide if you're going to, which loans you're going to fund before they disappear because we are going to have to give the people money, yeah. >> Right, how cool, and can you share the scale of kind of the size of your operation, or I don't know what's public or private. Obviously don't say anything you're not supposed to say. >> We are, yeah, so we actually are the nation's largest personal loan lender in this market space. >> Wow. >> Yeah. >> Several billion dollars a year. >> Very cool, so presumably you have an advantage because you're a modern company, you're looking at, you know, different types of data, more data, cutting it different ways than maybe a traditional bank that's just using your FICO score or some of the-- >> Exactly. >> Kind of more traditional scoring methods. >> Exactly. >> So, big data and data in general, tremendous piece of your guys' core business. >> Mm-hmm, yep. >> So, what are some of the things maybe, I don't know if you can share, that you look at that maybe people would never think that's a valuable-- >> Yeah. >> You know, not the whole portfolio but are there some-- >> I can't get into, I can't get into too much details-- >> Some funny ones. >> Because it is somewhat, you know-- >> It's your secret sauce. >> Propriety >> Yeah, yeah. >> That's the secret sauce, can't get into details. >> Don't give me any secrets. (laughs) >> You know, but we do use a wide variety of the traditional sorts of things, you know, that people are familiar with, but we look at things that are a little bit outside the box, too. >> [Jeff] Yeah. >> You know, that have a lot more to do with who you are as a person and the type of, you know, credit that you've had in the past and things like that. >> Very cool, all right, and then what do you do? Obviously we read your title, but what-- >> [Steven] Yeah. >> What do you keep busy with all day long? >> Yeah, so I-- >> Besides coming to visit us here in Palo Alto. (laughs) >> Yeah, I keep busy with making our internal employees happy. So, I'm very, I'm on the corporate technology side of Lending Club and I make sure that our employees have the tools that they need to be able to do their jobs on a daily basis. >> [Jeff] Right. >> So, I'm running backend infrastructure, things like our email services and stuff like that, but also just the day to day grind of laptops and desktops. >> Right, right, keeping the lights on. >> Yeah. >> So, classic kind of IT. >> Mm-hmm. >> So, you're here on behalf of Cohesity, so where does Cohesity play in your world-- >> Yeah. >> Now and then we'll get into it a little bit deeper as to why and how. >> Sure, so Cohesity is basically our new backup platform. We were a very traditional backup environment, standard, you know, software, backend virtual disc system. Very, you know, very traditional type shop. Honestly I've been in IT for over 20 years and I put in a system like this one of my first gigs as a consultant over 20 years ago. >> [Jeff] Right. >> So, you know, it was time to look outside the box and maybe shake things up a little bit and look at something that's been, you know, developed in the last decade. >> [Jeff] Right. >> And so that's how we kind of landed at Cohesity. >> So, what appealed to you, what were the kind of top two or three things you were looking for? >> Well, our huge, our biggest challenge was, you know... I mean, back when is started in IT I was backing up four gig hard drives and four gigs was awesome, you know, and now my phone is-- >> Four gigs... Not four terabytes, four gigs. (laughs) >> Yeah, you know, and now my phone is bigger than four gigs, a lot bigger than four gigs. >> A lot bigger than four gigs. (laughs) >> And that backup system couldn't backup my phone, and so, you know, we have terabyte file systems and things, and with the traditional backup system that was, if it was successful it took days. >> Right. >> You know, four days or so to actually do a backup, and so that's not tenable, and so, you know, going to something that rather than, you know, copying every file every single time does it on a block level and is a little more integrated directly into our virtualization layer- >> Right. >> Was the right way to go. >> Well, and I love how you said before we turned on the cameras that when you make a decision to replace something you try very, very hard to actually replay something and not just add something new. >> Yeah, so I drive my staff a little nuts because they know that when they come to me and say, "We're going to do this new exciting thing "and we're going to stop doing this over here," I'm like, "You're going to stop, that means I'm going to walk in the data center and flip that thing off." >> Turn it off. (laughs) >> Right, and they're like, "Well, "but there's that old stuff." I'm like, "Yeah, well we got to get the old stuff out," and so that was really one of the competitive advantages that Cohesity had for us is because they're not just a backup appliance or whatnot, they do have a file system in there. We could basically replicate all our old backup jobs into the Cohesity, and that way we, yeah, we have to keep the software around, you know, and been able to restore an old job if we had reason to do so we'd be able to, but at least we can go into the data center and shut that old device off, so... >> So, were there any particular features that jumped out at the top of the list, or was it just you're looking for really modern architecture with a whole bunch of features. >> Yeah, it's really, it's a very modern architecture. It has some great capabilities to move data into the cloud and into AWS space, to actually use the sort of same technology and the same policies to backup devices in the cloud that you would use on-prem, and so, you know, it has a lot of great features but to us, really the competitive differentiator was that file system. >> [Jeff] Okay. >> Being able to move our old backups directly into the system and be able to use our old backup software. We didn't have to do, you know, restore and re-backup or anything crazy like that, so... >> Right, so all your peers are all probably wondering how hard was it, (laughs) you know, what was kind of the scope of the effort, what was the scope of moving the old stuff over? >> Well, so-- >> What would you tell to somebody making, you know, considering this move? >> Have a good partner, I hired our integrator to do the actual migration, and one of the reasons I chose the integrator I chose is because they were willing to bid on this knowing that what they really were going to do is dial in to my system for four hours a week for a very long period of time and just scheduling backup jobs to keep the engine humming, and there wasn't a lot of, like, sit there and there was no value in having one of my people sit there and watch stuff because it's just backup restores. >> Right. >> It's not rocket science, but it does take a little bit of handholding. So, I outsourced the actual migration of all the jobs. The actual setting up of Cohesity is, like, you know, a couple hours. Once it's racked it's, you know, actually setting it up and the migration of, you know, turning that on, making it active, doing some test restores, you know, doing some test backups, test restores of systems and then just, you know, opening the floodgates, that was relatively simple. >> And you mentioned that one of the things that appealed to you was an integration to public cloud environments beyond just the on-prem. >> [Steven] Mm-hmm. >> Are you using that, and if so, how are you divvying up what goes where? >> Yeah, so most of our services are on-prem or cloud services. You know, no infrastructure, we're just, you know, the sales forces that work days, those sorts of services, and so we don't have a ton of stuff in AWS space on the corporate side. My peers in the product side would be a very different answer there, but what we're doing is we're doing migration so that we can do our DR in the cloud so that we can keep stuff on-prem, but if we needed, you know, if we had a problem on-prem we can do DR. We're also doing replications between our COLOs, but that's our primary use case-- >> Is to get it off, so it's cool. >> [Steven] Yeah. >> So, do you consider that kind of secondary storage or it's really more just pure backup there if you had a problem? >> Yeah, so I mean, so we are looking for secondary storage and things, you know, our file servers and things like that. We've had such good performance with the backup migration, and so we're looking at getting off of our file service so we don't even have to back it up, so that it's just native objects inside the device. >> So, I'm just curious in terms of kind of the data growth that you have to deal with on a day to day basis, your data growth in terms of the IT shop is probably... The explosive stuff's probably happening more, I would imagine, on the core product or-- >> [Steven] Well, we actually-- >> You're smiling and making a funny face. >> Yeah, so just let me, we didn't talk about earlier... >> I must be... (laughs) >> So, one of the things that was very interesting, we put in the Cohesity system and we sized it all out and based on our, you know, data volumes and things like that, but what we didn't realize is that we had a system that is a part of our statistical analysis for our loan modeling, okay, and what we didn't understand is we couldn't back that up. It was too large and we couldn't back it up with our old backup system, and what the statistics guys are doing is they're building a model and going, "Hm, does this work?" And they'll run a ton of data through there and they'll create a model and it'll be two terabytes in size and they'll take one, look at it, and go, "Nope, that doesn't work," and they'll throw it away, okay. And then a week later they go, "Well, you know, "maybe, let me look at that again." And they call us up and say, "I need "a restore that two terabytes." (laughs) Well, in the past they couldn't do that because we couldn't back it up, all right. >> Right, right. >> And so, all of a sudden we can back this stuff up, and so it's getting backed up and we're just starting to do these restores, and so they only had a working size of 20, 30 terabytes or something like that, but what we found out was they generate like 10 terabytes a day and they throw it away. And so, our backup volume had nothing to do with the size of the volume that we were giving them, it had to do with how much data they generate. So, they generate a ton of data, we had to expand-- >> So, they want to back up Mondays, Tuesdays, Wednesdays, and Thursdays-- >> They want to back up-- >> Even though the sum of that is 5x what-- >> Yeah. >> Is their working amount. >> Yeah. >> But they still want it backed up. >> Yeah. >> And they still make the call-- >> Well, in the past-- >> "Please bring it back, Steven." >> They wouldn't be able to call us, so they would rerun the job, it would take them a day or two and then they'd have their answer. Now we can expose that old backup job directly to them, it's maybe not high performance because it is secondary storage, but-- >> Right, right. >> But at least they can take a look at it and kind of go, "Yeah, okay, let's bring that back "into our primary storage and continue working with it." And that recreation, it's not so much a Monday, Tuesday, Wednesday, it's really like a, you know, 10 AM, noon, two, four kind of thing. >> Right, right. >> Yeah. >> So, has that changed the behavior in kind of the frequency or their work environment where now they feel more comfortable-- >> [Steven] Yes. >> Having a lot more-- >> [Steven] Yeah. >> Of those models, a lot more simulations, and ultimately should help their business, right? >> Yeah, well, and the thing is that it gives them the ability to quickly, you know, play with a model, throw it away, and they can throw it away knowing we can give it back to them quickly, rather than having them completely regenerate the data. So, they are able to churn through a lot more models a lot faster. >> How many weeks do you keep that stuff? Or how many versions, you must have some limit-- >> Well, yeah, there's a lot of data around that. >> You can't go from, like, zero to infinite. >> Yeah, there's a lot of-- >> But maybe it's a negotiation. >> Yeah, there's a lot of debate about that. There's some negotiation around that. >> Right. >> I mean, we have multiple different working areas and some of it's like, "Okay, if you think you might "need it and you want to keep it around for a while," and we actually may use it, then it goes into one storage area-- >> [Jeff] Right. >> And we keep that for a lot longer. >> That's funny, that's a really elegant example of something we talk about all the time in theCUBE, which is, you know, at what point in time will the value of the data become a balance sheet asset, whether that's your core data in your product set, or you know, I'm sure there's a whole lot of value in all these models that they're building, and before data wasn't necessarily considered an asset. It was a liability because I had to buy all this stuff to store it and keep it, and like you said, some stuff I couldn't even store. Now people recognize it's of huge value. It's not necessarily on the balance sheet yet. I think it will be at some point down the road, but this is a terrific example of how you can explode the value by exploding the access, the reuse, the capability without necessarily exploding the budget that you got to take back up to your boss. >> Yep, yeah, very much so. >> And then to be able to drive all these different models, tweak them, customize them, standardize them, target them, really they must be loving that. >> They're very happy, yeah, yeah. (laughs) >> Okay, so as you look down the road... Like you say, you've been in the business a long time, the data explosion's going bananas. You're in a pretty cool, unique little marketplace. What are some of your priorities, what's next for you? >> Well, okay, so this is nothing to do with what we've been talking about, but a month ago I turned my laptop into my desktop support team and I now run everything off my phone. >> [Jeff] Oh, you turned your physical laptop, you gave it over. >> My physical, that thing, I don't carry that thing, that's too big, baby. (laughs) So, we have a VDI implementation and I have a Samsung phone that has a dock, so I dock it and I have my monitor and I go in to do VDI, but I don't have a laptop anymore. I can do everything I can do from my phone, and so I think that is, like, how to make that something that the business users can do, rather than just us techy guys who, like, want to push the boundary and push the envelope. I think that really is the future. You know, the whole idea of mobile first, it's kind of like mobile only. >> [Jeff] Right. >> You know, we really shouldn't be doing mobile first, it's mobile only and how can you make it work. >> And I like your style, you're just extreme. Like you said, you just turn off the old light switch. If you're going to make the move, make the move. >> Yeah. >> Just the rip the bandaid off and get on with it. >> Yeah. (laughs) They've got the laptop, I told them redeploy it, it's a nice laptop, give it to somebody else. If there's something I can't do I'll go get one of the loaners for a couple hours. >> Don't say that too loud, Chuck's looking for a few laptops. (laughs) All right, Steven, well thank you for coming by and sharing the story. I got to dig more into the company. I didn't know that whole kind of backside in terms of the investor opportunity, that looks pretty cool. >> Yeah. >> And again, thanks for stopping by. >> All right, thanks for having me. >> All righty, Steven, I'm Jeff. You're watching theCUBE from the Palo Alto studios, Cube Conversation. 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, everybody. Jeffrey here with the Cube. Welcome back to our ongoing coverage of the biz. Opps manifesto Unveil Something has been in the works for a little while. Today's a formal unveiling and we're excited to have three of the core founding members of the manifesto Authors of the manifesto, if you will joining us again. We've had them all on individually. Now we're gonna have a great power panel. First up, we have met Kirsten returning. He's the founder and CEO of Task Top make good to see again. Where you dialing in from? >>Great to see you again, Jeff. I'm dialing from Vancouver, Canada. >>Vancouver, Canada. One of my favorite cities in the whole wide world. Also, we've got Tom Davenport coming from across the country. He's a distinguished professor and author from Babson College. Tom, great to see. And I think you said you're a fund Exotic place on the East Coast. >>Falmouth, Massachusetts, on Cape Cod. >>Nice. 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 you coming in from? >>From Boston. Right next to kick off. 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. Biz Opps Manifesto What was the initial reason to do this? And how did you decide to do it in a kind of a coalition way, bringing together a group of people versus just making it an internal company, uh, initiative that, you know, you could do better stuff within your own company Surge. Why don't we start with you? >>Yeah, so? So I think we are really a critical juncture, right? Many large enterprises are basically struggling with their digital transformation. In fact, many recognized that the the Business Society collaboration has been one of the major impediments to drive that kind of transformation. And if we look at the industry today, many people or whether we're talking about vendors or system integrators, consulting firms are talking about the same kind of concepts but using very different language. And so we believe that bringing a lot these different players together assed part of the coalition and formalizing, uh, basically the core principles and values in a busy office manifesto. We can really start to have kind of a much bigger movement where we can all talk about kind of the same concepts. And we can really start to provide kind of a much better support for large organizations to transform eso, whether it is technology or services or trading. I think that that's really the value of bringing all of these players together >>and Mick to you. Why did you get involved in this in this effort? >>So I've been closely involved the actual 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 started just noted, we really need to improving. At the business level, every companies trying to become a software innovator trying to make sure that they can pick them, adapt quickly in 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 that 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. Organizations are agile. Transmissions are actually failing because they're measuring activities and how they're becoming more agile. Have teams air functioning, not how much quickly they're delivering value to the customer. So we need to now move. Asked that. And that's exactly what the buzz off there's also manifested. Provides, >>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 and a lot of work around analytics and data on data evolution. So there's a definitely a data angle here. I wonder if you kind of share your perspective of of what you got excited Thio to sign on to this manifesto? >>Sure. Well, I have. You know, for the past 15 or 20 years, I've been focusing on Data Analytics and AI. But before that, I was a process management guy and a knowledge management guy and a in general. I think, you know, we've just kind of optimized at too narrow a level. Whether you're talking about agile or Dev ops or, um, ml ops. Any of these kind of obs oriented movements, we're making individual project, um, performance and productivity better, But we're not changing the business 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. >>That's 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 Cove it 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 both within your customer base and your partner base, but also then you're employees. When 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've 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 on. Do you really have Thio prioritize and get it right? >>Yeah. I mean, I'll just start by quoting city An Adele basically recently said that there's bean two years of digital transformation just last two months, and in many ways that's true. Um, but But yet when we look at large enterprises, they're still struggling with kind of a changes in culture that they really need Thio drive to be able to describe 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. About 40% of the personal loans today are being origin dated by Finn tax of a like of Sophie or or ah Lendingclub, right, Not your traditional brick and worked for bank. And so the while there is kind of ah, much more of an appetite, and it's it's more of a survival type driver these days. The reality is that in order for these large enterprises to truly transform and engage on these digital transformation, they need to start to really aligned the business 90 you know, in many ways and make cover that actually really emerge from the court desire to really improve software predictability, but we've which we have really missed is all the way. Start to aligning the software predictability to business predictability and to be able to have continuously continuous improvement and measurement off business outcomes. So by lining, but of this dis kind of inward metrics that I t is typically being using to business outcomes, we think we can start to really help different stakeholders within the organization to collaborate. So I think there is more than ever. There is an imperative to act now, um, and and results. I think it's kind of the right approach to drive that kind of transformation, >>right? I want to follow up on the culture comment with Utah because you've talked before about kind of process, flow and process flow throughout a whore, unorganized ation. 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 a tech issue to get this digital transformation in your organization. >>Yeah, you know, I've always found that the soft stuff the you know, the culture of the behavior of the values is the hard stuff to change and mawr and mawr. We we realized that to be successful with any kind of digital transformation, you have tow change, people's behaviors and attitudes. Um, we haven't made 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 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 cultural behavioral dimension and not just assuming that it will happen if we if we build a system, you know, if if we build it, they won't necessarily come right, >>right? So I want to go toe to you, Nick, because, you know, we're talking about work flows and flow. Andi, you've written about flow both in terms of, 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 because you have a lot less ah, wiggle room in tough times. But you also talked about flow from the culture side on the people's side. So I wonder if you could 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 just said. If you're optimize, you need to optimize your system. You need to optimize how you innovate and how you deliver value to the business into the customer. Now what we've noticed in the data since that that we've learned from customers value streams, enterprise organizations, value streams is that what's taking six months and to and to deliver that value, the flow is that slow. You've got a bunch of unhappy developers. Unhappy customers, when you're innovating, have so high performing organizations we can measure their intent flow time in days. All of a sudden, that feedback loop the satisfaction your developers measurably goes up. So not only do you have people context switching last year, delivering so much more value to customers at a lower cost because you've optimized for flow rather than optimizing for these thes other approximately six that we use, which is how efficient my annual team. How quickly can we deploy software? Those are important, but they do not provide the value of agility, of fast learning, of adaptability, of the business. And that's exactly what the bishops manifesto pushes your organization to. You need to put in place this new operate 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. I'm gonna go back to Utah, him on that to follow up, because 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 vs B, you know you could have a very different product that that you kick out. You know, my favorite example with With Clayton Christensen and Innovator's Dilemma talking about the three inch our 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 Palm because it was the it was the game council which which drove that whole business. So when you're talking to customers and we think we're here 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, forced them to to look at the at the prioritization and make sure they're prioritizing on the right thing is make just that. What do you optimizing for? >>Oh yeah, 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 toe of the decision toe 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 too narrowly, say, or you frame it as an either or situation when you could actually have some of both, um, it's very difficult for the process toe work out correctly. So in many cases, I think we need to think mawr at the beginning about how we frame this issue or this decision in the best way possible before we charge off and build a system to support it. You know, it's worth that extra time to think. Think carefully about how the decision has been structured. Right? >>Surge. I wanna go back to you and talk about the human factors because we just discussed you could put in great technology. But if the culture doesn't adopt it and people don't feel good about it, you know it's not gonna be successful. And that's going to reflect poorly on the technology. Even if I had nothing to do with it. And you know, when you look at the core values of the best hopes manifesto, you know a big one is trust and collaboration. You know, learn, responded pivot. Wonder if you can share your thoughts on trying to get that cultural shift s 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 position. >>So I think I think at the ground level, it really starts with the realization that we were all different. We come from different backgrounds. Oftentimes we tend Thio. Blame the data. It's not uncommon my experience that we spend the first, you know, 30 minutes of any kind of one hour the conversation to debate the ability of the data on DSO, one of the first kind of probably manifestations that we've had. Our revelations as we start to engage with our customers is by just exposing high Fidelity data set two different stakeholders from their different lands. We start to enable these different stakeholders to not debate the data, but that's really collaborate to find a solution. So in many ways, when when when we think about kind of the types of changes were trying Thio truly affect around data driven decision making? It's all about bringing the data in context the context that is relevant and understandable for different stakeholders. Whether we're talking about an operator developed 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. So I think one of the best examples I have is if you start to be able to align business k p i. Whether you are accounting, you know, with sales per hour or the engagement of your users on your mobile application, whatever it is, if you start to connect that k p I business K p I to the key piece that developers might be looking at, whether it is now the number of defects or velocity or whatever over metrics that they are used to to actually track, you start to be able to actually contextual eyes in what we are. The affecting, basically metric that that is really relevant. And 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 to to drive engagement, right? So, you know, if you look at zoom, for instance, Zoom giving away, it's service thio education is 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 a limited way. And so you really want to start to rethink? Oh, you connect everybody kind of business objective fruit data. And I always start to get people to stare at the same data from their own lands and collaborating on the data. Right? >>Right. That's good. Uh, Tom, I want to go back to you. You've been studying I t for a long time writing lots of books and and getting into it. Um, Why now? You know what? Why now? Are we finally aligning business objectives with objects? 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 with the biz ops. >>Well, in much of the past, I t waas sort of a back office related activity. You know, it was important for, um, 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 of data business. A digital business. The anti 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. And even if you're in a new industry that hasn't historically been terribly, um, technology oriented customer expectations flow from, you know, the digital native 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 I T projects or building things that don't really work for the business. Um, it's mission critical that we do that well, almost every time, >>right. And I just I just wanna fall by that time, in terms of the you've talked extensively about kind of these evolutions of data analytics, from artisanal stage to the big data stage, the data economy stage the ai driven stage. What I find interesting about all the stages you always put a start date. You never put it in date. Um, so you know, is the is the big data. I'm just gonna use that generically moment in time. Finally, here. Where were, you know, off mahogany row with the data scientists, But actually could 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 seem to go away. The three artisanal stuff is still being done, but we would like for less and less of it to be artisanal. We can't really afford for everything to be artisanal anymore. It's too labor and time consuming to do things that way. So we shift Mawr and Mawr of it to be done through automation and be to be done with a higher level of productivity. And, um, you know, at some point maybe we we reached the stage where we don't do anything artisanal e anymore. I'm not sure we're there yet, but, you know, we are We are making progress, >>right? Right. And make back to you in terms of looking at agile because you're you're such a student of agile. When when you look at the opportunity with biz 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 surgeon Tom hit on this. Is that in agile? What's happened is that we've been, you know, measuring tiny subsets of the value stream, right? We need to elevate the data's there, developers air working on these tools of delivering features. The foundations for for great culture are there. I spent two decades as a developer, and when I was really happy when I was able to deliver value to customers, the quicker is able to do that. The fewer impediments are in my way, the quicker was deployed and running the cloud, the happier I waas and that's exactly what's happening if we could just get the right data 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 and delivering value to customers. None of these legacies that Tom touched on, which has cost center metrics from a nightie, came from where for I t being a cost center and something that provided email on back office systems. So we need thio rapidly shift to those new, meaningful metrics, their customer and business centric. And make sure that every development organization is focused on those as well as the business itself that we're measuring value. And they were helping that value flow without interruption. >>I love that because 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, thank you again for for your time. Uh, congratulations on the on the unveil of the biz ops manifesto and bringing together this coalition of 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 resource is where you're not gonna get the r. O. I. So, uh, congratulations again. And thank you for sharing your thoughts with us here on the Cube. Thank >>you. All >>right, So we have surged. Tom and Mick. I'm Jeff. You're watching the Cube. It's a biz ops manifesto unveiled. Thanks for watching. We'll see you next time. Yeah,

>> Announcer: From around the globe. It's theCUBE. With digital coverage of BizOps Manifesto Unveiled. Brought to you by BizOps Coalition. >> Hey, welcome back everybody ,Jeff Frick here with theCUBE. Welcome back to our ongoing coverage of the BizOps Manifesto Unveiled. 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. And joining us again, we've had them all on individually, now we're going to have a great power panel. First up, we're going to have Mik Kersten returning. He's the founder and CEO of Tasktop. Mik, good to see you again. Where are you dialing in from? >> Great to see you again, Jeff. I'm dialing from Vancouver, Canada. >> Vancouver, Canada. One of my favorite cities in the whole wide world. Also we've got Tom Davenport, coming 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. >> From Massachusetts, Cape Cod. >> Nice, great to see you again. And also joining Serge Lucio. He is the VP and General Manager Enterprise Software Division at Broadcom. Serge, great to see you again, where are you coming in from? >> 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. BizOps Manifesto, what was the initial reason to do this? And how did you decide to do it in a kind of a coalition, way bringing together a group of people versus just making it an internal company initiative that you know, you can do better stuff within your own company? Serge, why don't we start with you? >> Yeah, so I think we were at a really critical juncture, right. Many large enterprises are basically struggling with their digital transformation. In fact, many recognized that the business (indistinct) collaboration has been one of the major impediments to drive that kind of transformation. And if we look at the industry today, many people are, whether we're talking about vendors or system decorators, 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 as part of the coalition and formalizing, basically the core principles and values in a BizOps Manifesto, we can really start to kind of 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. So whether it is technology or services or training, I think that's really the value of bringing all of these players together. >> Great. And Mik to you. Why did you get involved in this effort? >> So I've been 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 Serge has noted, 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 that quickly and then 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 that 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. 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 BizOps Manifesto provides. >> Right, great And Tom to you, you've been covering tech for a very 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 sign onto this manifesto. >> Sure. Well, I have, you know, for the past 15 or 20 years, I've been focusing on Data 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 DevOps or MLops, any of these kind of ops oriented movements. We're making individual project performance and productivity better but we're not changing the business effectively enough. And that's the thing that appealed to me about the BizOps 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. >> That's great. Serge 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 COVID hit and it was instant light switch. Everyone's working from home, you've got a lot more reliance on your digital tools, digital communication, both within your customer base and your partner base but also then your employees. One of you can 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 and you really have to prioritize and get it right. >> Yeah. Maybe I'll just start by quoting Satina Nello, basically recently said that there's been two years of digital transformation just last two months. And in any many ways that's true. But yet when we look at large enterprises, they're still struggling with a 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? About 40% of the personal loans today, are being originated by fintechs of a like of Sophie or LendingClub, right? Not to traditional brick and mortar for a bank. And so the, well, there is kind of a much more of an appetite and it's a more of a survival type of driver these days. The reality is that in order for these large enterprises to truly transform and engage on this digital transformation they need to start to really align the business in IT. You know, in many ways and make cover that agile really emerge from the core desire to truly improve software predictability which we've really missed is all that 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 discuss inward metrics that's, IT is typically being using to business outcomes. We think we can start to really help different stakeholders within the organization to collaborate. So I think there is more than ever. There's an imperative to acts now and resolves I think is kind of the right approach to drive that kind of transformation. >> Great. I want to follow up on the culture comment 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 realized that to be successful with any kind of digital transformation you have to change people's behaviors and attitudes. 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 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 cultural, behavioral dimension and not just assuming that it will happen if we build system. You know, if we build it, they won't necessarily come. >> Right. So I want to go to you Nick. 'Cause you know, we're talking about workflows and flow and, and you've written about flow both in terms of, 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 wiggle room in tough times, but you also talked about flow from the culture side and the people side. So, I wanted 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 their end flow 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 BizOps 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 Christensen 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 game console 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 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 look at the prioritization and make sure they're prioritizing on the right thing is make just said what are you optimizing for? >> Oh yeah, 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 you know, it's a difficult aspect to the decision to frame it correctly in the first place. 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, it's very difficult for the 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, it's worth that extra time to think carefully about how the decision has been structured. >> Right. Serge, I want to go back to you and talk about the human factors, because as we've just discussed, you could 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 core values of the Bezos Manifesto, you know, a big one is trust and collaboration, you know, learn, respond and pivot. One of you can share your thoughts on trying to get that cultural shift 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 position. >> So I think, at the ground level, it truly starts with the realization that we're all different. We come from different backgrounds. Often times we tend to blame the data. It's not uncommon my experiments that we spend the first you know 30 minutes of any kind of one hour conversation to debate the validity of the data. And so one of the first kind of probably manifestations that we've had or revelations as we start to engage with our customers is like just exposing 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 we think about kind of the types of changes that we're trying to truly effect around data driven decision making it's all about bringing the data in context, the context that is relevant and understandable for different stakeholders, whether we're talking about an operator or a developer or a business analyst. So 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 KPI to 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 actually track. You start 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 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 to drive engagements, right? So if you look at zoom for instance, zoom giving away it's service to education, is 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 through 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, great That's a good. 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. Why now, you know, what why now (laughs) are we finally aligning business objectives 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 move with the BizOps? >> Well, much of a past, IT was sort of a back office related activity. And, you know, it was important for producing your pay check and capturing the customer orders but the business wasn't built around it. Now, every organization needs to be a software business 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, and even if you're you know, an industry that hasn't historically been terribly technology oriented customer expectations flow from, you know, the digital native 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. It's mission critical that we do that well almost every time. >> Right. And 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 artisanal 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. So, you know, is the big data I'm just going to use that generically 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 artisanal stuff is still being done but we would like for less and lesser of it to be artisanal, we can't really afford for everything to be artisanal 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 to be done with a higher level of productivity. And, 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 making progress. >> Right And Mick, back to you in terms of looking at agile 'cause you're such a student of agile, when you look at the opportunity with BizOps 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 Serge and Tom hit on this is that in agile what's happened is that we've been you know 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 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 the 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 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 IT, 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 developer the organization is focused on those as well as the business itself, that we're measuring value and we're helping that value flow without interruptions. >> I love that Mik 'cause if you don't measure it, you can't improve on it but you got to be measuring the right thing. So gentlemen, thank you again for your time. Congratulations on the unveil of the BizOps Manifesto and bringing together this coalition of 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 congratulations again. And thank you for sharing your thoughts with us here on theCUBE. >> Thank you. >> Thank you from Vancouver. >> Alright, so we had Serge, Tom and Mik. I'm Jeff, you're watching theCUBE. It's a BizOps Manifesto Unveiled. Thanks for watching. We'll see you next time. (soft music)