(upbeat music) >> Welcome back, everyone, to theCUBE's coverage here live on the floor at AWS re:MARS 2022. I'm John Furrier, host for theCUBE. Great event, machine learning, automation, robotics, space, that's MARS. It's part of the re-series of events, re:Invent's the big event at the end of the year, re:Inforce, security, re:MARS, really intersection of the future of space, industrial, automation, which is very heavily DevOps machine learning, of course, machine learning, which is AI. We have Luis Ceze here, who's the CEO co-founder of OctoML. Welcome to theCUBE. >> Thank you very much for having me in the show, John. >> So we've been following you guys. You guys are a growing startup funded by Madrona Venture Capital, one of your backers. You guys are here at the show. This is a, I would say small show relative what it's going to be, but a lot of robotics, a lot of space, a lot of industrial kind of edge, but machine learning is the centerpiece of this trend. You guys are in the middle of it. Tell us your story. >> Absolutely, yeah. So our mission is to make machine learning sustainable and accessible to everyone. So I say sustainable because it means we're going to make it faster and more efficient. You know, use less human effort, and accessible to everyone, accessible to as many developers as possible, and also accessible in any device. So, we started from an open source project that began at University of Washington, where I'm a professor there. And several of the co-founders were PhD students there. We started with this open source project called Apache TVM that had actually contributions and collaborations from Amazon and a bunch of other big tech companies. And that allows you to get a machine learning model and run on any hardware, like run on CPUs, GPUs, various GPUs, accelerators, and so on. It was the kernel of our company and the project's been around for about six years or so. Company is about three years old. And we grew from Apache TVM into a whole platform that essentially supports any model on any hardware cloud and edge. >> So is the thesis that, when it first started, that you want to be agnostic on platform? >> Agnostic on hardware, that's right. >> Hardware, hardware. >> Yeah. >> What was it like back then? What kind of hardware were you talking about back then? Cause a lot's changed, certainly on the silicon side. >> Luis: Absolutely, yeah. >> So take me through the journey, 'cause I could see the progression. I'm connecting the dots here. >> So once upon a time, yeah, no... (both chuckling) >> I walked in the snow with my bare feet. >> You have to be careful because if you wake up the professor in me, then you're going to be here for two hours, you know. >> Fast forward. >> The average version here is that, clearly machine learning has shown to actually solve real interesting, high value problems. And where machine learning runs in the end, it becomes code that runs on different hardware, right? And when we started Apache TVM, which stands for tensor virtual machine, at that time it was just beginning to start using GPUs for machine learning, we already saw that, with a bunch of machine learning models popping up and CPUs and GPU's starting to be used for machine learning, it was clear that it come opportunity to run on everywhere. >> And GPU's were coming fast. >> GPUs were coming and huge diversity of CPUs, of GPU's and accelerators now, and the ecosystem and the system software that maps models to hardware is still very fragmented today. So hardware vendors have their own specific stacks. So Nvidia has its own software stack, and so does Intel, AMD. And honestly, I mean, I hope I'm not being, you know, too controversial here to say that it kind of of looks like the mainframe era. We had tight coupling between hardware and software. You know, if you bought IBM hardware, you had to buy IBM OS and IBM database, IBM applications, it all tightly coupled. And if you want to use IBM software, you had to buy IBM hardware. So that's kind of like what machine learning systems look like today. If you buy a certain big name GPU, you've got to use their software. Even if you use their software, which is pretty good, you have to buy their GPUs, right? So, but you know, we wanted to help peel away the model and the software infrastructure from the hardware to give people choice, ability to run the models where it best suit them. Right? So that includes picking the best instance in the cloud, that's going to give you the right, you know, cost properties, performance properties, or might want to run it on the edge. You might run it on an accelerator. >> What year was that roughly, when you were going this? >> We started that project in 2015, 2016 >> Yeah. So that was pre-conventional wisdom. I think TensorFlow wasn't even around yet. >> Luis: No, it wasn't. >> It was, I'm thinking like 2017 or so. >> Luis: Right. So that was the beginning of, okay, this is opportunity. AWS, I don't think they had released some of the nitro stuff that the Hamilton was working on. So, they were already kind of going that way. It's kind of like converging. >> Luis: Yeah. >> The space was happening, exploding. >> Right. And the way that was dealt with, and to this day, you know, to a large extent as well is by backing machine learning models with a bunch of hardware specific libraries. And we were some of the first ones to say, like, know what, let's take a compilation approach, take a model and compile it to very efficient code for that specific hardware. And what underpins all of that is using machine learning for machine learning code optimization. Right? But it was way back when. We can talk about where we are today. >> No, let's fast forward. >> That's the beginning of the open source project. >> But that was a fundamental belief, worldview there. I mean, you have a world real view that was logical when you compare to the mainframe, but not obvious to the machine learning community. Okay, good call, check. Now let's fast forward, okay. Evolution, we'll go through the speed of the years. More chips are coming, you got GPUs, and seeing what's going on in AWS. Wow! Now it's booming. Now I got unlimited processors, I got silicon on chips, I got, everywhere >> Yeah. And what's interesting is that the ecosystem got even more complex, in fact. Because now you have, there's a cross product between machine learning models, frameworks like TensorFlow, PyTorch, Keras, and like that and so on, and then hardware targets. So how do you navigate that? What we want here, our vision is to say, folks should focus, people should focus on making the machine learning models do what they want to do that solves a value, like solves a problem of high value to them. Right? So another deployment should be completely automatic. Today, it's very, very manual to a large extent. So once you're serious about deploying machine learning model, you got a good understanding where you're going to deploy it, how you're going to deploy it, and then, you know, pick out the right libraries and compilers, and we automated the whole thing in our platform. This is why you see the tagline, the booth is right there, like bringing DevOps agility for machine learning, because our mission is to make that fully transparent. >> Well, I think that, first of all, I use that line here, cause I'm looking at it here on live on camera. People can't see, but it's like, I use it on a couple couple of my interviews because the word agility is very interesting because that's kind of the test on any kind of approach these days. Agility could be, and I talked to the robotics guys, just having their product be more agile. I talked to Pepsi here just before you came on, they had this large scale data environment because they built an architecture, but that fostered agility. So again, this is an architectural concept, it's a systems' view of agility being the output, and removing dependencies, which I think what you guys were trying to do. >> Only part of what we do. Right? So agility means a bunch of things. First, you know-- >> Yeah explain. >> Today it takes a couple months to get a model from, when the model's ready, to production, why not turn that in two hours. Agile, literally, physically agile, in terms of walk off time. Right? And then the other thing is give you flexibility to choose where your model should run. So, in our deployment, between the demo and the platform expansion that we announced yesterday, you know, we give the ability of getting your model and, you know, get it compiled, get it optimized for any instance in the cloud and automatically move it around. Today, that's not the case. You have to pick one instance and that's what you do. And then you might auto scale with that one instance. So we give the agility of actually running and scaling the model the way you want, and the way it gives you the right SLAs. >> Yeah, I think Swami was mentioning that, not specifically that use case for you, but that use case generally, that scale being moving things around, making them faster, not having to do that integration work. >> Scale, and run the models where they need to run. Like some day you want to have a large scale deployment in the cloud. You're going to have models in the edge for various reasons because speed of light is limited. We cannot make lights faster. So, you know, got to have some, that's a physics there you cannot change. There's privacy reasons. You want to keep data locally, not send it around to run the model locally. So anyways, and giving the flexibility. >> Let me jump in real quick. I want to ask this specific question because you made me think of something. So we're just having a data mesh conversation. And one of the comments that's come out of a few of these data as code conversations is data's the product now. So if you can move data to the edge, which everyone's talking about, you know, why move data if you don't have to, but I can move a machine learning algorithm to the edge. Cause it's costly to move data. I can move computer, everyone knows that. But now I can move machine learning to anywhere else and not worry about integrating on the fly. So the model is the code. >> It is the product. >> Yeah. And since you said, the model is the code, okay, now we're talking even more here. So machine learning models today are not treated as code, by the way. So do not have any of the typical properties of code that you can, whenever you write a piece of code, you run a code, you don't know, you don't even think what is a CPU, we don't think where it runs, what kind of CPU it runs, what kind of instance it runs. But with machine learning model, you do. So what we are doing and created this fully transparent automated way of allowing you to treat your machine learning models if you were a regular function that you call and then a function could run anywhere. >> Yeah. >> Right. >> That's why-- >> That's better. >> Bringing DevOps agility-- >> That's better. >> Yeah. And you can use existing-- >> That's better, because I can run it on the Artemis too, in space. >> You could, yeah. >> If they have the hardware. (both laugh) >> And that allows you to run your existing, continue to use your existing DevOps infrastructure and your existing people. >> So I have to ask you, cause since you're a professor, this is like a masterclass on theCube. Thank you for coming on. Professor. (Luis laughing) I'm a hardware guy. I'm building hardware for Boston Dynamics, Spot, the dog, that's the diversity in hardware, it's tends to be purpose driven. I got a spaceship, I'm going to have hardware on there. >> Luis: Right. >> It's generally viewed in the community here, that everyone I talk to and other communities, open source is going to drive all software. That's a check. But the scale and integration is super important. And they're also recognizing that hardware is really about the software. And they even said on stage, here. Hardware is not about the hardware, it's about the software. So if you believe that to be true, then your model checks all the boxes. Are people getting this? >> I think they're starting to. Here is why, right. A lot of companies that were hardware first, that thought about software too late, aren't making it. Right? There's a large number of hardware companies, AI chip companies that aren't making it. Probably some of them that won't make it, unfortunately just because they started thinking about software too late. I'm so glad to see a lot of the early, I hope I'm not just doing our own horn here, but Apache TVM, the infrastructure that we built to map models to different hardware, it's very flexible. So we see a lot of emerging chip companies like SiMa.ai's been doing fantastic work, and they use Apache TVM to map algorithms to their hardware. And there's a bunch of others that are also using Apache TVM. That's because you have, you know, an opening infrastructure that keeps it up to date with all the machine learning frameworks and models and allows you to extend to the chips that you want. So these companies pay attention that early, gives them a much higher fighting chance, I'd say. >> Well, first of all, not only are you backable by the VCs cause you have pedigree, you're a professor, you're smart, and you get good recruiting-- >> Luis: I don't know about the smart part. >> And you get good recruiting for PhDs out of University of Washington, which is not too shabby computer science department. But they want to make money. The VCs want to make money. >> Right. >> So you have to make money. So what's the pitch? What's the business model? >> Yeah. Absolutely. >> Share us what you're thinking there. >> Yeah. The value of using our solution is shorter time to value for your model from months to hours. Second, you shrink operator, op-packs, because you don't need a specialized expensive team. Talk about expensive, expensive engineers who can understand machine learning hardware and software engineering to deploy models. You don't need those teams if you use this automated solution, right? Then you reduce that. And also, in the process of actually getting a model and getting specialized to the hardware, making hardware aware, we're talking about a very significant performance improvement that leads to lower cost of deployment in the cloud. We're talking about very significant reduction in costs in cloud deployment. And also enabling new applications on the edge that weren't possible before. It creates, you know, latent value opportunities. Right? So, that's the high level value pitch. But how do we make money? Well, we charge for access to the platform. Right? >> Usage. Consumption. >> Yeah, and value based. Yeah, so it's consumption and value based. So depends on the scale of the deployment. If you're going to deploy machine learning model at a larger scale, chances are that it produces a lot of value. So then we'll capture some of that value in our pricing scale. >> So, you have direct sales force then to work those deals. >> Exactly. >> Got it. How many customers do you have? Just curious. >> So we started, the SaaS platform just launched now. So we started onboarding customers. We've been building this for a while. We have a bunch of, you know, partners that we can talk about openly, like, you know, revenue generating partners, that's fair to say. We work closely with Qualcomm to enable Snapdragon on TVM and hence our platform. We're close with AMD as well, enabling AMD hardware on the platform. We've been working closely with two hyperscaler cloud providers that-- >> I wonder who they are. >> I don't know who they are, right. >> Both start with the letter A. >> And they're both here, right. What is that? >> They both start with the letter A. >> Oh, that's right. >> I won't give it away. (laughing) >> Don't give it away. >> One has three, one has four. (both laugh) >> I'm guessing, by the way. >> Then we have customers in the, actually, early customers have been using the platform from the beginning in the consumer electronics space, in Japan, you know, self driving car technology, as well. As well as some AI first companies that actually, whose core value, the core business come from AI models. >> So, serious, serious customers. They got deep tech chops. They're integrating, they see this as a strategic part of their architecture. >> That's what I call AI native, exactly. But now there's, we have several enterprise customers in line now, we've been talking to. Of course, because now we launched the platform, now we started onboarding and exploring how we're going to serve it to these customers. But it's pretty clear that our technology can solve a lot of other pain points right now. And we're going to work with them as early customers to go and refine them. >> So, do you sell to the little guys, like us? Will we be customers if we wanted to be? >> You could, absolutely, yeah. >> What we have to do, have machine learning folks on staff? >> So, here's what you're going to have to do. Since you can see the booth, others can't. No, but they can certainly, you can try our demo. >> OctoML. >> And you should look at the transparent AI app that's compiled and optimized with our flow, and deployed and built with our flow. That allows you to get your image and do style transfer. You know, you can get you and a pineapple and see how you look like with a pineapple texture. >> We got a lot of transcript and video data. >> Right. Yeah. Right, exactly. So, you can use that. Then there's a very clear-- >> But I could use it. You're not blocking me from using it. Everyone's, it's pretty much democratized. >> You can try the demo, and then you can request access to the platform. >> But you get a lot of more serious deeper customers. But you can serve anybody, what you're saying. >> Luis: We can serve anybody, yeah. >> All right, so what's the vision going forward? Let me ask this. When did people start getting the epiphany of removing the machine learning from the hardware? Was it recently, a couple years ago? >> Well, on the research side, we helped start that trend a while ago. I don't need to repeat that. But I think the vision that's important here, I want the audience here to take away is that, there's a lot of progress being made in creating machine learning models. So, there's fantastic tools to deal with training data, and creating the models, and so on. And now there's a bunch of models that can solve real problems there. The question is, how do you very easily integrate that into your intelligent applications? Madrona Venture Group has been very vocal and investing heavily in intelligent applications both and user applications as well as enablers. So we say an enable of that because it's so easy to use our flow to get a model integrated into your application. Now, any regular software developer can integrate that. And that's just the beginning, right? Because, you know, now we have CI/CD integration to keep your models up to date, to continue to integrate, and then there's more downstream support for other features that you normally have in regular software development. >> I've been thinking about this for a long, long, time. And I think this whole code, no one thinks about code. Like, I write code, I'm deploying it. I think this idea of machine learning as code independent of other dependencies is really amazing. It's so obvious now that you say it. What's the choices now? Let's just say that, I buy it, I love it, I'm using it. Now what do I got to do if I want to deploy it? Do I have to pick processors? Are there verified platforms that you support? Is there a short list? Is there every piece of hardware? >> We actually can help you. I hope we're not saying we can do everything in the world here, but we can help you with that. So, here's how. When you have them all in the platform you can actually see how this model runs on any instance of any cloud, by the way. So we support all the three major cloud providers. And then you can make decisions. For example, if you care about latency, your model has to run on, at most 50 milliseconds, because you're going to have interactivity. And then, after that, you don't care if it's faster. All you care is that, is it going to run cheap enough. So we can help you navigate. And also going to make it automatic. >> It's like tire kicking in the dealer showroom. >> Right. >> You can test everything out, you can see the simulation. Are they simulations, or are they real tests? >> Oh, no, we run all in real hardware. So, we have, as I said, we support any instances of any of the major clouds. We actually run on the cloud. But we also support a select number of edge devices today, like ARMs and Nvidia Jetsons. And we have the OctoML cloud, which is a bunch of racks with a bunch Raspberry Pis and Nvidia Jetsons, and very soon, a bunch of mobile phones there too that can actually run the real hardware, and validate it, and test it out, so you can see that your model runs performant and economically enough in the cloud. And it can run on the edge devices-- >> You're a machine learning as a service. Would that be an accurate? >> That's part of it, because we're not doing the machine learning model itself. You come with a model and we make it deployable and make it ready to deploy. So, here's why it's important. Let me try. There's a large number of really interesting companies that do API models, as in API as a service. You have an NLP model, you have computer vision models, where you call an API and then point in the cloud. You send an image and you got a description, for example. But it is using a third party. Now, if you want to have your model on your infrastructure but having the same convenience as an API you can use our service. So, today, chances are that, if you have a model that you know that you want to do, there might not be an API for it, we actually automatically create the API for you. >> Okay, so that's why I get the DevOps agility for machine learning is a better description. Cause it's not, you're not providing the service. You're providing the service of deploying it like DevOps infrastructure as code. You're now ML as code. >> It's your model, your API, your infrastructure, but all of the convenience of having it ready to go, fully automatic, hands off. >> Cause I think what's interesting about this is that it brings the craftsmanship back to machine learning. Cause it's a craft. I mean, let's face it. >> Yeah. I want human brains, which are very precious resources, to focus on building those models, that is going to solve business problems. I don't want these very smart human brains figuring out how to scrub this into actually getting run the right way. This should be automatic. That's why we use machine learning, for machine learning to solve that. >> Here's an idea for you. We should write a book called, The Lean Machine Learning. Cause the lean startup was all about DevOps. >> Luis: We call machine leaning. No, that's not it going to work. (laughs) >> Remember when iteration was the big mantra. Oh, yeah, iterate. You know, that was from DevOps. >> Yeah, that's right. >> This code allowed for standing up stuff fast, double down, we all know the history, what it turned out. That was a good value for developers. >> I could really agree. If you don't mind me building on that point. You know, something we see as OctoML, but we also see at Madrona as well. Seeing that there's a trend towards best in breed for each one of the stages of getting a model deployed. From the data aspect of creating the data, and then to the model creation aspect, to the model deployment, and even model monitoring. Right? We develop integrations with all the major pieces of the ecosystem, such that you can integrate, say with model monitoring to go and monitor how a model is doing. Just like you monitor how code is doing in deployment in the cloud. >> It's evolution. I think it's a great step. And again, I love the analogy to the mainstream. I lived during those days. I remember the monolithic propriety, and then, you know, OSI model kind of blew it. But that OSI stack never went full stack, and it only stopped at TCP/IP. So, I think the same thing's going on here. You see some scalability around it to try to uncouple it, free it. >> Absolutely. And sustainability and accessibility to make it run faster and make it run on any deice that you want by any developer. So, that's the tagline. >> Luis Ceze, thanks for coming on. Professor. >> Thank you. >> I didn't know you were a professor. That's great to have you on. It was a masterclass in DevOps agility for machine learning. Thanks for coming on. Appreciate it. >> Thank you very much. Thank you. >> Congratulations, again. All right. OctoML here on theCube. Really important. Uncoupling the machine learning from the hardware specifically. That's only going to make space faster and safer, and more reliable. And that's where the whole theme of re:MARS is. Let's see how they fit in. I'm John for theCube. Thanks for watching. More coverage after this short break. >> Luis: Thank you. (gentle music)

>> (Announcer) From the Bellagio hotel in Las Vegas. It's theCube covering UiPath FORWARD IV, brought to you by UiPath. >> Good afternoon. Welcome back to theCube's live coverage of UiPath FORWARD IV. Lisa Martin here with Dave Vellante. We're on day two of our coverage. We've been talking a lot about automation, all of the opportunities that it's uncovering across industries. We're now going to be talking about a big company undergoing its own automation-led digital transformation. Joining us next, Mariesa Coughanour, head of Automation Advisory Services at Cognizant. Mariesa, welcome to the program. >> Thank you for having me. I'm excited to be here today. >> So let's talk. So Cognizant is a part, both a partner and a customer of UiPath. >> Yes. >> We're going to talk about you in the customer realm today. Cognizant is undergoing its own automation-led digital transformation. Let's talk about that. Talk to me about some of the business outcomes that are, that you're expecting, how it's going to transform the employee experience, the customer experience. >> (Mariesa) Sure, absolutely. We actually started working with automation ourselves back in 2018, where we just put in a CoE, we said we want to drive it into our business operations. But about a year ago, we said, let's go further. I really wanted to play with all of our employees. We wanted to empower them. We talk about citizen development, of robot for every person. And we know that that's really the future. That's where we're going. We're digitally transforming our organizations. And so what we did is we sat down and we worked really closely with UiPath on how do we do this? What kind of training do we need? We're going to need some process, some governance in there. And so we put that in place and, you know, we said, let's get this going this year. So we went out, we did, our first Hackathon, went really well. It was Bring Your Own Bots. So BYOB, so, fun themes. And we got some good savings. We actually drove over 10,000, close to 20,000 hours back into the organization. And we said after that, let's go a bit bigger though. And we did what's called Game of Bots. So obviously we know where that came from, right? And we said, we're going to go a little bit longer and we want to go bigger. So we went and had 2,500 people participate over eight weeks. We built over a thousand bots. And guess what? We drove over 200,000 hours back into the organization in just eight weeks. So super big success story. People loved it. Our teams were excited. We recognized over 200 people out of that with team awards, who submitted the most ideas. And even our top leadership said, let's do a presentation. So the guys and gals who had the top, biggest impact automations got to meet with our top senior leaders and present out to them. It's been awesome. And now we're starting to move that force. We're scaling bigger. We're actually going pretty big in Cognizant. We have some big goals right now. >> That's a gob of hours. Game of Bots, get it? GOB. >> (laughs) >> Come on, with me. >> It is a gob of hours. >> How do you measure the hours? Is it a back of napkin kind of thing? We ask people, Hey, how much, how what, how do you actually measure it? >> No, we actually track it. We could see how many hours people were doing a certain tasks and things that they do every day, whether they're running reports, submitting claims for a customer. And so we're able to see that that time is actually going down. We're faster. We get better quality. People were also able to get hours back in their day so they could do more value added work in the organization. So we actually do track it. And we're able to really measure those tangible outcomes for the teams. >> Sounds like you guys have been moving pretty quickly on this. >> We are. >> So the appetite at Cognizant was there, the culture was there to embrace it. Those are probably, I imagine, two big facilitators of being able to move at the speed and the scale, >> Yeah >> that, with what you're doing. >> Culture was there. We're really digitally savvy. I would say we're digital at heart in Cognizant. We are, we're really a tech company and we really focus on how to be at the forefront of all things when it comes to technology. But we said, we also want to transform how we work. So starting to shift the conversation from, you know, do you want to automate, to why not? How do we actually start talking about, you know, I have this to do list, but you know what, actually, we can improve if we did some of this other stuff instead. So let's free up that time, but use automation there and we can actually grow things. We can add more value. We do all that stuff on your to-do list that I think everybody has and they want to get to, but you get caught up in your day-to-day job all the time. So we're actually getting people to be more excited about and have a real voice. And I actually think that's important. Is that, it's not just about giving people the tool, it's about shifting our culture to really embrace digital, embrace this technology, because we're trying to transform how we all work. And we want to lead by example. >> So we talk about BPO. Business Process Optimization, right? It was kind of the buzz word of the '90s and early 2000s. A lot of times it meant putting in SAP. (chuckles) >> (Mariesa) (laughs) Yeah. >> So that's evolved. And there's some companies that would say, "Hey, we specialize in that," technology companies, obviously, >> (Mariesa) Yep. >> you know, SI's as well. How do you think about the difference between end-to-end enterprise automation and, and sort of traditional BPO? >> I think it has to come together a bit, is one thing. So when you do the BPO, or you do shared services, or you outsource some of the work. We actually put into those contracts, because we do a lot of that for our customers. And we put in automation. The step we took further was we actually started to empower people to actually build the automations themselves, which meant we actually had to work with customers too. So they knew we were doing this. We wanted to make sure they understood, they were comfortable. We put any controls in place that they also needed, to make sure that, you know, we didn't impact any of their services. We want to make it better. We want them to feel nothing but bigger, better results in outcomes. And then as you think about the enterprise side, we have to compliment, because a lot of those processes do feed back into how you run a business. And so we focus on how do you bring both of those stories together so that you're driving synergies across the board. And actually some good lessons learned along the way because some of this stuff becomes reusable. You have best practices you could share across the board. And we want to make sure that we are connecting the dots from the shared services BPO work, back into the enterprise because really a process is end to end, an organization. And we want to help people think that way and also get the results that way too. >> Is that end to end automation, at enterprise automation, more tech heavy, or, or maybe it's tech light in a way, whereas BPO is maybe a lot more, sort of, lean thinking, a lot more chalkboard. Are we deep into the, so I, sometimes, you're saying they have to come together. >> They do yeah. >> But from, from where I guess is, is what I'm trying to better understand. >> So I would think about it this way. When you think about a process, right, from when you even placed an order, the whole way through when you fulfill it for a customer. There's work that we, we do outsource all the time, right? So maybe it's the, the PO process, some of the order transactions from the payment, but you also have the pieces is actually touching the customer, too. You have the pieces that are fulfilling the order. So we say end to end, that is really thinking about that beginning, from a conversation with the customer, the whole way to when we're delivering. And I do think there's a lot of technology. That is something I think everyone gravitates to because there is a lot. Especially if you're going to go end to end, you have to be able to take in documents. You have automation. You're not going to know all the rules, no matter how many times you ask, you're going to need machine learning to be able to help figure it out and get smarter as what, as you go along the way. But as you're putting this into place, what's important is: as you're thinking about, kind of, transforming that business so that they're feeling the results the whole way through, because if you just focus on one, you might create a bottleneck, right? You might've got super fast, but the guy who's going to get the work from you, they're going to feel like, oh my goodness, there's all this work on my plate. So we really want to make sure that we create that seamless experience for everyone across the board, as we put it in. >> And how does UiPath, help facilitate that? >> Across the board, I mean, we were sitting down, we were laying out our program. 'Cause we're actually trying to get to 60,000 strong. So we have 7,000 trained today. We're going to get to 60,000. That's our plan. So we're working very closely with UiPath on what does that training that you need to have in place? What's that model? How do we get people comfortable? Because one thing you'll find is not everyone's in the same spot. Some are going to jump in, dive right in, give me the tool. I want to build. I love this. Others might need a little bit more confidence boost. They might need more handholding. And I think that's really important. And it's probably the one thing I would add too, as you do talk a lot about the technologies, we put it in, but it's the people at the end of the day, it's how you help them adopt, feel comfortable with this technology and really embrace it. That's really going to be the difference on whether, how fast you get down that line for transformation. >> Is it a classic bell curve? You got your 10% early adopters, you got a big fat middle, and then you've got some laggards who come along. >> It kind of is. And I think what's important is that middle is all up in how you do it because 10% are always going to love it. You're always going to have a few people, they're a little extra nervous maybe. But in the middle, if you really think about it, and you're able to put in that culture, you're able to put in your leadership is engaged. You're putting us in gamification, make it fun. That's what we found is, if we got people really having fun up front with it, it gives people a reason to be a part of it. And also, why don't we let people partner up? We can give them the technology, but if someone's not as comfortable, let us do teams. Let's meet people where they're at and then move them along this journey. And let's try to accelerate the best we can. >> How did you gamify it? Crypto. No. (chuckles) >> (laughs) >> (laughs) No, no crypto. But I will say we have some really cool prizes and people were super excited to get to do the presentations because they got to show their, their bots live, their creations, to the team. And I think that was important. Not everyone always is able to capture all the results, but we wanted to actually talk about like, what were the ideas, share it across the board. Cause it also generated ideas. because what you'll find is, when you hear something like, you know what, that's kind of what I do. Wonder if I could do some automation too. At least submit an idea, and then, maybe they're moving down the line, they're getting their hands on the technology. And I think that's how we all push the needle forward and move this along faster. >> One of the most important things about automation is letting people be able to move away from the mundane, the repetitive tasks, that they probably don't enjoy. And being able to focus more on their core competencies or more strategic initiatives that really make them more relevant to themselves and to their company. And it sounds like you guys have achieved that pretty quickly and, and you have an aggressive plan >> (chuckles) We do. >> to go from 7,000 to 60,000. >> Yes. And that's really the power of automation, if you think about it. We all have things in our job we don't like to do. I don't know about you guys, but there's things that I'm like, oh man, like, can we please automate this? Expense reports, for example. All about automated expense reports. (laughs) But it's really about freeing people up. Think about it. These people went to school, they often have degrees and things, and they do get caught in a lot of the manual things, downloading reports, consolidating data, you know, submitting spreadsheets and forms. Imagine if we're able to make that easier for people, we give them what they need to do their job. So that all that stuff you would like to do, that you know would improve things. You know would make the company better. The culture better. Heck, maybe it's a new product that people know would be really awesome to go build, but everyone feels like they're so busy. They don't have the time to do it. I mean, that's one of the big values of automation. Is this value creation conversation that you get to have with people. And you get to start asking 'why not' a little bit more. >> You've mentioned a couple of times the IDC presentation this morning. And we were talking about earlier, and the pie chart of, of, of value benefits was cost savings, which was very large, new revenue, which was very large. And then I think 15% was quality improvements. And that, I think that's an underappreciated slice of the pie. Somebody, I think years ago, of the UiPath FORWARD said to me, I can very inexpensively apply Six Sigma to business process. >> (Mariesa) Yeah. >> And I could never afford to do that before RPA. And, and so I wonder if you could talk to the quality impacts that you're seeing. >> Absolutely. I actually spent a lot of time in Lean Six Sigma in my early career days. And one of the things about it too, is when you're doing automation, we actually asked that question upfront, can we just simplify, can we just stop doing this? Because you don't want to automate a bad process either. So you want to ask some of those questions. >> (Dave) Yeah. >> But you're spot on. There's a ton of quality benefits that you get from automation. And one of the things I've actually seen is if you focus on some of the quality upfront, process gets better. Get better impact, as when you get faster. If you have better quality, and get faster, you also get your cost out targets. And I, that really matters because quality also, beyond being able to drive the cost out, it also helps a lot with the experience that people face. Customers are frustrated if they have poor quality, something doesn't work the way it's supposed to, a site's not working the way it should. And also even employees, they go, how many times, if you try to do something and you try to follow a process and something's hung up or who knows what happened, right. It's frustrating. So if you're able to improve the quality in the process, not only do you get the cost savings, but you get these, it's softer tan, there's still tangible experiences that get better and actually motivates people to want to do more. >> And those motivated people are probably dealing with customers much, much better. >> Yes, yeah. >> I mean, it's, I always think the employee experience is so, is, is a critical component. >> It is. >> But the customer experience. So how has the customer experience improved at Cognizant as a result of building in automation and enabling all these people? >> Yeah, they're loving the results because we're giving them back efficiencies in their process immediately by putting this automation in. These are quick impacts they're feeling and we're able to do more for them as well. So we're actually having conversations now on how do we drive more efficiencies for you and also, you know, how can we do more? Is there more volume of work? Is there more we could be doing to add value back to your organization? And that's what you want to talk about with customers is we're able to give you this value. And by the way, we actually did X for you now as well, because we knew you needed it. And we have the capacity to do this for you. So it's a really positive conversation, but we did have to upfront talk to them about it, to make sure that we, everyone was on board. They're comfortable. And we're continuing to have those conversations because you know, sometimes you're in a regulated business and we did put a little extra control in. Absolutely okay. But we want to be able to drive these efficiencies back for them. So they feel it in their own operations internally too. And it hits their bottom line and oftentimes helps their employees too, because we interact with them. So those downstream benefits and sometimes even upstream get some nice returns there as well. >> We've heard from, well, we're going to have Daniel on soon. He's the CEO. We've of course heard from CFOs. We've, that's kind of one of the main springs of RPA in the early days. We've heard a lot more CIOs at this event and we have a CTO coming on later. Are these C suite executives totally aligned in their objectives? Do they have they have different agendas? What are you seeing in terms of serving the C suite? >> Yeah. They're all going to have a little bit different agendas, right? Cause that's, their roles have different objectives, but they all align back to the strategy, obviously, for their company. But they're going to have portions of it that they're trying to drive and deliver. What we do see is that there's still some merging that needs to happen between the operations, the more business focused side and the more technical side. But we do, we're starting to see that convergence happen. Because what happens is, is that, you have these technologists, who really are going to have to help move you forward. We're, you know, we're applying AI, ML. Very technical technologies, and we want to make sure we do it right, that we put the right governance in. And we think about the security that we have to have in place for this too. And but we also have the business outcomes and coming together is where you really see the results. If you look at all of those that have reached true maturity, it's where you see these agendas aligning a bit more because you also have to shift the culture too. And it's a collaboration point. You need to be able to have the tech savvy folks. It helps bring them along this journey, but you also have to have the business depth as because you're looking at a process and you're going really deep into it to apply the technology. So it's when people partner is when we really see the results become more exponential. >> So digital transformation, you know, we hear that term a lot. And automation-led digital transformation. >> Yep. >> I hear a lot of data led digital transformations are those parallel tracks, or they can talk a lot about convergence. >> Yeah. >> Are they? I mean, they're not competing. They're obviously very much related. How do you see the data agenda and the automation agenda coming together. >> They have to. Because you really need good quality data to be able to enable your automation at the end of the day. And, but they actually play nicely together. You can actually use automation to help go back and improve your master data management too, which is the core of your information because that's actually where a lot of the struggle sometimes comes, is in the quality of the data that everyone has to work with. So you see the data agenda working on, "How do I clean this? How do I get more insightful, predictful information?" And then from an automation standpoint, how do I then use that to go take action? So all we see is you bring it together, to be able to identify where do you need to get in the process? How do I get the right information? So the automation also is proven data behind it, that we drove the outcomes, because that's where you take it to the bank at the end of the day. Is that you see it in the data itself. But I think one of the things I've seen with automation that helps drive the digital transformation conversation is, the business and IT teams are coming together and having a joint conversation now. People are excited. They're understanding it. I think that's why people jumped on with RPA so quickly, was because they're like, I get this, this is rule-based, this is my business process. I just tell it what to do. I'll take that. I want to do that. And so people got excited about that. And then they said, let's do more. How do I make it more intelligent? How do I help it do things in my process that it's harder for me to explain because there's just so much information here. There's so many nuances. Well, we have the technology can help make it more intelligent, smarter, and learn, so that we're able to drive that back into the business itself to transform. >> You mentioned Master Data Management is, is the data agenda as it relates to automation, primarily reporting, is it moving? Is it transcending reporting into the building of data products, for example, data services that can be monetized either within Cognizant or in your customer base? >> So it's really evolving. I would say some start with reports. That's easy. That's where we'll start, but I'll just kind of give you maybe a little example. So we have a customer and we work with them. So they have customers where they need to, when they call in, the sales folks and the contact centers, they have to upsell. So they work with a lot of different restaurants and different, maybe, bars and, you know, different companies that have different type of like beverages and things like that. So we worked with them to show, how are they performing today with all their sales reps? And then we started to use some automation to be able to get them more helpful information the moment the customer's calling in. And we also did some semantic analysis on a voice, how people were, how were they sounding? How was their tone? Were they happy? Were they upset? Were they sad during the call? And we fed that information back to those teams, back to those managers, and went back even to their training programs. What they actually saw was a ton of top line growth. They saw all of their metrics starting to get better, and they also start to get more predictive on ways that they can use more data to drive the support for those teams and their customers. Like for example, if you know holidays are coming up or a certain time of year with weather, we're able to actually put that type of information in and helps those sales reps better serve their customers. >> Last question, some of the announcements that came out yesterday and some of the news today about UiPath, what excites you about the technology and how it's going to continue to enable you to, to foster this new culture that you've shifted? >> I think, so one thing about UiPath that we've always loved to be able to partner with them as we're still customer centric. And you see that in every announcement that they're doing, and also they're focused on this true process transformation, intelligent end to end thinking, because I think a lot of times when we've had conversations most get stuck in kind of point solutions. And that's just because people are trying to solve today's problems. But with where UiPath is moving and where we want to move to, is how do we help you to really transform how people work? We know automation is a part of our future. We know it's going to be how we work in the future. And we love about UiPath is to really think about how do we integrate it? How do we make those connections? So we can drive the bigger results, we can make it easier for people to adopt and really embrace it because we need to bring the people along this journey and we need to be able to actually impact our processes too, so we can transform them. So I think that's one thing that's been really exciting is just watching them in general. Involved with the announcements the last couple of days, we really see them continue to push that needle. >> Excellent. Well, Mariesa, thanks for joining us. Talking to us about the automation-led digital transformation at Cognizant. Good luck raising your trained individuals from 7K to 60K. It sounds like the momentum is there. The culture's there. We can't wait to hear what happens next! >> Awesome. Thanks again for having me today. >> Our pleasure. >> Good to see you. >> Thank you. >> For Dave Vellante, I'm Lisa Martin live in Las Vegas at the Bellagio. UiPath FORWARD IV is the event we're covering. We'll be right back with our next guest. >> (bubbly outro music)

>>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.

(upbeat music) >> From theCUBE studios in Palo Alto, in Boston, connecting with thought leaders all around the world. This is a Cube conversation. >> Hi everybody, this is Dave Vellante. And as you know, I've been running a CxO series in this COVID economy. And as we go into the post-isolation world, really want to focus and expand our scope and really look at startups. And of course, we're going to look at startups, let's follow the money. And I want to start with the investor. Mark Roberge is here. He's the managing director at Stage 2 capital. He's a professor at the Harvard Business School, former CRO over at HubSpot. Mark, great to see you. Thanks for coming on. >> Yeah, you bet, Dave. Thanks for having me. >> So I love that, you know... looking at your career a little bit, on your LinkedIn and following some of your videos, I love the fact that you did, and now you teach and you're also applying it with Stage 2 Capital. Tell us a little bit more about both of your career and Stage 2. >> Yeah, I mean, a lot of it's a bit serendipitous, especially last 10 years, but I've always had this learn, do, teach framework in my, in mind as I go through the decades of my career, you know, like you're probably like 80% learning in your twenties, early thirties and you know, 20% doing. Then, you know, I think my thirties was like leading the HubSpot sales team, a lot of doing, a little bit of teaching, you know, kind of hopping into different schools, et cetera, and also doing a lot of, some writing. And now like, I'm teaching it. I think investing kind of falls into that too, you know, where you've got this amazing opportunity to meet, the next generation of, of extraordinary entrepreneurs and engage with them. So yeah, that, that has been my career. You know, Dave, I've been a, passionate entrepreneur since 22 and then, the last one I did was HubSpot and that led to just an opportunity to build out one of the first sales teams in a complete inside environment, which opened up the doors for a data driven mindset and all this innovation that led to a book that led to recruitment on HBS's standpoint, to like come and teach that stuff, which was such a humbling honor to pursue. And that led to me a meeting my co-founder, Jay Po, of Stage 2 Capital, who was a customer to essentially start the first VC fund, running back by sales and marketing leaders, which was his vision. But when he proposed it to me, addressed a pretty sizeable void, that I saw, in the entrepreneur ecosystem that I thought could make a substantial impact to the success rate of startups. >> Great, I want to talk a little bit about how you guys compete and what's different there, but you know, I've read some of your work, looked at some of your videos, and we can bring that into the conversation. But I think you've got some real forward-thinking for example, on the, you know, the best path to the upper right. The upper right, being that, that xy-axis on growth and adoption, you know, do you go for hyper-growth or do you go for adoption? How you align sales and marketing, how you compensate salespeople. I think you've got some, some leading-edge thinking on that, that I'd love for you to bring into the conversation, but let's start with Stage 2. I mean, how do you compete with the big guys? What's different about Stage 2 Capital? >> Yeah, I mean, first and foremost, we're a bunch of sales and marketing and execs. I mean, our backing is, a hundred plus CROs, VPs of marketing, CMOs from, from the public companies. I mean, Dropbox, LinkedIn, Oracle, Salesforce, SurveyMonkey, Lyft, Asana, I mean, just pick a unicorn, we probably have some representation from it. So that's, a big part of how we compete, is most of the time, when a rocket ship startup is about to build a sales team, one of our LPs gets a call. And because of that, we get a call, right. And, and so there's, we're just deep in, in helping... So first off, assess the potential and risks of a startup in their current, go to market design, and then really, you know, stepping in, not just with capital, but a lot of know-how in terms of, you know, how to best develop this go-to-market for their particular context. So that's a big part of our differentiation. I don't think we've ever lost a deal that we tried to get into, you know, for that reason, just because we come in at the right stage, that's right for our value prop. I'd say Dave, the biggest, sort of difference, in our investing theme. And this really comes out of like, post HubSpot. In addition to teaching the HBS, I did parachute into a different startup every quarter, for one day, where you can kind of like assess their go-to-market, looking for, like, what is the underlying consistency of those series A businesses that become unicorns versus those that flatline. And if I, you know, I've now written like 50 pages on it, which I, you know, we can, we can highlight to the crew, but the underlying cliffnotes is really, the avoidance of a premature focus on top line revenue growth, and an acute focus early on, on customer attention. And, I think like, for those of you, who run in that early stage venture community these days, and especially in Silicon Valley, there's this like, triple, triple, double, double notion of, like year one, triple revenue, year two, triple revenue, year three, double revenue, year four, double revenue, it's kind of evolved to be like the holy grail of what your objectives should be. And I do think like there is a fraction of companies that are ready for that and a large amount of them that, should they pursue that path, will lead to failure. And, and so, we take a heavy lens toward world-class customer retention as a prerequisite, to any sort of triple, triple, double, double blitzscaling type model. >> So, let me ask you a couple of questions there. So it sounds like your LPs are heavily, not only heavily and financially invested, but also are very active. I mean, is that a, is that a fears thing? How active are the LPs in reality? I mean, they're busy people. They're they're software operators. >> Yeah. >> Do they really get involved in businesses? >> Absolutely. I mean, half of our deals that we did in fund one came from the LPs. So we get half of our funnel, comes from LPs. Okay. So it's always like source-pick-win-support. That's like, what basically a VC does. And our LPs are involved in every piece of that. Any deal that we do, we'll bring in four or five of our LPs to help us with diligence, where they have particular expertise in. So we did an insuretech company in Q4, one of our LPs runs insurance practice at Workday. And this particular play he's selling it to big insurance companies. He was extremely helpful, to understand that domain. Post investment, we always bring in four or five LPs to go deeper than I can on a particular topic. So one of our plays is about to stand up in account based marketing, you know, capability. So we brought in the CMO, a former CMO at Rapid7 and the CMO at Unisys, both of which have, stood in, stood up like, account based marketing practices, much more deeply, than I could. You know of course, we take the time to get to know our LPs and understand both their skills, and experiences as well as their willingness to help, We have Jay Simons, who's the President of Atlassian. He doesn't have like hours every quarter, he's running a $50 billion company, right? So we have Brian Halligan, the CEO of HubSpot, right? He's running a $10 billion company now. So, we just get deal flow from them and maybe like an event once or twice a year, versus I would say like 10 to 20% of our LPs are like that. I would say 60% of them are active operators who are like, "You know what? I just miss the early days, and if I could be active with one or two companies a quarter, I would love that." And I would say like a quarter of them are like semi-retired and they're like, they're choosing between helping our company and being on the boat or the golf course. >> Is this just kind of a new model? Do you see having a different philosophy where you want to have a higher success rate? I mean, of course everybody wants to have a, you know, bat a thousand. >> Yeah. >> But I wonder if you could address that. >> Yeah. I don't think it, I'm not advocating slower growth, but just healthier growth. And it's just like an extra, it's really not different than sort of the blitzscaling oriented San Francisco VC, okay? So, you know, I would say when we were doing startups in the nineties, early 2000s before The Lean Startup, we would have this idea and build it in a room for a year and then sell it in parallel, basically sell it everywhere and Eric Ries and The Lean Startup changed all that. Like he introduced MVPs and pivots and agile development and we quickly moved to, a model of like, yeah, when you have this idea, it's not like... You're really learning, keep the team small, keep the burn low, pivot, pivot, pivot, stay agile and find product-market fit. And once you do that, scale. I would say even like, West Coast blitzscaling oriented VCs, I agree with that. My only take is... We're not being scientifically rigorous, on that transition point. Go ask like 10 VCs or 10 entrepreneurs, what's product-market fit, and you'll get 10 different answers. And you'll get answers like when you have lots of sales, I just, profoundly disagree with that. I think, revenue in sales has very little to do with product-market fit. That's like, that's like message-market fit. Like selling ice to Eskimos. If I can sell ice to Eskimos, it doesn't mean that product-market fit. The Eskimos didn't need the ice. It just means I was good at like pitching, right? You know, other folks talk about like, having a workable product in a big market. It's just too qualitative. Right? So, that's all I'm advocating is, that, I think almost all entrepreneurs and investors agree, there's this incubation, rapid learning stage. And then there's this thing called product-market fit, where we switch to rapid scale. And all I'm advocating is like more scientist science and rigor, to understanding some sequences that need to be checked off. And a little bit more science and rigor on what is the optimal pace of scale. Because when it comes to scale, like pretty much 50 out of 50 times, when I talk to a series A company, they have like 15 employees, two sales reps, they got to like 2 million in revenue. They raise an 8 million-dollar round in series A, and they hired 12 salespeople the next month. You know, and Dave, you and your brother, who runs a large sales team, can really understand how that's going to failure almost all the time. (Dave mumbles) >> Like it's just... >> Yeah it's a killer. >> To be able to like absorb 10 reps in a month, being a 50, it's just like... Who even does all those interviews? Who onboards them? Who manages them? How do we feed them with demand? Like these are some of the things I just think, warrant more data and science to drive the decisions on when and how fast to scale. >> Mark, what is the key indicator then, of product-market fit? Is it adoption? Is it renewal rates? >> Yeah. It's retention in my opinion. Right? So, so the, the very simple framework that I require is you're ready to scale when you have product-market and go to market-fit. And let's be, extremely precise, and rigorous on the definitions. So, product-market fit for me, the best metric is retention. You know, that essentially means someone not only purchased your offering, but experienced your offering. And, after that experience decided to repurchase. Whether they buy more from you or they renew or whatever it is. Now, the problem with it is, in many, like in the world we live inside's, it's like, the retention rate of the customers we acquire this quarter is not evident for a year. Right, and we don't have a year to learn. We don't have a year to wait and see. So what we have to do is come up with a leading indicator to customer retention. And that's something that I just hope we see more entrepreneurs talking about, in their product market fit journey. And more investors asking about, is what is your lead indicator to customer retention? Cause when that gets checked off, then I believe you have product-market fit, okay? So, there's some documentation on some unicorns that have flirted with this. I think Silicon Valley calls it the aha moment. That's great. Just like what. So like Slack, an example, like, the format I like to use for the lead indicator of customer retention is P percent of customers, do E event, in T time, okay? So, it basically boils it down to those three variables, P E T. So if we bring that to life and humanize it, 70% of the customers, we sign up, this is Slack, 70% of the customers who sign up, send 2000 team messages in 30 days, if that happens, we have product-market fit. I like that a lot more, than getting to a million in revenue or like having a workable product in a big market. Dropbox, 85% of customers, share one file in one hour. HubSpot, I know this was the case, 75% of customers, use five or more of the 25 features in the platform, within 60 days. Okay? P percent, do E event, in T time. So, if we can just format that, and look at that through customer cohorts, we often get visibility into, into true product market-fit within weeks, if not like a month or two. And it's scientifically, data-driven in terms of his foundation. >> Love it. And then of course, you can align sales compensation, you know, with that retention. You've talked a lot about that, in some of your work. I want to get into some of the things that stage two is doing. You invest in SaaS companies. If I understand it correctly, it's not necessarily early stage. You're looking for companies that have sort of achieved some degree of revenue and now need help. It needs some operational help and scaling. Is that correct? >> Yeah. Yeah. So it's a little bit broader in size, as any sort of like B2B software, any software company that's scaling through a sales team. I mean, look at our backers and look at my background. That's, that's what we have experience in. So not really any consumer plays. And yeah, I mean, we're not, we have a couple product LPs. We have a couple of CFO type LPs. We have a couple like talent HR LPs, but most of us are go-to-market. So we don't, you know, there's awesome seed funds out there that help people set up their product and engineering team and go from zero to one in terms of the MVP and find product-market fit. Right? We like to come in right after that. So it's usually like between the seed and the A, usually the revenue is between half a million and 1.5 million. And of course we put an extraordinary premium on customer retention, okay? Whereas I think most of our peers put an extraordinary premium on top line revenue growth. We put an extraordinary premium on retention. So if I find a $700,000 business that, you know, has whatever 50, 70 customers, you know, depending on their ticket size, it has like North of 90% local retention. That's super exciting. Even if they're only growing like 60%, it's super exciting. >> What's a typical size of investments. Do you typically take board seats or not? >> Yeah. We typically put in like between like seven hundred K, one and a half million, in the first check and then have, larger amounts for follow on. So on the A and the B. We try not to take board's seats to be honest with you, but instead the board observers. It's a little bit selfish in terms of our funds scale. Like the general counsel from other venture capitalists is of course, like, the board seat is there for proper governance in terms of like, having some control over expenditures and acquisition conversations, et cetera, or decisions. But a lot of people who have had experience with boards know that they're very like easy and time efficient when the company is going well. And there are a ton of work when the company is not going well. And it really hurts the scale, especially on a smaller fund like us. So we do like to have board observers seats, and we go to most of the board meetings so that our voice is heard. But as long as there's another fund in there that, has, world-class track record in terms of, holding proper governance at the board level, we prefer to defer to them on that. >> All right, so the COVID lock down, hit really in earnest in March, of course, we all saw the Sequoia memo, The Black Swan memo. You were, I think it HubSpot, when, you remember the Rest In Peace Good Times memo, came out very sort of negative, put up all over the industry, you know, stop spending. But there was some other good advice in there. I don't mean to sort of, go too hard on that, but, it was generally a negative sentiment. What was your advice to your portfolio companies, when COVID hit, what were you telling them? >> Yeah, I summarized this in our lead a blog article. We kicked off our blog, which is partially related to COVID in April, which has kind of summarize these tips. So yes, you are correct, Dave. I was running sales at HubSpot in '08 when we had last sort of major economic, destabilization. And I was freaking out, you know (laughs briefly) at the time we were still young, like 20, 30 reps and numbers to chase. And... I was, actually, after that year, looking back, we are very fortunate that we had a value prop that was very recession-proof. We were selling to the small business community, who at the time was cutting everything except new ways to generate sales. And we happen to have the answer to that and it happened to work, right? So it showed me that, there's different levels of being recession proof. And we accelerated the raise of our second fund for stage two with the anticipation that there would be a recession, which, you know, in the venture world, some of the best things you could do is close a fund and then go into a recession, because, there's more deals out there. The valuations are lower and it's much easier to understand, nice to have versus must have value props. So, the common theme I saw in talking to my peers who looked back in the '01 crisis, as well as the '08 crisis, a year later was not making a bolder decision to reorient their company in the current times. And usually on the go-to-market, that's two factors, the ICP who you're selling to, ideal customer profile and the CVP, what your message is, what's your customer value prop. And that was really, in addition to just stabilizing cash positions and putting some plans in there. That was the biggest thing we pushed our portfolio on was, almost like going through the exercise, like it's so hard as a human, to have put like nine months into a significant investment leading up to COVID and now the outcome of that investment is no longer relevant. And it's so hard to let that go. You know what I mean? >> Yeah. >> But you have to, you have to. And now it's everything from like, you spent two years learning how to sell to this one persona. And now that persona is like, gyms, retail and travel companies. Like you've got to let that go. (chuckle simultaneously) You know what I mean? Like, and, you know, it's just like... So that's really what we had to push folks on was just, you know, talking to founders and basically saying this weekend, get into a great headspace and like, pretend like you were parachuted into your company as a fresh CEO today. And look around and appreciate the world and what it is. What is this world? What are the buyers talking about? Which markets are hot, which markets are not, look at the assets that you have, look at your product, look at your staff, look at your partners, look at your customer base, and come up with a strategy from the ground up based on that. And forget about everything you've done in the last year. Right? And so, that's really what we pushed hard on. And in some cases, people just like jumped right on it. It was awesome. We had a residential real estate company that within two weeks, stood up a virtual open house module that sold like hotcakes. >> Yeah. >> That was fantastic execution. And we had other folks that we had to have like three meetings with to push them deep enough, to go more boldly. But that, was really the underlying pattern that I saw in past, recessions and something I pushed the portfolio on, is just being very bold on your pivots. >> Right? So I wanted to ask you how your portfolio companies are doing. I'm imagining you saw some looked at this opportunity as a tailwind. >> Yeah. >> You mentioned the virtual, open house, a saw that maybe were exposed, had, revenue exposure to hard-hit industries and others kind of in the middle. How are your portfolio companies doing? >> Yes, strong. I'm trying to figure out, like, of course I'm going to say that, but I'm trying to figure out like how to provide quant, to just demonstrate that. We were fortunate that we had no one, and this was just dumb luck. I mean, we had no one exclusively selling to like travel, or, restaurants or something. That's just bad luck if you were, and we're fortunate that we got a little lucky there, We put a big premium, obviously we had put a big premium on customer retention. And that, we always looked at that through our recession proof lens at all our investments. So I think that helped, but yeah, I mean, we've had, first off, we made one investment post COVID. That was the last investment on our first fund and that particular company, March, April, May, their results were 20% higher than any month in history. Those are the types of deals we're seeing now is like, you literally find some deals that are accelerating since COVID and you really just have to assess if it's permanent or temporary, but that one was exciting. We have a telemedicine company that's just like, really accelerating post COVID, again, luck, you know, in terms of just their alignment with the new world we're living in. And then, jeez! I mean, we've had, I think four term sheets, for markups in our portfolio since March. So I think that's a good sign. You know, we only made 11 investments and four of them, either have verbal or submitted term sheets on markups. So again, I feel like the portfolio is doing quite well, and I'm just trying to provide some quantitative measures. So it doesn't feel like a political answer. (Mark chuckles) >> Well, thank you for that, but now, how have you, or have you changed your sort of your thesis post COVID? Do you feel like your... >> Sure. >> Your approach was sort of geared towards, you know, this... >> Yeah. >> Post COVID environment? But what changes have you made. >> A little bit, like, I think in any bull market, generally speaking, there's just going to be a lot of like triple, triple, double, double blitzscaling, huge focus on top-line revenue growth. And in any down market, there's going to be a lot of focus on customer retention unit economics. Now we've always invested in the latter, so that doesn't change much. There's a couple of things that have changed. Number one, we do look for acceleration post COVID. Now, that obviously we were not, we weren't... That lens didn't exist pre-COVID, So in addition to like great retention, selling through a sales team, around the half million to a million revenue, we want to see acceleration since COVID and we'll do diligence to understand if that's a permanent, or a temporary advantage. I would say like... Markets like San Francisco, I think become more attractive in post COVID. There's just like, San Francisco has some magic happening there's some VC funds that avoid it, cause it's too expensive. There's some VC funds that only invest in San Francisco, because there's magic happening. We've always just been, you know... we have two portfolio companies there that have done well. Like we look at it and if it's too expensive, we have to avoid it. But we do agree that there's magic happening. I did look at a company last week. (chuckles inaudibly) So Dave, there are 300K in revenue, and their last valuation is 300 million. (both chuckle) >> Okay, so why is San Francisco more attractive, Mark? >> Well, I mean and those happened in Boston too. >> We looked at... (Mark speaks inaudibly) >> I thought you were going to tell me the valuations were down. (Dave speaks inaudibly) >> Here's the deal all right, sometimes they do, sometimes they don't and this is one, but in general, I think like they have come down. And honestly, the other thing that's happened is good entrepreneurs that weren't raising are now raising. Okay? So, a market like that I think becomes more attractive. The other thing that I think that happens is your sort of following strategies different. Okay so, there is some statistical evidence that, you know, obviously we're coming out of a bear market, a bullish market in, in both the public and the private equities. And there's been a lot of talk about valuations in the private sector is just outrageous. And so, you know, we're fortunate that we come in at this like post seed, pre-A, where it's not as impacted. It is, but not as or hasn't been, but because there's so many more multibillion-dollar funds that have to deploy 30 to 50 million per investment, there's a lot of heating up that's happened at that stage. Okay? And so pre COVID, we would have taken advantage of that by taking either all or some of our money off the table, in these following growth rounds. You know, as an example, we had a company that we made an investment with around 30 million evaluation and 18 months later, they had a term sheet for 500. So that's a pretty good return in 18 months. And you know, that's an expensive, you know, so that that's like, wow, you know, we probably, even though we're super bullish on the company, we may want to take off a 2X exposition... >> Yeah. >> And take advantage of the secondaries. And the other thing that happens here, as you pointed out, Dave is like, risk is not, it doesn't become de-risk with later rounds. Like these big billion dollar funds come in, they put pressure on very aggressive strategic moves that sometimes kills companies and completely outside of our control. So it's not that we're not bullish on the company, it's just that there's new sets of risks that are outside of the scope of our work. And so, so that that's probably like a less, a lesser opportunity post COVID and we have to think longer term and have more patient capital, as we navigate the next year or so of the economy. >> Yeah, so we've got to wrap, but I want to better understand the relationship between the public markets and you've seen the NASDAQ up, which is just unbelievable when you look at what's happening in main street, and the relationship between the public markets and the private markets, are you saying, they're sort of tracking, but not really identical. I mean, what's the relationship. >> Okay, there's a hundred, there's thousands of people that are better at that than me. Like the kind of like anecdotal thoughts that I, or the anecdotal narrative that I've heard in past recessions and actually saw too, was the private market, when the public market dropped, it took nine months roughly for the private market to correct. Okay, so there was a lag. And so there's, some arguments that, that would happen here, but this is just a weird situation, right? Of like the market, even though we're going through societal crazy uncertainty, turmoil and, and tremendous tragedy, the markets did drop, but they're pretty hot right now, specifically in tech. And so there's a number of schools of thoughts there that like some people claim that tech is like the utilities companies of the eighties, where it's just a necessity and it's always going to be there regardless of the economy. Some people argue that what's happened with COVID and the remote workplace have made, you know, accelerated the adoption of tech, the inevitable adoption, and others could argue that like, you know, the worst is still the come. >> Yeah. And of course, you've got The Fed injecting so much liquidity into the system, low interest rates, Mark, last question. Give me a pro tip for entrepreneurs. (Mark Sighs) >> I would say, like, we've talked a lot about, this methodology with, you know, customer retention, really focusing there, align everything there as opposed to top line revenue growth initially. I think that the extension I do at this point is, do your diligence on your investors, and what their thoughts are on your future growth plans to see if they're aligned. Cause that, that becomes like, I think a lot of entrepreneurs, when they dig into this work, they do want to operate around it. But that becomes that much harder when you have investors that think a different way. So I would just, you know, just always keep in mind that, you know, I know it's so hard to raise money, but you know, do the diligence on your investors to understand, what they'd like to see in the next two years and how it's aligned with your own vision. >> Mark is really great having you on. I'd love to have you back and as this thing progresses, and see how it all shakes out. It really a pleasure. Thanks for coming on. >> No, thanks, Dave. I appreciate you having me on. >> And thank you everybody for watching. This is Dave Vellante for The Cube. We'll see you next time. (music plays)

>> Narrator: From around the globe, it's theCUBE, covering HPE Discover Virtual Experience, brought to you by HPE. >> Hello and welcome to theCUBE's coverage of HPE Discover 2020, The Virtual Experience. I'm Lisa Martin and I've got a couple of guests joining me, Stephen Laaper principal at Deloitte consulting and Brenna Sniderman the Executive Director for the Center of Integrated Research at Deloitte Services, Stephen and Brenna, nice to have you on the program today. >> Thank you, >> (mumbles) >> So we're going to be talking about The Smart Factory. I'd love for you to start Brenna, we'll start with you. Give our audience an overview of Deloitte's definition of The Smart Factory then we can dig into some of the very interesting research that Deloitte has been doing the last few years. >> Sure, absolutely. So the way we think about The Smart Factory is it is a system that's quite flexible that uses data and information from throughout, physical assets to optimized performance, to enable the facility to be more agile, to be proactive, to optimize its assets and to react and change as quickly as possible to shifts going on. It overall enables organizations to just be more intelligent about the way they use their assets to use data, to make more informed decisions and to drive a more optimized process. >> And Stephen for you, one of the things that I found interesting looking at some of Deloitte's research is that the last few years or so, there's been net zero growth in manufacturing labor productivity and labor productivity being an indicator of economic impact. Why in Deloitte's perspective, has that manufacturing labor productivity growth been flat? >> Yeah, it's a really interesting observation. And what we've seen is really decades and decades of management principles, companies using things like Lean, like Six Sigma, taking advantage of labor arbitrage in many cases. And the reality is that a lot of that low hanging fruit is gone. Those projects have been executed well and we're now seeing what we would consider to be diminishing returns as it relates to the investments in those same types of tools. And that is really what's leading many organizations now towards things like the capabilities that you'd find in a Smart Factory. Adding additional technologies to the capability set to really bring companies to that new productivity frontier. >> One of the things that I saw too, is that Smart Factory adoption in one of your studies, can result in a threefold productivity increase. So talk to me about in the last few years, some of the early adopters, Brenna we'll start with you, what are some of the trends that you've seen with those early adopters? any industries in particular that are leading in that respect? >> Well, that's a good question. I think when we recently published a study on lessons from early adopters in the Smart Factory and what we found was that a lot of the organizations that have adopted the Smart Factory have learned lessons that are not necessarily new but some that are new as well. Really I think the biggest challenge has been to figure out how to gather data from a lot of assets that maybe haven't had to produce data before to find out where all the information is from throughout the facility to bring together different groups and different cultures within the organization, whether it's IT and OT and have them figure out how to share information and data and really just to figure out what to do with that information once we've gotten it. Some of the organizations that we spoke with for our research really ran the gamut from aerospace to automotive, to consumer products, to industrial manufacturing. It really has been an interesting spread that we've looked at. >> Stephen walk us through the last three years or so of research that Deloitte has been doing into the Smart Factory from the 2017 study to the 2019 study, to the one that was just released, what's some of the progress that you've seen over the last three years? Is it what you anticipated it would be? >> Yeah, it's interesting. I mean, three years ago, I think a lot of people were talking about Industry 4.0, they were talking about the industrial internet of things, they were talking about The Smart Factory, but we saw relatively few very concentrated efforts to advance those. Now as we fast forward three years, we're seeing that the specific capabilities that each one of those topic areas can enable for organizations, has become much clearer. So correspondingly companies have been planning for these types of investments and they're taking action on much of the capability build and quite frankly, starting to see the value. One of the underlying kind of architectural elements that I think are critical as part of the modern Smart Factory is exactly what Brenna touched on. And that was as it relates to the data. Many assets out there even if they're several decades old likely have a wealth of data associated with them. The challenge is that data is either not readily accessible or it's not well understood. And much of the effort that organizations have now undertaken is not only how do they connect, extract and use that information many times on a real time or near real time basis, but now also combining that information with other assets, other parts of the manufacturing facility, or even their manufacturing network to generate that value. >> So Stephen follow on question, how does an organization, a company start that process, if as you said, there's myriad assets of varying age, some really advanced, some really old as well as even from, I guess, a generational perspective in the workforce, you've got multiple generations, for organizations that know we've got data that's hidden, where do they start? >> Yeah, absolutely. And I think a really important element of your question is how do you determine where to start? And the reality is that not all of these solutions are created equal. Not all of the assets have data that's interesting enough to be equal. And so really going through a very concerted effort to understand what are the capabilities we're trying to build And what value does it create for our organization? Aligning that to the objectives and the goals of the organization is critical right from the outset. And we see companies that are being most successful in their implementation of the Smart Factory, following that value orientation. And that might not mean that that value comes tomorrow, It might not come next month, but there's a very clear guidance in terms of how the particular capabilities that are being built will lead to value. Organizations that are not doing that, we tend to see random X visual. We see a lot of different efforts underway with very little tied value and correspondingly many of those efforts don't continue because the executive team, the shareholders aren't going to continue those investments in that space without showing them (mumbles). >> So Brenna walk us through, along what Stephen was just saying. I was reading in your 2020 study that positioning a Smart Factory initiative for value starts with human-centered design and I thought this was really interesting that Deloitte research demonstrated successful teams generally focus on the user first, not the technology. >> Well, yeah. And I think to follow on a little bit to what Stephen said about understanding the value and the goal of what you're trying to do before thinking about the technology you need to rush out and implement goes along with this as well. You want to think about what the user is actually going to be using that data for, what is their job, what information are they going to need and think about from their perspective, what is going to be most helpful and effective for them. And I think the value of this is twofold. One is if talent within your organization and folks on the shop floor, see the value of this data and information, they're going to be more inclined to adopt it because it makes their job easier. But also if you have a tremendous amount of data and information from all the different assets and parts of your facility, if an individual has to sift through all of that, to find what's going to be valuable to them, it's not really going to make their job easier. So human-centered design is really thinking about what that individual needs to do their role, and in a lot of the work that we've done, we've almost thought about it as personas where this particular persona or job needs this information, needs to go through these steps and here's the data information we need to show them to enable them to do that. It's just a way for people to leverage information, to make smarter decisions more quickly. >> How does a manufacturing company do that, Brenna, excuse me, without being siloed, like in business units, so I'm thinking, getting cross-functional support all the way up to the top level. >> Mhhh, that's something that we saw quite a bit in our research that many of the groups or organizations that have successfully enacted a Smart Factory have done so because it's not just coming down from the top, it's also coming up from the bottom. You know, although that may sound like a pejorative term, but coming from all angles of the organization. So we see from the strategic level, this is what we need to do to change the way our organization operates in a more effective way. But from the line of business individuals that are using this information and data every day, we need to think about sort of having a groundswell of support work there as well, so that our team members are using this information. So I think it has to be something that comes from throughout the organization. What we've also found your point about silos is bringing in diverse teams and individuals from throughout the organization who have different types of expertise, different perspectives, different things that they're looking at in different ways that they need to use this technology to do their job, will enable us to make sure that, what we're producing is something that's going to be of value to them. >> And along those lines, Stephen question for you, this must need to be looked at, not as what can we do today or the next six months, but over the long-term. So that ongoing enablement and education is going to be critical. >> Yeah, absolutely. Right. And you know, the reality is that some of these investments that organizations are making into Smart Factory, do take quite a bit of thought, research and assessment and those aren't investments that they're making for the short-term, many of them are long-term. The important part about those investments that organizations are making is that they're creating platforms by which teams can continue to evolve the persona-based type solutions that Brenna referred to, so critical. And so, the flexibility, the adaptability, the agility of those platforms and the investments that are being made, really is one of their critical factors. I did want to just revisit the user adoption of these types of solutions. And, I'm a engineer by education. And I could look up back to early in my career and say, "Hey, look, I built solutions, "using data for manufacturing shop floor equipment. "And I created those solutions for others." But the reality was that I created it in a way that an engineer would you consume that data. And the reality is the persona-based approach really lets us focus on how is a particular individual in their job going to consume that data in a way that enables them to make the best next decision which ultimately has a positive outcome for the company. And in some cases that might mean not exposing them to all the complexities that happen underneath the surface. The modern smartphone, for example, enormously complex device, yet intuitive to use, easy to pick up, easy to interact with. The modern Smart Factory is also very similar in that frame. >> Along those lines of agility, but also designing with certain mindset, culturally IT and OT are different. Brenna, one of the things that I found interesting in the research was the marriage of IT and OT, how do you advise or let's go to clients that were part of that 2020 study, what lessons can the next wave of adopters learn where it comes to bridging those two IT OT mentalities and different cultures? >> Yeah, that's a good question. And I think the different cultures is sort of, key insight that is helpful. With respect to IT, they work on different timeframes, they think about investments in a different way, they think about technology in a different way than individuals who are in OT, who are on the shop floor, who are using these tools every day. and what we found was that bridging that divide and bringing them together, is a challenge that many overlook and something that really the importance of it, can't be overstated. I think to get back to Stephen's point about adoption, if those within the OT space have an understanding of what IT is doing and why, they're just likelier to adopt and to use. And conversely, if those in IT have a deeper understanding of what those in OT are doing and what types of tools they need, they're likelier to come up with solutions that are going to be effective. I think the cultural divide is something that's practically important to understand, to address and not to overlook because I think the last thing that anyone implementing any sort of Smart Factory solution wants is to roll out a solution that was sort of baked in one area, but not taking into account the other as well. >> Great point. Stephen, I want to go back to you for a second. Just understanding along the lines of the cultural differences and the design principles that need to be factored in. When the COVID-19 pandemic hit in March of 2020, for clients that you were talking to that were in whatever stage process of rolling out Smart Factory initiatives, where are they now? And what are some of the advantages that you see that organizations that aren't yet adopting Smart Factory initiatives should be doing to prepare to thrive in this new normal? >> Yeah, absolutely. Let me start with some of those advantages right at the outset. So many organizations now have been looking at advanced solutions, perhaps, to enforce social distancing within the manufacturing environment or perhaps contact tracing within the manufacturing environment and the advantages organizations are seeing that are already on that Smart Factory journey is they're finding they have largely a lot of the infrastructure required to be able to do that already in place. So that has been an enormous accelerant for companies that are already on the journey. The reality is that many organizations, are unable to have their experts, their engineers, their vendors, many of the people that are supporting the equipment and the people in their manufacturing plants around the world, they're not able to get them there. And companies that have been on the Smart Factory journey, specifically as it relates to creating what we would call the digital twin of many of their assets, where they can now see not only visual representations of those assets, but can also see that the data flowing off those assets and in the most advanced solutions, being able to see those together, they'd be able to unlock remote support, in a way that organizations that have not been on this journey simply can't. And we're starting to see some very distinct results, as it relates to those who are able to continue running at scale, and those who are struggling in the COVID environment. >> And Stephen, last question for you. I know you've got a session or a demo on Smart Factory an AI that you're doing at Discover 2020. Tell us a little bit about that and what the participants can anticipate. >> Yeah. So we're really excited to be able to bring Factory AI as we call it, in a live virtualized session. That session is going to cover what we have built around we'll call it a mini manufacturing line. And usually we'd have that with you at the conference, or we take that around the country, to many of our manufacturing clients to really show them, the power of adopting many of these different types of capabilities in the manufacturing environment. So what we're going to be showing and what viewers can expect to see is a demonstration of edge capabilities, of computer vision, of advanced internet of things, all wrapped into several high-impact use cases. So we're looking forward to you're doing that. >> Excellent. Well, Stephen, Brenna, thank you so much for your time discussing The Smart Factor. This is such an interesting provocative topic. I wish we had more time, but appreciate you speaking with me today. >> Thanks for having us. >> Thank you. >> You're watching the cube, Lisa Martin for HPE Discover 2020, The Virtual Experience. Thanks for watching. (upbeat music)

>> Announcer: From theCUBE studios in Palo Alto in Boston, connecting with thought leaders all around the world this is theCUBE conversation. >> Hello everybody, my name is Dave Vellante welcome to this CUBE conversation. You know for the last several weeks, we've been interviewing key executives to really try to understand how they're responding to the COVID-19 crisis. And one of the key areas that we've been reporting on is the so-called work from home offset. And I'll explain that in a little bit, but there are two great executives from Citrix that I'm really please to have on. Donna Kimmel, the Executive Vice-President and Chief People Officer. Donna, great to see ya', thanks for comin' on. >> Thank you. >> And she's joined by Meerah Rajavel who's the CIO of Citrix. Meerah, thank you as well. >> Thank you. >> So I mean this thing, it's been amazing. We've been doing a lot of research and it just obviously came out of the blue. Guys, if you would actually bring up that chart, I want to sort of set up the conversation here. This is something that we've been reporting on for a while. This is an ETR survey from about 1300 CIO's and IT practitioners that, we asked them how is your budget going to change in 2020 as a result of COVID? And you can see the red. We all know the story in the red, it's ugly. But surprisingly about 35% of the respondents said, no change. They're actually going to plow ahead, but what's even more surprising was 20 plus percent, about 21% said, we're actually going to spend more. And so you can see from the data that it's actually would be a lot worse were it not for the green. Now the reality is, that green is a function really of work from home infrastructure and guys that's something that I really want to talk to you about today. So, Donna let me start with you. I mean we always talk about people, process and technology. I mean we went from put your toe in the water with work from home infrastructure to all in. (chuckles) Your thoughts, I mean this is just overnight. >> Absolutely. You know I think when I think about remote work and working from home, it is really not business as usual. And probably was the biggest change that businesses have experienced, even in my career and many others. This was pretty much thrust upon us, the work from home. And we realize that it requires new ways of thinking and behaving and operating. Our home offices quickly became kitchen tables and basements and bathrooms and bedrooms. And in addition to it not neccesarily being setup the way we would normally set it up if we knew we were going to work from home. It also didn't generally involve caring for family members at the same time. And so most people thought for the first couple of weeks, well I can get through this you know for it's not an extended period of time, but the reality it's become an extended period of time. And I think ultimately, you know when we step back and think we're, as humans, we're all survivors and we're resilient. And there's a number of ways that we can help our employees as they make the adjustment that was really sort of pushed on them. >> Now, the executives that I've been talking to, they to a person start with look, the safety and health of our team is the most important. So you obviously had to communicate that, Donna. I wonder if you could talk about sort of the priorities, how you, you know what is it the cadence of your communication, the transparency of your communication, what really was your, sort of first move if you will? >> Yeah, absolutely, I think for us, one of the first things we had to step back and think about is, who are we, what is our culture, what's important to us? And we recognize at Citrix, that it's our talent that makes the business successful, so we need to show, understand as much of the experience as possible that our employees are having. And really come at it from, I think a place of empathy. Listening to what's important to them, thinking about what's going to enable them to be successful. Because when are employees are successful, they truly drive success and a great experience for our customers. They're the ones out there helping to support our customers to support our sales partners, and certainly ultimately our community. But when we think about this, we're thinking about the challenges, the opportunities, trying to developing plans and programs and making sure that we have continuous information that is provided to our employees. And I think part of it, we'll have an opportunity to talk with Meerah as well. When we step back, we think about kind of three things from a future of work perspective. We always think about the culture of the organization, which is the embodiment of the values, the who we are and what we do. All of this clearly is grounded in the business objectives. So the first piece is our culture. The second piece is our physical space. So what is our environment like that enables us to be as productive as possible? And then the third piece is our digital space. If you can think about all of those almost as a Venn diagram, that really puts the employee at the center. When we think about what's going to enable our employees to be successful, we think about that in a very holistic way. And so, culture is, sorry did you want to, I'm, >> Oh no, please, keep on talking, go ahead. >> Yeah, I was just going to say culture for us is really grounded in our ability to drive trust in the organization. It's about that human connection. Because the more we can be connected with each other as managers to employees and peers to employees, the better off we are. People will feel less isolated, because without that face to face it makes it, and face to face and I'll say in person makes it a lot more difficult. The second piece that we focus on is that physical environment. And I think for many employees, because they were thrust into the situation. When they compare it to the work environment, when you're in the office there's almost a professional feel, in that work environment. And so employees feel a fair amount of pressure to try to create that same professionalism at their home. And the reality is, it's hard to do that. So it puts a lot of pressure on employees when they recognize that the whole family is quarantined with them. Right there's home schooling going on, there's no child care or elder care, there's interruptions at inopportune times, barking dogs and cats walking across keyboards and family members doing drive-bys while the video camera's on. And I think one of the things that we've been able to do is to help employees feel comfortable with, that's who you are, that's our humanity. And the more we can help people feel comfortable about creating that physical space that's open and welcoming, that really helps drive that experience. And then the third piece as I mentioned, is the digital space. And that's really where the partnership with Meerah comes in and is so, so important. Do they have the right tools and technology at home to be able to drive that experience? And for us, you know as Meerah and I have talked that partnership between IT and HR is critical. We're almost like the new BFF. In order to drive the right experience to enable our employees to be as productive as possible in this work from home. >> All right, so Meerah let's get into that. So once you've established though the self, the safety, the health, of your employees obviously financial flexibility, and Runway and the like, their physical digital space. Now you're really under a microscope with the tech. Now, of course Citrix has been in this business for decades. So you know a lot about this, but nonetheless, this is really new. You were thrust into it overnight. Your thoughts on how you responded and you know kind of where we're at in that journey. >> Absolutely, absolutely. So one of the things Donna mentioned right, the three aspects. When we move to work from home the biggest piece of this aspect that made it, like for example she was telling, like myself, we are in transition. I'm moving from Austin, Texas to Florida when it is all in the middle, I'm right now in the middle of my transition, I'm not settled in my new house and literally I'm doing this interview with the, sitting my laptop on top of cereal boxes, right now. That's actually something that I empathize clearly with my employees. So the physical space, when you are in an office location it's not anymore that we can control. So the digital space needs to really compensate for the physical space. The culture is something, I think we are very lucky being in Citrix, the notion of what we have always been talking about remote work and employee experience, we have got that ingrained so when we have to go into this remote work space in a work force culture, the culture is something that I would say we had some foundation to stand on. But IT has to come in. It's not an easy job, because we want to give people the ability to do what they want in a productive fashion, but now digital needs to compensate for the physical, you know efficiency that are possibly lacking in a home environment. So I looked at it from three C's. It starts with connectivity, right. Connectivity being, are we providing the right kind of connectivity which is through a secure connection. At the end of the day, my job here is to make the employee productive and secure at the same time. It's not just about the productivity, but wrap it up with the greater experience. So we start looking at connectivity from a security point of view, from a performance point of view, using technologies like Sdram and maximizing their performance to their nearest, how we can break out the security to maximize performance for our employees. We also need to take into account that there are countries we went into the last way understand where the true problem, because if you go to Asia, there are so many countries, you know even if we can provide experience, they're experience is very dependent on the local connectivity. So we need to look at, okay how do we ensure our heavy duty applications are in a very optimized so it doesn't become a productivity hit for the employee. The second is you think about productivity for employees, and it's all about information sharing and content sharing right. So I call the second C is the content. The ability for the employee to have the right data, the right place and so they can make decisions and they can be productive. So using things like, whether it is your share file or your OneDrive or your vision platform, G-Drive, it doesn't matter, but you have to really make sure the data and information are available and be focused on making sure that they are streamlined and communicating about that very openly, like to Donna's point. The third C we looked at was collaboration, right. I mean that's actually with, you know we are now compensating for the physical touch with a digital touch. So that includes things like your audio conferencing platform, your videoconferencing platform, your ability to bring these different facets together right. I mean the ability to share, the ability to white board. I had last week, three days offsite and it was a complete virtual offsite with nine hours of working sessions and we used all kinds of tools that literally we had digital sticky's to move around that integrated into our videoconferencing platform that integrated into our conference sharing platform. So that whatever they are doing, those are all connected. At the end of the day, I truly felt like you know what? I can contribute to not adding to the carbon footprint of the globe. Because truly we had people from all over the globe, all of us set in. I'm getting feedback from employees saying, now the playing field is completely leveled down. People who were being remote users before, they felt they had a short stick. Now everybody's same, in fact my staff actually talked to one of my permanent remote employee and say, "Hey what is some tips that I can use from you "to make sure I'm productive, right?" So I see the culture aspect is super important that's actually bringing us together, but it is from a technology and digital point of view, bringing your you know connectivity, content and collaboration in a way that it's going to be secure and innovative. We are looking at it with the aspect of your culture and from the employee shoes is a super important thing from a technology point of view. >> So Donna you mentioned the sort of BFF between HR and IT. Now of course, HR and IT have always had a relationship, but it really has been around, like you know Human Capital Management software, whether it was simplified and efficient, onboarding, or certain you know change management functions. What have you been able to learn from that relationship and apply and what's new? >> You know, I think, what we're doing together, what Meerah and I and the IT and the HR organizations are really doing together is truly understanding what it means to enable productivity for employees. And when you think about having the right tools to enable employees to be productive, doing that in alignment with the culture of the organization. What is it that drives our sense of meaning and accomplishment? And then being able to do it in a way, both in a physical environment, whether that physical environment is in the office or if it is remote, we do look collectively together at the change management. How do you get employees to adopt new ways of doing things? And utilize that and learn from it. So if we experiment with certain types of productivity tools as Meerah was talking about. Which ones work, which ones needed a change, what works for some teams and didn't work for others? When she and I can do that together and our departments can do that together, that enables us to truly drive productivity across the organization. >> I would probably add one more thing to what Donna said. I mean the thing is, also if you think about it, you know the human resources, the talent organization has a much better understanding of the culture, of the sub-cultures, right. I mean I've never been in a company even when it's a thousand people company, you have sub-cultures. And HR you know involved in the culture of those sub-cultures. As we are going through from IT point of view, we look at it from user persona, okay. So a salesperson who's actually always on the road or always like more remote worker versus an engineering person. I mean we are a software company, an R & D persona quite a different set of productivity tools compared to a sales person, compared to an executive, compared to an executive assistant right. So for us, it's actually bringing that different functional line of business and the type of persona. And HR is absolutely crucial because as we are looking at it they're saying, what is a success for this organization? And what the culture of the organization and what are the primary job roles? And we don't do it just with HR, but HR uses so much content to get jump start and then we engage with the real users. We are not going with a blank sheet of paper. We are going with something that they can react to and they add to it. So we're doing a design thinking with them that something they can be in start to get rather than you know white canvas and telling, tell me what do you want? I mean, you know ask what you want, you'll be getting pie in the sky and the moon. >> Well it's a good thing you have those virtual sticky's too. That'll help with that design thinking right? You know, one of the things that I've been saying is that you know, we've never seen obviously anything like this before, a forced shut down of the economy which is why we're going to remember it. And like 911, you know post 911, we are going to see some things here that have permanence. And post GDPR for example, it required certain changes. So Donna, I wonder if we could start with you, just and it's ironic that we're starting a new decade with this crisis. We're not just going to go back and revert to 2019. There's not just going to be some you know all of a sudden everything is rosy again, it's not. It's going to, there's going to be certain permanent changes. How much have you thought about that and do you have any visibility on what those are going to be? >> Yeah, you know when I step back and I think about this and I think a large part of it has to do with much of what Meerah was just talking about in terms of design thinking. It's really, I think for all of us, it's coming back to recognize that this became almost a forced opportunity to focus on business continuity. And how do we think about what's right for us as we move forward? But the design of that is based on what is right, what's the context for that particular business? What's the culture of that organization? What are the products and services that that business provides? What are the sub-cultures in the organization? So for me, it really does step back to say, look we need to focus on business continuity. And now we have a couple of new models, where in the past it would be really easy for managers to say, you know I don't think my team can work remotely, or your job isn't possible to do remotely. And now what we're finding in many businesses is that many jobs can actually be done remotely, if they're provided the right tools and the right resources. So for me, I step back and say, as we think about the business continuity going forward, there is a new way to work. It is a combination of finding that flexibility between working in the office and remote work. And providing the right tools that enable employees to be able to do it successfully. >> You know, Meerah this notion that Donna's bringing up of business continuance, I've sort of been noodling on this and thinking that going forward, one of the things that will change is that companies might be willing to sub-optimize near term performance to put in better business resiliency. Now at the same time, I know how CEO's think. And they say okay great, we're going to make that investment yeah, fine we'll maybe sacrifice some short term performance. But and I had a really interesting conversation recently with a chief data officer who said, you don't have to sacrifice necessarily with data in this new era. There actually are ways in which you can both drive business resilience and drive productivity and ultimately profitability. What's your thinking on that sort of imbalance or balance, if you will? >> I agree with that statement because to me, you know today's business we need to look at I mean especially with the cloud and some of the new technology that we have, I mean even, I seriously think coming out of COVID there's going to be industries that are going to come out new business models that are going to emerge, right. I mean think about Telemedicine. We have been very, very hesitant about Telemedicine for decades now. I mean that's not a new concept. But we have been very hesitant. We said, "I have to see the doctor." But today pretty much everybody, except for if your seriously injured you're getting Telemedicine. That industry is going to work right. So to me the statement you made is absolutely, absolutely for me it's actually an opportunity coming out of an adversity that's going to come out. When I think about it the most important thing I see is the businesses that are going to be successful, that's why even HR, you know partnership is even more greater. The businesses that have talent with digital dexterity are the ones that are going to win, right. I mean regardless you know, where you are in HR, whether you're in finance, whether you're in IT, you're in R & D, you're in manufacturing, doesn't matter. Your digital dexterity of your company really makes you, whether you win in the market or you're one of those dinosaurs in the market right. And how do you bring those together? That's a cultural change, that's actually educating right. I mean we don't want to leave, we already have talent shortage and we don't want to leave a generation of population behind and focused on only the millennials and others. Because I mean, recently I've been going through Scaled Agile Framework, which is a Lean-Agile. And I really love the board of Lean-Agile. Lean has a lot of economy's of scale. Agile brings a lot of volatility. When you bring them together you get both and that's exactly what we need to do with our talent. Bring the system and bring the digital dexterity that we need to bring to that. Can we get it from a productivity, of course we want to be respectful of privacy, but as we have been going through we have been looking at different productivity metrics, looking at you know, what is the usage pattern for employees? How much quotient they have done, how was my MTTR? I mean in my organization I've been looking at the velocity of all transaction processing, Azure, Allusion escalate time. And we also even you know kind of little, because I think at the end of the day we as humans, we actually are social animals. We need the touch and we can not forget, we are not mechanical, we are human. So we need that empathy and we need that emotional side of it. So we have been both qualitatively and quantitatively checking with our workforce, how they are feeling about it and also looking at the data to see if the productivity is telling the story what people are talking about. And quite surprised, 66% of our population when we did this culture survey, said they feel more productive in this situation, because many of them contribute it back to, the time they save from not commuting or they feel just the sense of spending a little bit more time with the family, is actually getting them an extra boost. And they can really do a work-life integration, not like a work-life balance they need to do and we also heard about 11% felt pretty much, they are in the same range. But I also want to recognize it's not for everyone, but I mean we do have folks who are in manufacturing, they need to touch the physical things. And those jobs in certain ways need to be, you know more physical. So there's about three to five percent depending on your job functions that, you know what I need access to the lab, because I really feel the changing my connectivity, changing my or just like for the customer I'm repairing their board. I really need to see that. Those are the ones where we find you know absolute physical touch is required. >> You know in a way I mean we're kind of lucky in the technology business, talk about the digital transformation and I've been saying this has been accelerate a lot of digital transformations. But for us, you look at theCUBE, we've been a remote studios, no problem. You're a software company. You've already really transitioned largely to a subscription model, so you can code remotely. But there are some industries and in particular industries where you guys sell a lot of product. I think about healthcare, you mentioned Telemedicine Meerah. Financial services, the Feds, big users of VDI, highly regulated and secure industries. While it's not you know your main thrust, you talk to your peers in those industries. So and I've always said you know some of these industries really haven't digitally transformed. They're actually kind of complacent. My feeling is that this is going to really accelerate you know some of those industries that haven't transformed and haven't been disrupted. I wonder if you could both, you know comment from both a technology perspective and a people perspective. >> You know I think from the people perspective it's really about mindset. And recognizing that how we approach these new problems and these new ways of thinking about getting work done is all about what our minds block us from thinking. And this pushed us into a situation where we've been able to demonstrate roles that we did not think could ever be done remotely, can actually be done remotely. And so for me it is about a mindset shift. It's about enabling the dialogue, sort of having the courage to have that dialogue inside of the organization to understand again what's the business context? What can we do in a more flexible way? And how do we continue to serve our customers the best that we can? >> I think for me it comes down to you know, protection is always in extinction, right, I mean if you're trying to protect a current model and you're trying to be, saying you know, you don't want to be the dinosaur. Things are going to change and being proactive about the change and embracing the change will let you, to some extent influence and control that change versus being the change being done to you. In this particular case, to me looking at it to see especially with today's technology around you know, manufacturing industry's probably going to see a lot of remote trends that while with IOT and robotics coming in. And I see there's going to be one area you may see a drift down on type of talent that's getting extinct. On the other side, we are going to continue to see the demand on technology is going to continue to go up. And especially which is already shortage I mean if I remember the last survey from KPMG in December, the CIO survey said 60% of the CIO's responded they are having challenges with you know filling the roles. And I also remember the other one is around country survey of technology talent shortage. By 2030 the expectation is we are going to leave something around 8.7 billion or seven trillion dollars of revenue on the table and 85% will be unfulfilled. I mean this is the time for you know, really how do you insure, there are industries that are going to transform which means there are certain skills people need re-skill. I mean, even in technology, the re-skill and the up-skill is good to be a constant thing that's actually it's, nobody is bit you know as far from that one in my opinion in today's world. So that re-skill and up-skill is going to, the one's who are going to embrace that, they're going to be in a bigger way, taking advantage of this transitions and transformation. I also think there are areas that we may see what we call the height may have a broader adoption. So you had mentioned about the chief data office, talking about how data can come in. I mean I see automation accelerating. And data is going to be a full component of acceleration and you will see more and more, you know things around how measurement becomes important as a start, that leads to you know more data modeling, that least to more automation. That cycle is going to accelerate. The influence of AI is going to actually even further than we have said. I just wish some of the areas with you know, we have been slow in adoption, a few have accelerated. Some of the challenges we are dealing with now with capacity, we wouldn't have been having problem. I mean when I did a reflection with my team, the one of the highest one ranked by my leadership was we should have accelerated automation more. >> Well I think was some really, really interesting and deep points. Really no industry is safe from disruption and really Meerah to your points, if you're just a paving the cow path, you're going to be in trouble. If you're trying to protect the past from the future you're going to get disrupted. And I feel like you guys really have a good handle on this and it's our pleasure to be able to host and interview such experts like yourselves. I really appreciate you're sharing your insights and your experience with our audience. I mean we're kind of all in this together. So thank you Donna, Meerah. Thanks so much for coming on theCUBE. >> Both: Thank you so much for having us. >> You're welcome and thank your for watching everybody. This is Dave Vellante for theCUBE for my CXO series. We will see you next time. (calm music)

(upbeat music) >> Announcer: Live from Las Vegas, it's theCUBE! Covering UIPath FORWARD America's 2019. Brought to you by UIPath. >> Welcome back, everyone, to theCUBE's live coverage of UIPath FORWARD, here in Sin City, Las Vegas Nevada. I'm your host, Rebecca Knight, co-hosting alongside Dave Velante. We have two guests for this segment. We have Kurt Carlson, Associate Dean for faculty and academic affairs of the Mason School of Business at the college of William and Mary. Thanks for coming on the show. >> Thanks you for having me. >> Rebecca: And we have Tom Clancy, the SVP of learning at UIPath, thank you so much. >> Great to be here. >> You're a Cube alum, so thank you for coming back. >> I've been here a few times. >> A Cube veteran, I should say. >> I think 10 years or so >> So we're talking today about a robot for every student, this was just announced in August, William and Mary is the first university in the US to provide automation software to every undergraduate student, thanks to a four million dollar investment from UIPath. Tell us a little bit about this program, Kurt, how it works and what you're trying to do here. >> Yeah, so first of all, to Tom and the people at UIPath for making this happen. This is a bold and incredible initiative, one that, frankly, when we had it initially, we thought that maybe we could get a robot for every student, we weren't sure that other people would be willing to go along with that, but UIPath was, they see the vision, and so it was really a meeting of the minds on a common purpose. The idea was pretty simple, this technology is transforming the world in a way that students, we think it's going to transform the way that students actually are students. But it's certainly transforming the world that our students are going into. And so, we want to give them exposure to it. We wanted to try and be the first business school on the planet that actually prepares students not just for the way RPA's being used today, but the way that it's going to be used when AI starts to take hold, when it becomes the gateway to AI three, four, five years down the road. So, we talked to UIPath, they thought it was a really good idea, we went all in on it. Yeah, all of our starting juniors in the business school have robots right now, they've all been trained through the academy live session putting together a course, it's very exciting. >> So, Tom, you've always been an innovator when it comes to learning, here's my question. How come we didn't learn this school stuff when we were in college? We learned Fortran. >> I don't know, I only learned BASIC, so I can't speak to that. >> So you know last year we talked about how you're scaling, learning some of the open, sort of philosophy that you have. So, give us the update on how you're pushing learning FORWARD, and why the College of William and Mary. >> Okay, so if you buy into a bot for every worker, or a bot for every desktop, that's a lot of bots, that's a lot of desktops, right? There's studies out there from the research companies that say that there's somewhere a hundred and 200 million people that need to be educated on RPA, RPA/AI. So if you buy into that, which we do, then traditional learning isn't going to do it. We're going to miss the boat. So we have a multi-pronged approach. The first thing is to democratize RPA learning. Two and a half years ago we made, we created RPA Academy, UIPath academy, and 100% free. After two and a half years, we have 451,000 people go through the academy courses, that's huge. But we think there's a lot more. Over the next next three years we think we'll train at least two million people. But the challenge still is, if we train five million people, there's still a hundred million that need to know about it. So, the second biggest thing we're doing is, we went out, last year at this event, we announced our academic alliance program. We had one university, now we're approaching 400 universities. But what we're doing with William and Mary is a lot more than just providing a course, and I'll let Kurt talk to that, but there is so much more that we could be doing to educate our students, our youth, upscaling, rescaling the existing workforce. When you break down that hundred million people, they come from a lot of different backgrounds, and we're trying to touch as many people as we can. >> You guys are really out ahead of the curve. Oftentimes, I mean, you saw this a little bit with data science, saw some colleges leaning in. So what lead you guys to the decision to actually invest and prioritize RPA? >> Yeah, I think what we're trying to accomplish requires incredibly smart students. It requires students that can sit at the interface between what we would think of today as sort of an RPA developer and a decision maker who would be stroking the check or signing the contract. There's got to be somebody that sits in that space that understands enough about how you would actually execute this implementation. What's the right buildout of that, how we're going to build a portfolio of bots, how we're going to prioritize the different processes that we might automate, How we're going to balance some processes that might have a nice ROI but be harder for the individual who's process is being automated to absorb against processes that the individual would love to have automated, but might not have as great of an ROI. How do you balance that whole set of things? So what we've done is worked with UIPath to bring together the ideas of automation with the ideas of being a strategic thinker in process automation, and we're designing a course in collaboration to help train our students to hit the ground running. >> Rebecca, it's really visionary, isn't it? I mean it's not just about using the tooling, it's about how to apply the tooling to create competitive advantage or change lives. >> I used to cover business education for the Financial Times, so I completely agree that this really is a game changer for the students to have this kind of access to technology and ability to explore this leading edge of software robotics and really be, and graduate from college. This isn't even graduate school, they're graduating from college already having these skills. So tell me, Kurt, what are they doing? What is the course, what does it look like, how are they using this in the classroom? >> The course is called a one credit. It's 14 hours but it actually turns into about 42 when you add this stuff that's going on outside of class. They're learning about these large conceptual issues around how do you prioritize which processes, what's the process you should go through to make sure that you measure in advance of implementation so that you can do an audit on the backend to have proof points on the effectiveness, so you got to measure in advance, creating a portfolio of perspective processes and then scoring them, how do you do that, so they're learning all that sort of conceptual straight business slash strategy implementation stuff, so that's on the first half, and to keep them engaged with this software, we're giving them small skills, we're calling them skillets. Small skills in every one of those sessions that add up to having a fully automated and programmed robot. Then they're going to go into a series of days where every one of those days they're going to learn a big skill. And the big skills are ones that are going to be useful for the students in their lives as people, useful in lives as students, and useful in their lives as entrepreneurs using RPA to create new ventures, or in the organizations they go to. We've worked with UIPath and with our alums who've implement this, folks at EY, Booz. In fact, we went up to DC, we had a three hour meeting with these folks. So what are the skills students need to learn, and they told us, and so we build these three big classes, each around each one of those skills so that our students are going to come out with the ability to be business translators, not necessarily the hardcore programmers. We're not going to prevent them from doing that, but to be these business translators that sit between the programming and the decision makers. >> That's huge because, you know, like, my son's a senior in college. He and his friends, they all either want to work for Amazon, Google, an investment bank, or one of the big SIs, right? So this is a perfect role for a consultant to go in and advise. Tom, I wanted to ask you, and you and I have known each other for a long time, but one of the reasons I think you were successful at your previous company is because you weren't just focused on a narrow vendor, how to make metrics work, for instance. I presume you're taking the same philosophy here. It transcends UIPath and is really more about, you know, the category if you will, the potential. Can you talk about that? >> So we listen to our customers and now we listen to the universities too, and they're going to help guide us to where we need to go. Most companies in tech, you work with marketing, and you work with engineering, and you build product courses. And you also try to sell those courses, because it's a really good PNL when you sell training. We don't think that's right for the industry, for UIPath, or for our customers, or our partners. So when we democratize learning, everything else falls into place. So, as we go forward, we have a bunch of ideas. You know, as we get more into AI, you'll see more AI type courses. We'll team with 400 universities now, by end of next year, we'll probably have a thousand universities signed up. And so, there's a lot of subject matter expertise, and if they come to us with ideas, you mentioned a 14 hour course, we have a four hour course, and we also have a 60 hour course. So we want to be as flexible as possible, because different universities want to apply it in different ways. So we also heard about Lean Six Sigma. I mean, sorry, Lean RPA, so we might build a course on Lean RPA, because that's really important. Solution architect is one of the biggest gaps in the industry right now so, so we look to where these gaps are, we listen to everybody, and then we just execute. >> Well, it's interesting you said Six Sigma, we have Jean Younger coming on, she's a Six Sigma expert. I don't know if she's a black belt, but she's pretty sure. She talks about how to apply RPA to make business processes in Six Sigma, but you would never spend the time and money, I mean, if it's an airplane engine, for sure, but now, so that's kind of transformative. Kurt, I'm curious as to how you, as a college, market this. You know, you're very competitive industry, if you will. So how do you see this attracting students and separating you guys from the pack? >> Well, it's a two separate things. How do we actively try to take advantage of this, and what effects is it having already? Enrollments to the business school, well. Students at William and Mary get admitted to William and Mary, and they're fantastic, amazingly good undergraduate students. The best students at William and Mary come to the Raymond A. Mason school of business. If you take our undergraduate GPA of students in the business school, they're top five in the country. So what we've seen since we've announced this is that our applications to the business school are up. I don't know that it's a one to one correlation. >> Tom: I think it is. >> I believe it's a strong predictor, right? And part because it's such an easy sell. And so, when we talk to those alums and friends in DC and said, tell us why this is, why our students should do this, they said, well, if for no other reason, we are hiring students that have these skills into data science lines in the mid 90s. When I said that to my students, they fell out of their chairs. So there's incredible opportunity here for them, that's the easy way to market it internally, it aligns with things that are happening at William and Mary, trying to be innovative, nimble, and entrepreneurial. We've been talking about being innovative, nimble, and entrepreneurial for longer than we've been doing it, we believe we're getting there, we believe this is the type of activity that would fit for that. As far as promoting it, we're telling everybody that will listen that this is interesting, and people are listening. You know, the standard sort of marketing strategy that goes around, and we are coordinating with UIPath on that. But internally, this sells actually pretty easy. This is something people are looking for, we're going to make it ready for the world the way that it's going to be now and in the future. >> Well, I imagine the big consultants are hovering as well. You know, you mentioned DC, Booz Allen, Hughes and DC, and Excensior, EY, Deloitte, PWC, IBM itself. I mean it's just, they all want the best and the brightest, and now you're going to have this skill set that is a sweet spot for their businesses. >> Kurt: That's the plan. >> I'm just thinking back to remembering who these people are, these are 19 and 20 year olds. They've never experienced the dreariness of work and the drudge tasks that we all know well. So, what are you, in terms of this whole business translator idea, that they're going to be the be people that sit in the middle and can sort of be these people who can speak both languages. What kind of skills are you trying to impart to them, because it is a whole different skill set. >> Our vision is that in two or three years, the nodes and the processes that are currently... That currently make implementing RPA complex and require significant programmer skills, these places where, right now, there's a human making a relatively mundane decision, but it's sill a model. There's a decision node there. We think AI is going to take over that. The simple, AI's going to simply put models into those decision nodes. We also think a lot of the programming that takes place, you're seeing it now with studio X, a lot of the programming is going to go away. And what that's going to do is it's going to elevate the business process from the mundane to the more human intelligent, what would currently be considered human intelligence process. When we get into that space, people skills are going to be really important, prioritizing is going to be really important, identifying organizations that are ripe for this, at this moment in time, which processes to automate. Those are the kind of skills we're trying to get students to develop, and what we're selling it partly as, this is going to make you ready of the world the way we think it's going to be, a bit of a guess. But we're also saying if you don't want to automate mundane processes, then come with us on a different magic carpet ride. And that magic carpet ride is, imagine all the processes that don't exist right now because nobody would ever conceive of them because they couldn't possibly be sustained, or they would be too mundane. Now think about those processes through a business lens, so take a business student and think about all the potential when you look at it that way. So this course that we're building has that, everything in the course is wrapped in that, and so, at the end of the course, they're going to be doing a project, and the project is to bring a new process to the world that doesn't currently exist. Don't program it, don't worry about whether or not you have a team that could actually execute it. Just conceive of a process that doesn't currently exist and let's imagine, with the potential of RPA, how we would make that happen. That's going to be, we think we're going to be able to bring a lot of students along through that innovative lens even though they are 19 and 20, because 19 and 20 year olds love innovation, while they've never submitted a procurement report. >> Exactly! >> A innovation presentation. >> We'll need to do a Cube follow up with that. >> What Kurt just said, is the reason why, Tom, I think this market is being way undercounted. I think it's hard for the IDCs and the forces, because they look back they say how big was it last year, how fast are these companies growing, but, to your point, there's so much unknown processes that could be attacked. The TAM on this could be enormous. >> We agree. >> Yeah, I know you do, but I think that it's a point worth mentioning because it touches so many different parts of every organization that I think people perhaps don't realize the impact that it could have. >> You know, when listening to you, Kurt, when you look at these young kids, at least compared to me, all the coding and setting up a robot, that's the easy part, they'll pick that up right away. It's really the thought process that goes into identifying new opportunities, and that's, I think, you're challenging them to do that. But learning how to do robots, I think, is going to be pretty easy for this new digital generation. >> Piece of cake. Tom and Kurt, thank you so much for coming on theCUBE with a really fascinating conversation. >> Thank you. >> Thanks, you guys >> I'm Rebecca Knight, for Dave Velante, stay tuned for more of theCUBEs live coverage of UIPath FORWARD. (upbeat music)

(upbeat fast paced techno music) >> Narrator: Live from San Francisco, celebrating 10 years of high tech coverage, it's The Cube. Covering VMworld 2019. Brought to you buy VMware and it's ecosystem partners. >> Welcome back everyone. Cube, the coverage here VMworld 2019. I'm John Furrier. Dave Vellante. Dave 10 years covering The Cube. Lots changed. The game is still the same when it comes to storage back in recovery. Got some new stuff too, some great news. Two great guests. Cube Alumni Shay Mowlem who's the Senior Vice President of Product Strategy Rubrik. Chris Wahl, Chief Technologist at Rubrik. Guys, welcome back to The Cube. >> Thanks. >> Good to be here. >> The game always is getting better in terms of modernization, that's the big trend. Digital transformation their are talks about that, but cloud impact has been something that you guys been riding the wave like I said, great success. I don't think you guys have been classified as a startup anymore, you're more in high growth mode. Let's cover the news. What's happening with the announcements here at Vmworld? What's the big news? >> We announced our new release of Andy's 5.1 and really breaking new ground and expanding our position into new markets around data governance, disaster recovery and we're also bringing in continuous data protection as a core capability of our product. Really excited about it. These are areas that have generally been addressed through sort of separate siloed approaches, and we see a lot of synergy with backup recovery and brought it all together as part of this offering. >> How's the news going over? >> Oh it's been great. I mean if you look at data governance, everyone is struggling today with privacy. How do you discover personally identifiable information in your backup archives? Very hard problem to solve. Generally people do spot audits and checks. We've just made that really easy. Streamline with a backup process. It sort of naturally fits there in some ways 'cause I'm backing it up, why not process that data to discover? Sends that information and classify it and our customers are really excited about that. >> Chris, talk about the architectural shift. 'Cause one of the things that we were observing in our opening day analysis is storage is still a hot startup sector. I mean, storage is not storage anymore. It's evolved. We were even joking this morning with Nvidia and Dalium C guy around H, VDI. That's not VDI anymore, it's user experience. Storage specifically with cloud has certainly changed on premises. Everyone now recognizes hybrid finally as standard, not going away. But the operating model is requiring a new architect, 'cause you can't just take the old and recycle it into the new. We'll talk about what that is specifically and why it's important. >> Yeah and I'll kind of tie that back to what we're talking here with cloud data management. It's kind of this acknowledgement that the way we did IT back in the day, where the storage food group was completely isolated, things went into it, things came out of it, but it wasn't part of that kind of overall architecture. Especially when you start talking public cloud and whatnot, that was just to kind of acknowledge that this model of IT just isn't going to carry us forward, and that's similar to the process of let's take all this backup data with Rubrik, let's index it, inventory it, really start to understand what's going on and use that as like the jet fuel that actually powers our Polaris platform and all of our data management applications. I think that all starts with storage. We had to have that data, add a primary into some secondary location, keep it very efficient, figure out how it's going to get from one place to the next. That used to be data centers, now it's clouds and back and forth. >> It's funny, these sacred cloud categories, backup recovery idea. It's data. I mean, this is a data problem. It's data, it's value is in data. You're seeing platform kind of thinking coming in. We talked about this in Palo Alto in our studio when you came in. >> Yes we did. It's a platform thing, it's not just this tool or siloed approach. >> Absolutely. That was when we spoke last, I had recently joined Rubrik back then. Our vision had always been, this is high value data. Yes, we're going to build back up in a way that is quite revolutionary, but how do we create more leverage out of that data? We're starting to see actual execution to that, both with our radar product ransom where recovery, sonar for data governance, orchestrated DR, exposing more and more value out of that data and it's really connecting. >> I'd love to come back to the announcement, the Andys announcement. >> Shay: Yes. >> You talk about governance, DR, and CDP. You're right, these often times would be point products, but explain to people sort of the before and the after. >> Shay: Sure. >> That you try to, when you walk into an account, you might see like I say, different point products. How are they transitioning? Maybe you could add some color there. >> Yeah absolutely. With data governance, everybody's, everyone's got deal with it today at some level. I use privacy as an example, but truly we all are impacted if you're in health care you've got HIPPA. If you're dealing with financial data, you've got PCI. Generally, the backup data has been somewhat of a black box. The only way to really check it, is to do sort of a spot audit check. It's labor intensive and hard. We're streamlining that process for our customers and incorporating it as a value add on top of what they're doing with backup and I think that's solving a major pain point. On DR, same thing. Separate silo today, generally different product lines, but backing up core objects, VM's, databases and application stacks, which is what you're really trying to do with a DR solution, you know there's a lot of synergy there. We're helping to just bring that synergy together into this integrated platform approach. >> You guys are doing some machine learning. I saw in the news around classification you mentioned it, index. It sounds like a search engine, but again to my point about these categories kind of being broken down, this platform, you guys are using machine learning to do some classification around protecting against breach. Is that right? Could you guys just drill down on that a little bit? What's that all about? >> Yes, so we use machine learning in a variety of ways. In our radar product, our ransomware recovery product, we us it for not only detection of changed patterns in the data. Ransomware techs generally involve people coming in, updating, deleting, encrypting your data. We look at the changing profile of the data, and alert allonomous behavior, and then recover it back to the last stable state. With our data governance product, we're also learning machine learning to discover that PII information and trying to really help find a very rich accurate way of detecting that data. >> So, to killer apps, one Ransomware which, big problem. I mean, you just, you can't look a day without seeing major ransomware. The Texas thing to me jumps out. Coordinated attacks. I even speculate, that's cybersecurity related. Some would say there's some stayed actors on that or sanctioned groups doing that, but that's, again I'm with conspiracy theory on this one, but that's Ransomware. Killer app. Compliance, kind of a boring category, but super important because of the penalties. I mean, compliance is an issue. Huge. >> Absolutely. I mean, you look at GDPR in Europe, compliance bossies here in this country across various verticals. Everyone's dealing with it in some form or another, and there's no reason why that should be a separate sort of process. Why not leverage the data management, like what is being provided by Rubrik to deliver on that? >> Here's another question on DR. One of the complaints that you hear, maybe not complaints, but observations when you talk to practitioners, is they can't test their DR. They can test the fair load, but they can't test the fail back 'cause it's too risky. >> Shay: That's spot on, yes. How do you address that problem? You're all about your modern data management, simplicity cloud. Describe how you solve that problem. >> That's a very, very powerful question Dave and it's so true. Traditionally, customers that are using on prem DR systems need to set up the infrastructure, the people, the processes. It's very labor intensive and expensive, so you can only do it a few times a year max and that's how you know that your DR system is operational. You don't want to discover that there's a problem when there's an actual DR happening. Our approach basically takes the full application stack that you want to protect, we convert it for you into a cloud native format and we can instantiate any one of those snapshots that we're taking that full application at any point in time, in the cloud for you to verify and test and we streamline that process, fully orchestrated. If you choose to keep it in the cloud, we have a cloud native approach to protect it and then you can fail back to your on prem system. We've just streamlined this process in a way that really helps our customers do DR test in a much more frequent basis without that operation burden and challenge that they're dealing with today. >> Talk about, Chris, this Rubrik build open source initiative. Because I want, it's interesting. First explain what is Rubrik build, what's it all about. What's the philosophy behind it? >> I'll take you back a few years, when I was interested in joining Rubrik. The one major defining characteristic of the product that really tugged my heart strings, was a restful set of API end points for everything. Doesn't matter what the product does. Anything you click it's always calling a restful API. That goes to a pain point that I had a a customer, was automating, we'll say any kind of backup product, but a lot of things in the infrastructure space was like smashing my face against a hot iron. (chuckles) >> Chris: You know, it's just not pleasant. >> Bad visual too. >> Chris: Exactly, so I'm thinking- >> I've never tried that. (laughs) >> Do not do that at home. >> The analogies, that's my one gift to the world. >> You need restful API is what you need. (laughs) >> Cute. So, finding a product that not only had them, but wanted you to consume them, made them available across every feature, click whatever existed, was very, very powerful for me and a lot of other people that I work with. Fast forward a few years, we developed quite the library of different source projects for integrating with things like ServiceNow and vRealize and anything that does things from configuration management, all the way to infrastructures code, and we would go talk to customers about these things. You had two camps of people. Either, I need the 100 level stuff. I've never dealt with CIDC Pipelines, automation, unit tests, pull requests, what is GitHub? All the way through, I know all that stuff, give me the use cases. What can I do with your API? We wanted to develop Rubrik Build as kind of a teach you how to make the champagne, and teach you how to drink the champagne. The idea is, all of our software development kits, our eco integrations and our use cases, are bundled into this very friendly ecosystem where it's all open source, we have quick start guides, educational materials, and a number of folks that are on the engineering and marketing teams that are engaging with people that either don't care much about cloud data management and just want to learn kind of the automation dev ops world of things, or are very keep to learn more about CDP >>and stuff like that. So Rubrik employees donating the code for open source. Did you guys create the project? Was it community driven or how was that structured? >> It was kind of three slices. It could be from Rubrik. We built this thing like an SDK. We obviously own and support that. It could be someone found our SDK, and wanted to write a third party integration. Heck, even Microsoft wrote a system center ops manager plugin and hosted on their GitHub site. Or it kind of something in the middle where working with like a red hat on their Ansible integrations is an example. >> What other kind of innovations have come out of that? You mentioned Microsoft doing the GitHub. Are there sort of things that have come out of it, or things that you're hoping to come out of it? It's hard to predict, I know. >> We've had the predecessor of the DR product that we released or announced, was actually born in open source. Many years ago, I had a customer saying, I'd really like to automatically do DR tests like every night, for the se five critical apps. We have the API's, we have the ability to live mount work loads, we tie into the cloud, I was like, there's no reason we can't do this. We had that kind of bit more, manual process, but it does the job years ago that we developed as a use case doing Helper Different Languages, fast forward now it's a product. You can kind of get to see that evolution from idea to sort of hacking on things to get them to work, to now it's a full product and you can just push the button and everyone's going to love that. That's one example. >> Very cool. >> Talk about the Vmware relationship. What's the status? How long have you guys been working with VMware and the ecosystem, and what are some of the new things that are developing in the relationship? >> Yeah I mean, this is a deep relationship. It's been a critical one from the beginning of the company. We integrate and support, and are certified across a variety of solutions. Obviously V Center and in this latest release with our continuous data protection, we've done that in a way that is a certified, approved approach and I think that helps us really build a confidence and deliver this sort of excellent overall experience that our customers are looking for. >> They got that open source aspect too, that's pretty hot right now with the cloud native stuff going on, that's pretty relevant. >> Shay: Absolutely. (chuckles) >> All right well we got to ask, with multi-cloud everything here. What's your guys point of view on multi-cloud? Real? BS? Somewhere in the middle? Time will tell? What's your thoughts? >> Definitely real. I'll add color. I mean, I think- >> Dave: Yeah, thank you. >> Absolutely. (laughs) we used to talk about hybrid just a few years ago and that's still real too, but we see a lot of customer looking at leveraging best in class for different work loads and different services across multiple clouds, and our vision it to be the data management platform of choice across all of that. Enabling that choice, and giving the excellent sort of cloud native experience that they're looking for as they deploy different work loads in these different environments. >> Just share with us. We've been talking at The Cube a lot. There's a lot of us who believe this, that certain parts of the multi-cloud are on the BS side. Now there's that vision that any app can run anywhere without recompiling, without retesting. That's aspirational. Then you're going to need a lot of homogenous infrastructure to do that. The one area that I do think that you can standardize on, is what you guys call a data management, or backup, that you can actually say, okay we're going to mandate that this is the platform that we're going to use across all clouds, and that actually will work technically. >> Chris: Yes. Some of this other stuff, I'm not so sure. >> If you have a control plane, if you will, with data management entities that live on prem as well as localities that are available across public cloud, then it's really just a choice of why do you want to put the data there. We're driving that through our serviceable agreement domains or isolated domains where you can say, this data needs to live in Germany. It needs to be in this particular data center forever, where this one needs to replicate to between France and London, something like that. You can make those choices based on what you're trying to achieve, more around non technical decision making, than actual technical decision making. Which I think has really been kind of, you call the BS versus no BS. It's like, are we trying to do this because we can or because we need to do something? That's to me, the decision between BS or not. >> Well, it's customer driven too. The use cases will drive it. For instance, a security requirement might be build our own stack, I want to be on this cloud, have a backup cloud or the work load might have certain requirements, but again I think the data question's a good one. That's going to be independent of- >> I want to test it with the technologist because if you have, let's say you have outposts and you got Azure Stack, Cloud Customer, whatever, and you think you're going to run apps anywhere and that's not going to happen anytime soon anyway. However, if I want a data management solution across all those, actually that can work. Right? There's not reason it can't because you'll write to their API's, you'll take care of that. >> You're saying that today with like Kubernetes deployments. They're not all the same, but they, everybody's got an offering in there and everyone has a full suite of API's that you can plug into. I do agree that things like data management not only can, but should be ubiquitous across localities. It shouldn't matter where you're at, the experience should be roughly the same. >> It's not that disruptive to say, okay rogue division, we're going to swap out and you're going to go standardize that. >> That's usually where the multi-cloud comes from. (chuckles) it's kind of involuntary. You got two teams, just chose different things. >> Right, right. >> While we got the brain trust on the key here, I want to pose another question for you that I mean, we're going to relive the video tape five years from now when we're going to see it, how it all turns out. (laughs) one of the things we've been kind of talking about here on The Cube, but also leading up to Vmworld this year is Cloud 2.0. Mainly around the following premise. Cloud 1.0 with being defined as AWS, DevOps, Agile, Lean Startup, all that stuff that was we all love in DevOps, compute, storage, scale, all the goodness that came from that. Cloud 2.0 is more of an enterprise cloud kind of configurations, so with that kind of, where networking and security and data are now kind of in the architecture. I want to ask you guys, if that's the premise of Cloud 1.0 was DevOps pure cloud native, born in the cloud, what's your definition of Cloud 2.0? Because a lot of people are looking at it from that simple lens, just trying to simplify that the requirements are changing, the architectures are different, the backup can work multi-cloud but this can't, so there's a lot of moving parts now in this enterprise hybrid world, so what's your definition guys on Cloud 2.0? >> I think increasingly you're seeing the landscape of the infrastructures you pointed out evolving the use of different services across clouds evolving. What's really important is that solutions like data protection don't limit your ability to capitalize on that in our minds, and so we want to build this ubiquitous sort of policy, engine and governance around how to protect my assets and enable whether it's containerized, application stacks that are being delivered or new private cloud deployments that we are not getting in the way of that in any way at all and allowing our customers to sort of broaden and leverage best in class services. >> Chris, what's your definition of Cloud 2.0? >> I'll take us back I mean, we saw this with virtualization. We saw everybody go, oh my gosh! I can get all this capacity used, and all these new services and just going bonkers, and that's where we had like zombie virtual machines and all these other terms that we don't really throw about anymore, but it was the Wild West. Everyone was just land and expand, and we kind of did that with cloud in a lot of cases. You're like, oh look at these new shiny's that I can play with, and now you're absolutely right. It's what about rollback status control and user security? My S3 bucket got hijacked. Ransomware is tearing through. You can now ransomware video cameras and things like that. It's a pretty terrifying world and I think this is that moment, where we take a look back and say, well is it highly available? Is it secure? How do I know that? How am I able to recover from availability or even external threat issues? To me, that's where most of the conversations we have are hard. >> Yeah it's the transformative opportunities is all intoxicating. Oh, this is great, but the reality is, it's not as clean as going to the cloud. >> Chris: Give me something that you know will work. >> I got to build the system out. It's an operating environment. >> Yes. >> Yeah. >> Totally agree. You guys are doing great. Thanks for the commentary and insight on Cloud 2.0 and multi-cloud, >> Pleasure guys. and congratulation on your success at Rubrik. Thanks for coming on sharing the insight. It's Cube coverage here at Vmworld 2019. More after this short break. (light techno music)

>> Announcer: From the heart of Silicon Valley, it's theCUBE. Covering CloudNOW's seventh annual Top Women Entrepreneurs in Cloud Innovation Awards. (upbeat music) >> Hi, Lisa Martin with theCUBE, on the ground at Facebook Headquarters. We're here for the seventh annual CloudNOW Top Women Entrepreneurs in Cloud Innovation Awards. Welcoming one of the award winners and a CUBE alumni to the program, we have Tongtong Gong. You are co-founder and COO of Amberdata, Tongtong. Welcome back to theCUBE, and congrats on the award. >> Thank you, thanks for having me Lisa. >> Our pleasure. So, you've been on theCUBE before. We'll talk about Amberdata in a second. And I love the name, so I want you to tell us a little bit about that. Health and intelligence for blockchain, but one of the really interesting things about you is you are a technical female co-founder of a venture-funded company. A lot of words there, huge accomplishment. >> Tongtong: Thank you. >> Tell us about the inspiration. What was the opportunity? Was it your idea? Was it your co-founder's idea? How did this opportunity for the technology come to fruition? Then how did you, as a female, go and lead and get funding for this technology? >> Wow, how much time do I have? I can talk all day on this subject. So, it all started last 2017, summer. I was just very intrigued with blockchain technology and the potential of how blockchain can change our life and take our identity, assets, have full control, remove intermediaries. I had a full-time job at that time, leading engineering for a startup company, and I just don't have enough time in the day to learn about this new technology and what's the better way to do it, and then jump right in, start own company, and start from blockchain data. So, my background is in data analytics and computing, and when I start learning blockchain, I realized blockchain data, it's stored, it's immutable, but it's really hard to access. It's really hard to analyze. It's really hard to process without all the tools that we all know and comfortable with. So, me and my co-founder at that point were going back and forth with this new technology and the opportunities. I think it's his idea. Let's do something with the data that's stored on blockchain. Amberdata, the company's name, it's because Nick Szabo did a podcast with Tim Ferriss and Naval about blockchain is a fly trapped in amber. Upon layers and layers of amber solidified and the bubbles and the fly, you can still see it but it's immutable. You can't change it anymore. So, we're like, what brilliant name is that, right? >> Lisa: Absolutely. >> Amberdata. Without a tool, a platform like us, you can't possibly count all the bubbles in the amber. We help you extract the bubbles from the amber, the flies from the amber, and analyzing it. And that's what we do. >> Wow, that's a great analogy, a great name. Health and intelligence for blockchain. Blockchain is a very hot technology topic. Every company out there, whether they're a startup born in the cloud or legacy enterprise, wants to be doing something in blockchain. As a female co-founder, was that an advantage for you when you went in to venture capitalists looking to get funding? What do you think some of those advantages were? >> Honestly, I always consider being female is an attribute of me. It's not the definition of me. My gender doesn't define me. It doesn't constrain me. It's just who I am and I'm also engineer. I'm also incredibly curious all the time. I'm also bubbly. I'm also a wife. I'm also a daughter. So, there's just many attributes of me. When we start a company, we went into lots of friends and VCs and Meetups and we'd talk to anyone about our idea. Looking for advice, looking for validation. That's really what led us to get the funding. >> I love that. One day I hope we'll be to a place where gender doesn't define us but we know the numbers in females in technical roles. But it sounds like one of the things that you leveraged, maybe, were some of those softer skills. You're very personable. You had a great idea. You clearly have passion for it. Building your own groundswell with Meetups and a network seems like one of the key initiators of your success. >> Now you put it that way, I think so. I never thought about it that way. Yeah, 'cause in the beginning, you really try to define and refine the idea and the product. Are you solving a problem? What is the problem that you are solving? You really can't get answers unless you talk to lots of people and I think, perhaps, being a female, it really helps me just to talk to people all day long. >> It's good that you can do that. Genetically, I think we both have that in common. Tonight, as we wrap up here, you're presenting in front of Sheryl Sandberg, who is probably one of the beacons that women have globally. Not just in technology, she's obviously written some incredibly inspiring books about a number of different life situations. You must be pretty excited to have the opportunity to not only be a co-founder but to be recognized by this award and have somebody as prestigious and inspirational as Sheryl in the audience. >> Absolutely. I have both her books, Lean In and Option B. I actually bough both books in Chinese version for my mom, as well. So, I have four copies. I'm a huge fan of Sheryl. I think she's very inspirational about leaning in and take a seat at the table. One of my friend, Jamie Moy, once said, "Girl, let's forget about taking a seat. Let's create a table. Let's create a seat for other people." >> "Girl, let's create a seat." I love that. Tongtong, thank you so much for stopping by. Congratulations again on the award. >> Thank you. >> And we look forward to having you back on theCUBE again, talking more about what you're doing with Amberdata. >> Thank you for having me. >> We want to thank you. You're watching theCUBE. I'm Lisa Martin from Facebook headquarters. Thanks for watching. (upbeat music)

[Narrator] From the heart of Silicon Valley, it's the Cube. Covering Cloud Now seventh annual Top Women Entrepreneurs in Cloud Innovation Awards. (techno music) >> Hi, Lisa Martin on the ground with the Cube at Facebook headquarters at the seventh annual Cloud Now Top Women in Cloud Innovation Awards. We are here for our third time with the founder of Cloud Now, Jocelyn Degance Graham. Jocelyn, it is great to have you back. Great to be back here for your seventh annual Cloud Now. >> We are just so delighted to be here with you Lisa and the Cube and all of the support and wonderful help that you've given us through the years for this event. >> So you have a lot of firsts that I wanted to cover and I know we've just got a few minutes of your time. Seventh annual, as I mentioned. >> Jocelyn: That's right. >> Your Cloud Now community now boasts over 1500 members. There's over 300 attendees here tonight. >> Jocelyn: That's right. >> And tell us what was really unique about how easy it was to attract this audience. >> Well this, we've never had such a great response for this event Lisa. And some of that could just be the timing. It is finally an idea who's time has come, right? And so there just seems to be such a groundswell of understanding the importance of inclusion and diversity. And beyond that actually creating belonging, right? So more and more, I feel like there's such an actual enthusiasm that we hadn't seen before. So this year, we didn't actually publish tickets or let people know that tickets were available. Everything was essentially sold through word of mouth. And so, we never even published any tickets. And we sold out of the event. And that was definitely a first for us. >> Another first is being here. >> Yeah. >> Not only being here at Facebook headquarters in Menlo Park California, but also having Sheryl Sandberg as one of the keynote speakers this evening. >> It is such an honor. You know she is one of the women who has just been so important in terms of the Seminole movement of women in tech. Like many women, I read her book, Lean In, years ago. And the fact that she's here with us tonight at the event, after having inspired an entire movement, is really significant and we're just thrilled. >> Another thing that's really interesting and a unique first for Cloud Now this year is you're recognizing 10 female tech entrepreneurs who are technical founders. >> Jocelyn: Technical founder, venture backed. >> Of venture backed businesses. >> Jocelyn: That's absolutely right. >> Tell us about how you've been able to achieve that because their backgrounds are diverse and the technologies that they're designing and driving are really incredible. >> This is one of the most, I think, exciting firsts about the event this year is in past events, we were recognizing women that had made major contributions in a technical field. And we were recognizing women regardless of the level or role or responsibility in the organization. Now we had largely done that because there were so few female founders of venture funded startups. This year was an absolute breakthrough year for many different reasons. There are organizations now like Allraise.org that are supported by women VC's. And there just seems to be an entire groundswell of female founders and we were able to, this year for the first time, align the criteria around female technical founders. And I'm really hoping that moving forward we'll be able to continue with that as more and more women realize that they should be starting businesses and they can get venture backing. >> And we're excited to talk to those winners tonight and ask how did you go about doing that? What were your inspirations and how do you kind of combat those fears and just the history of the challenge of getting funding there? Another thing that I noticed on the Cloud Now website is one of your taglines is together we can make a difference. In, you know, just the last minute or so give me some examples of how you're helping to make a difference that really resonate with you and that give you inspiration for your 2019 goals. >> That's such a great question. So for me, really one of the most heartening things about the organization is that the work we're doing together and through our scholarship program. So we're identifying the next generation of both female and minority leaders in tech and we're investing in them through our stem scholarship fund. This year, we have funders. Our funders include Google, Intel and Facebook. And we're really hoping to be able to expand that scope next year, Lisa, to increase the number of students we're helping. This year we're also, in addition to women, we are helping minority students as well. And for next year, we're wanting to expand those categories even further and being able to support people with disabilities. So we're really hoping that to create this kind of very strong fabric of the community coming together and really giving each other support. >> Jocelyn, thank you so much for having the Cube back for the third year in a row and congratulations on the groundswell that you're capitalizing on and that you're helping to create. We congratulate you and we appreciate your time. >> Lisa, it's always a pleasure. I love speaking with you. Thanks so much for coming. >> Likewise, we want to thank you for watching the Cube. Lisa Martin on the ground at Facebook headquarters at the Cloud Now Top Women Entrepreneurs in Cloud Innovation Awards. Thanks for watching. (techno music)

>> Narrator: Live from Las Vegas, it's theCUBE. Covering Dell Technologies World 2018. Brought to you by Dell EMC, and its ecosystem partners. (techno music) >> Hey, welcome back to theCUBE, day three of our coverage of Dell Technologies World. I'm Lisa Martin joined by John Troyer, and we're excited to welcome back to theCUBE, distinguished alumni Bask Iyer, the CIO of Dell Technologies and VMware. Bask it's great to have you here. >> Thank you, thank you very much. >> So we were joking before we went on that we're right next to the therapy dog area, so always nice to have a technology conversation populated with dogs barking. >> No I like the dogs better if you want to talk about dogs or guitar, I would rather prefer that over >> Oh I could talk about that all day. So talk to us about, you are the CIO of Dell Technologies and VMware, first Dell Technologies World, 14,000 attendees >> Right. >> In person. >> Yep. >> 6,500 technology and solutions partners here, another expected 30,000+ people engaging with the livestream, the on-demand videos. Big, big focus this week. Love to get your perspective on the role of the CIO, the role that you have now, you know you a few years ago, it was truly all about technology, now it's really about your involvement in the corporate strategy. Talk to us about the vision that you're setting, with Michael Dell, with your peers in IT and other stakeholders at Dell Technologies. >> Okay. No it's a great event I love this. A lot of these are colleagues, other CIOs. So they know, they want to know really do you use it inside Dell. A lot more credibility when you talk real stories about how you use it in Dell. The first thing is when I started this career there was no such title as CIO. That itself is pretty new. We were just the geeks who kind of ran everything. And then you became head of IT. So it was very strongly technical, and then they said you needed leadership and business skills, the pendulum swung one way to all business and leadership skills and no technology, and then came back to we should need both of that. And then you have business and general management, so every year the job changes. What I'm finding though, which is good and bad, is nothing goes away. You still need to know the technology, you still need to know the business skills, soft skills, still need to be a general manager. What is now is a lot more on the strategy. So the importance of strategy though is you never talk strategy if your operations is not good. Right nobody cares. But if your operations is somewhat good, you better not talk about operations. So I tell people don't keep on saying your trains are running on time. It has to run on time, if it doesn't, if it runs recently on time, talk about strategy. So now it's an important job to do that, and your question about in a technology company, I am the customer. I'm probably one of the very few people who actually signed a purchase order within Dell Tech to buy Dell or EMC or VMware. So they're interested in the customer's perspective. So you're the internal voice of the customer. We are also using all the tech that we make, and we need to give feedback to the developers and the R&D folks. So we call it drink our own champagne, but not our own Kool-Aid, you know what I mean. >> I like that. >> So sometimes you get carried away by the marketing things that we do. The challenge though is you working with Michael Dell, you're working with Pat Gelsinger and everybody else, and thousands of engineering fellows and so on, who know IT, who've invented a lot of things in IT. So you cannot really keep up with them. You know you need to know enough to hold your own, but if you try to compete with them, that is not a good thing. So luckily for me I was a good B student, I'm comfortable with A students around me. So you have you to be comfortable that you're not the smartest one in the room, but you're still contributing. That's the change you have. It is surreal to go in front of a Pat or Michael or other people and talk about digital transformation. And they're making eye contact they want to know how, what do you mean by digital transformation? How do you do it internally? What's your plan? So every once in a while you pinch yourself and say I can't believe this is happening. But it does happen. >> So Bask, I mean digital transformation is a theme of the show, right? >> Yeah. >> Make it real. As you talk with other CIOS, do they feel like they have a seat at that table? Are they the driver, are they the implementer? You start to hear more about a Chief Digital Officer, is that, does the CIO became the CDO, are they different? Do you have any thoughts on that? >> Yeah I'm very strong on the fact there's a again if the CIO focus only on operations and cost, then people say your trains are running on time lets get somebody clever to do the innovation and digital. You don't want to leave that, that is the cream of the crop. So I think if you're a good CIO, you want to be the Chief Digital Officer for the company. You don't want to have two CFOs, one for Wall Street and one for doing the real work. You don't want to have two salesperson, one for putting the numbers and one actually selling. So you need to have one technology person. Some companies may be so complex that you may consider that. I started as a chief Digital Officer in Hunnewell, ended up as the CIO for Hunnewell for example, but you need to have people who are very collaborative, those two have to work very closely together. It's very difficult to find one person who's collaborative and nonpolitical to be a leader of an IT organization. To find two and working as a team is complicated. So that's what I want. So I'm not a big supporter of that although I could see why it would happen, if you will. Okay. >> Lisa: So drinking your own champagne I like that by the way, you are in this role, it's interesting that you say you still kind of feel like you're pinching yourself when you're talking to a Michael Dell or a Pat Gelsinger, but you're up there having to implement digital transformation within Dell Technologies and all the companies underneath. >> Sure. >> That's a pretty big seat at the table. How are you sort of embodying the theme of this event and making digital transformation real for Dell Technologies? >> So I go very practical and I give, yesterday I talked to my fellow CIOs on the mistakes I've made. Right I came as the VMware CIO, we've already done this journey in a couple of years ahead of time. So wouldn't it be a cut and paste? Given the hybrid cloud, given the best end user environment possible and you're done. You already have that start. But I made the same mistake every CIO makes, we preach this but we don't follow it. It's not just the technology, it's people, process, culture, and technology, and I jumped on the technology, and I'm kicking myself to say, first three months didn't make a whole lot of progress. I was just yelling like a madman to say why is it not getting done. And then you have to go back into I have to hire the right people. So lets talk a few things. I made changes to the leadership team. Certain people were not comfortable in the pace of change. We did it respectfully but we had to have people who can actually lead the change. That was first. Then we called something about putting T back in IT. Which a long time in IT what we have done is we've outsourced, off shored, treated IT as a commodity and then we have program managers and leaders. Every magazine asked us to do that. Well, guess what we've been wrong. I think I've been wrong, doing that. You do need technologies right now. You cannot do digital transformation without understanding the technology. So we have to staff internally, we have to get good folks. Still manage the cost right, that doesn't go away, but you have to do the right thing. So IT, first get the right people, the process for it, what it dawned on me is we are talking about Agile and DevOps and continuous development. Those are all IT, geeky terMs. Those are not business terms. Those are not business terms even in Dell technology. Because there are manufacturing folks and HR folks and finance folks and so on. So I looked at fast experience of somebody like Hunnewell or GE. Remember they adopted Lean Six Sigma some kind of process to transform their company. And even me who's an IT geek had to go through a green-belt certification or a black-belt certification. And I revolted I said why would I do that, I'm an engineer why would I go through this stupid course, but it was required otherwise you don't get promoted. So now you need a prescriptive process to change the culture. So digital transformation needed that. Luckily for us we took the pivotal way, which we have within our company. We made it the Dell Digital way, since you still have to write it in your own language if you will. That is the process we use, we train our folks and our customers, our clients as I call them, customer is the person who buys the products from us, client is all the colleagues. So finance folks have to know what Dell Digital way is. You cannot do requirements the old way, and throw it over the wall and expect me to develop. You have to get into the room, With me and draw it on the wall and be able to design it together. So that's been a good change. And the culture changes with us because initially people are thinking, this guy's coming from Silicon Valley, he's not going to stay here, he's going to do all these things, he's going to get either fired or leave. So people try to run out the clock a little bit. So it takes a little bit of time to work on the culture and say innovation is not only demanded from you, but you have to keep the trains running on time. You have to chew gum and walk at the same time. So that's the process we go through. >> I love what you just described Bask because both in terms of culture and in technology, that actually makes for an interesting set of IT careers, right. That turns IT into a very interesting career again. >> Right. >> Many of my colleagues are IT pros, do you have any advice for somebody who is maybe in the start, the middle of their career, maybe specializing in something but they have I think this dream at the end of the tunnel, maybe the CIO is where they want to be. What do you see, how do I prep to be a CIO now, to be a CIO in say ten years? >> I'd tell him are you crazy? (laughs) Do you know what you're getting into? But here's what there's some truth to it. Getting a job is really easy I think. Doing the job is very difficult. So I tell 'em, get prepared for the job. Also, you should have some passion for technology. If you're a sportswriter, I mean I'm into sports, so you can give me all the magazines you want, I can see all the videos, I can watch 'em all day long. I can retire just watching sports all day long, or playing occasionally. You have to have the passion in technology because things keep coming at you. So we think Blockchain is cool by the time it get off the seed it's going to be something else. You have to be interested and passionate to keep up with that, right. So first thing is can you keep up with the change. Are you actually interested in it? Michael Dell sends you a text in the middle of the night, I don't think he expects me to react but I do. Because he's reading something and he's hearing something from the customers. You need to be interested in learning. So I said you have to be a lifelong learner, passionate on technology, and also learn the ropes because I always felt when I was younger I wasn't given the opportunities at the right time. I felt like am I going to die before I become a vice president or a CIO or whatever? It felt to me that it took a little longer than I wanted it to but thank god because once you got the job you were prepared for it. So that's one of the things I tell people is get prepared. Get into learning. Also the job changes all the time so I can't really write a book on it. You have to almost be like a chameleon in a sense. You got to learn so the last few years was technology, then it was business, then it was soft skills, transformation, ERP implementation, now it's business strategy, it's not going to stop. Technology is going to keep coming as a wave. So be ready for adapting and adopting to the changes if you will, right. >> I'm glad that you brought up people because it's not just systems and processes, none of this comes to fruition, companies don't transform IT, transform digitally, deliver more differentiated products without the people. We had some folks on earlier I think day one with Dell EMC Education Services, we've talked to the Channel folks about the things that they're enabling and one of the things that I think is really important that you brought up is all the things you said, I made all these mistakes. But those are opportunities not just for you to learn and grow, but also for you to share with the people that look at you and say I want to be Bask Iyer on stage. >> Yeah. >> You know in a few years because it's really all about being brave enough to say you know what I didn't know this, or I made a mistake, actually maybe it wasn't a mistake, maybe if I didn't go this path I wouldn't have learned and gotten more solidification under my feet to be able to be up there and get a text from a Michael Dell [Bask] That's right. >> In the middle of the night. >> That's right. >> So your advice to the next generation I think is key but I also really respect identification of hey all the things that maybe I did them wrong and encouraging more people as they want to grow their careers to not be afraid to go I don't know this. This this is an opportunity for me to learn. >> Yeah you cannot be the I wish I was the smartest room in Dell Technology, you know that is not possible. You're not even talking about the senior managers you have to talk to the fellows and engineers we have who I just nod and pretend like I know what they're talking about, it's just amazing. So you need a little bit of the humility I think to learn what you want to learn. But have the confidence right. You cannot have nothing and come and work here because I always tell people working in a tech company versus being a CIO of a regular company and I've done both, it's like getting to a batting cage and all of a sudden the balls are coming at 150 miles an hour. You better be prepared to face it. So you have to figure out can I face a ball at 40 miles or 60 miles or 150 miles. So you need to prepare yourself to get there. But having said that though, we are all learning. We are all growing, we all make mistakes. In fact I learn a lot from my millennial kids. They seem to know more about this than I do. I learn a lot and I do something called reverse mentoring in Silicon Valley, which is all the people from LinkedIn, Google, they want to learn from me because they think I'm the greatest CIO whatever, and I want to learn from them. I ended up at the end of the session learning a lot more from them and I feel actually guilty that the mentoring session has gone the other way but, that's what keeps it's interesting is the minute you feel like you know everything or you've done it, very risky in a technology profession, especially in a CIO profession. >> Lisa: So wrapping up the show here, talk to us about some of the things, and in the spirit of learning, what are some of the things that you've heard from customers about, whether it's the new product announcements or new partnerships or just the new areas that Dell Technologies is going in, what has the feedback been like? >> People love the fact that they saw Pat onstage and talk about VMware and Dell working together. People want to see the independence of VMware as well, and they want Dell and VMware working together. They want to see both. They want to make sure that there is the fierce independence that VMware is known for, and the fact that they're working together. That was good to hear because if you do one or the other people get freaked out. The fact that the best private cloud in the world is getting hooked up to the best public clouds in the world, that's a good message for people because they don't want to be locked into a cloud discussion or other kind of stuff. So you want to have the freedom to do that. A lot of people are now expressing interest in IOT and other kind of places and why the edge is important again. What tends to happen in my profession is we talk about IOT last year, this year we talk about AI and ML, guarantee next year's going to be something else. The technology sweet spot takes three, four, five years to hit. So if you just chasing the next wave because you want to be cool and fun you're missing out on opportunity to leverage this. So lot of buzz around the whole world is going to be wired, everything's going to have sensors, the amount of data that comes in and how to manage it and secure it. A lot of CIOs are saying we should get on top of that. Before it's done to us. Lot of buzz on that. I freaked out. I, like any other geek, went to the show to see the cool techs that everybody has. I went to the Dell booths to see the latest laptops because sometimes they don't show us the latest things >> (laughs) >> they keep it for the show. And then Michael Dell is in the booth. He didn't think it was funny but I thought Michael Dell in a Dell booth in Dell World, that's like you want to go buy a Mustang and you find Mr. Ford in the dealership. So I thought it was hilarious and I was shocked and he was just amused to say why do you think that is so funny. But it's nice to have a founder who's like an icon in the industry. Is he listening? Let me stop. (laughs) >> (laughs) He is a big fan of theCUBE. >> Thank you, then I'm not going to say anything nice about him. >> So, last question You talked about last year was IOT, now it's AI and ML, next year's going to be something else, are the people that are chasing those trends the ones that need the therapy dogs the most? (laughs) >> Yeah I think so because you know we have no time for anything these days, we are chasing the next shiny object. When AI and IOT come together, this is going to be fascinating for me. I worked on industry controls and so on, but if every wall could talk, and every object could talk to you what it would be telling you? And humans cannot comprehend it, because the wall is going to tell you so many things. So and so walked by, so and so sat here, whatever. You need artificial intelligence to filter it and say, you know Eric Clapton was here because that's the only thing maybe you want to know. I don't want to know about anything else. That requires AI to process and say this is what Bask would be interested in. And the rest of it doesn't really matter. So this combination I think is very powerful and I'm pretty excited about what if everything, what if dogs could talk, what if walls could talk, What if thermostat could talk >> Oh I'm waiting for that. >> So it's going to happen in our lifetime, pretty soon. >> Lisa: Well Bask thanks so much for stopping by theCUBE and sharing your insights of how you're leading the charge as the CIO, right up there with Michael Dell, Pat Gelsinger and all those big cheeses, but also how you're bringing the technology to the people and really like you said drinking the champagne. >> Thank you, appreciate it. >> We want to thank you for your time. >> Thank you for the time. >> And we thank you for watching theCUBE, we are live day three of Dell Technologies World, right next to the dog therapy center if you need a little break, come say hi and stop by and see some dogs. I'm Lisa Martin for John Troyer, stick around we'll be right back after a short break. (techno music)

(rhythmic music) >> From Phoenix, Arizona, The Cube. At Catalyst Conference, here's your host, Jeff Frick. (rhythmic music) >> Hey, Jeff Frick here with The Cube. We are in Phoenix, Arizona at the Girls Who Code Catalyst Conference It's a great show, about 400 people; they're fourth year. It's going back to the Bay Area next year, so I wanted to come down, talk to some of the key notes, some of the speakers. And really give you a taste if you weren't able to make the trip to Phoenix this year of what's going on. So we're really excited to be joined by our next guest, Fran Maier, she co-founded Match, she co-founded TRUSTe. Serial entrepreneur, the start-up veteran. Fran, welcome. >> Thank you so much Jeff, It's great to be here. >> Absolutely. So you were giving a presentation on really what it is to be a woman entrepreneur. >> Yes, so I've been a internet entrepreneur for now more than twenty years going back to when we started Match.com. And I joined that in late 1994. We really launched around 1995, about 21 years ago, this month, April of 1995. >> Time flies >> And many of the things that were still very much, I think, in the early years of the impact of the internet and mobile and cloud and connectivity on our lives, but Match.com has proven to be what they call a unicorn, a very successful new business model, but more than that many, many people have found their life partner or at least a few good dates on Match.com. So I am always very happy about that. >> And you're way ahead of the curve. Now, I think, I don't know, I've been married for over twenty years, but I think a lot of people that's kind of the first way >> Yeah. to meet people. >> Not the second way. Where when you guys first made Match.com, that was a pretty novel idea. >> Well, well now they call dating where like we used to do it, where you met people at parties and bars, now that's called dating in the wild. >> In the wild (laughing) >> So the more natural thing is using Match.com. But from an entrepreneurial support, I was one of the only women who was involved in starting company in the mid-1990's, still women are less than 10% of TechFounders or venture-backed founders. Women raise a lot less money. And so one of my passions and why I am here at Girls in Tech is to try and impart some of the wisdom gleamed over twenty plus years. >> So what are some of the ways that you see that barrier starting to break down? Is it just, you just got to keep banging on it and slowly and slowly it will move and >> (murmers) >> So I think there's been some difference, I think it's a lot easier to be an entrepreneur of any kind now >> Well that's true. >> than it was twenty years ago. I mean, now having meals delivered to you and the sort of support like Girls in Tech, there was very little of that guidance or certainly there were very few role models, >> Right. >> Twenty years ago. So that certainly has changed. I think another big change, and this is probably over the last two or three years, is that now women feel they can speak out loud about some of the issues. And that there is some, men are willing to listen, >> Right >> Right >> at least some are. >> We still see things like TechCrunch a couple of years ago had a team present a new mobile app called Titstare. We still hear about things like that. We still, there was a survey called The Elephant in Silicon Valley that itemized stories and stats about women and sexual abuse, other kinds of harassment, exclusion, not being invited to sit at the table. So a lot of that stuff is still going on. But I feel like we can call it out a little bit easier. >> Right, right. And it's ... >> Without retribution potentially. >> Is there, is there, kind of a tipping point event, action, that you see potentially as to kind of accelerating ... accelerating it? >> Well I think the media, since lead-in has really kind of picked up on this and discovering it. And the Ellen Pao trial, last year; I spoke a little bit about that, where she brought suit to Kleiner Perkins. She lost the suit, but it started the dialogue. >> Right. >> So I think a lot of this is, is happening and my approach is to try and ... I see, I advise so many start ups. And I see business plans. And almost invariably the business plans from women aren't big enough. They don't say "Hey we're going to be a hundred million dollar company in five years. And we need to raise five million dollars to get there." >> Right. >> Women play it more safe, and, I don't think that, I'm trying to encourage them to take more risk, to figure out how to do it, to play to win. >> Right. Play big to win, right? Playing big. >> Play big to win, yes, swing big. >> It's interesting, on the Lean In, you know Sheryl Sandberg's, I don't know if ground breaking is the right word, but certainly ground breaking. >> Surely, yeah. >> But the Golden State Warriors right now, probably the most popular professional sports team in the country, at the zenith of their success, they have a Lean In commercial. I don't know if you've seen it in the Bay Area, >> I havent seen it! >> where all of the players talk about leaning in. And it just so happens that Steph Curry, their number one superstar, >> Sure. is very close to his wife. She has a cooking show. They're very family orientated. Green ... >> But I thought you were going to ... >> Draymond Green has his mom, who he just constantly just gushes about his mom. And so they, as a male sports team, have a whole commercial they run quite frequently on specifically Lean In. >> Well I, I appreciate that. I also, though, read the article that, that team is owned by bunch of venture capitalists. They all get together and play basketball and it reminded me of a little bit of another place where women have been excluded. And so I was talking to a venture capital friend of mine saying "Buy into the Warriors, or let's buy into a women's soccer team." And you know sports being what they are, it's almost a different thing, but the news about the women's soccer players being paid much less than the men, even though they generate more income. It's just another example, profession by profession where women are paid less or have less opportunity to advance. >> But to your point, I think people understand it, it's not right, but I think everyone pretty much knows that women aren't paid the same as men. But that was interesting about the soccer story, to your point is it was brought up. >> Yeah we could talk about it. >> It wasn't a retribution, right? It's like hey, you know, we're not getting paid and they listed the numbers in Sports Illustrated. They were dramatically different. And, in fact, you know, one of the knocks in the WNBA is that you can't make a living as a player in the WNBA. You just can't. They pay them like, I don't know >> So they should have been. Yeah. >> $60,000. Whatever it is. You know they have to go play in other places, foreign countries to make enough money to live. So I do think its interesting, your point that, you know, the exposure of the problem, the kind of acceptance that we need to do something about it, does seem to be in a much better place than it used to be. >> The other thing that I think that these things illustrate is one of the messages I try and get across, is women tend to settle for too little. You know, they don't necessarily negotiate for themselves. Out of college they don't do as well. They, I've talked to many women who they felt that when they were raising capital, or negotiating deals, that the men on the other side of the table, mostly, not always of course, it sort of said, "Hey this is great, you should be happy to get this. How many women get this?" And that's not really the issue. The issue should be, you should be getting what you deserve. I learned that the hard way, we talked about it a little bit, awhile ago, where Match.com was sold in 1998 for less than $10,000,000. And I was the general manager, I had grown it, we were number one, we were cash flow positive, although probably shouldn't have been. And I walked away with a hundred thousand dollars. And, at the time, sure that's a lot of money, but nobody seemed to encourage me that I probably could have raised the money and led the investment and had an equity round. A year later Match.com was sold from Send It to ISC for $70,000,000. And of course I didn't get anything. >> Yeah. >> So that's my big lesson. The good news is, ten years later, I took TRUSTe, which was a nonprofit, switched it to a for-profit, I raised the capital, and got my ownership in equity position. But tough lesson. >> Yeah, expensive one. >> Yeah. >> But those are the ones you learn though. (laughter) >> I could go through a few of those too. So Fran, we're running low on time. I wanted to give you the last word and get your perspective on, kind of, mentorship and sponsorship. We hear those words tossed around a lot. And that there's a significant difference between just being a mentor and actually being a sponsor, taking an active role in someone else's career. Pushing them to maybe uncomfortable places. Giving them, you know, kind of, the oomph, if you will, that, "Yes you can do this, you do belong." What are you seeing kind of the development of that as people try to help more women ascend, kind of up the line? >> Well, you know, I tend to think of mentorship as something that happens within a company and sponsorship can happen within a company, but advising, sponsoring, promoting, championing, are things that we certainly need to do within the entrepreneurial community of women. So, mentoring is, I see that as a little bit more passive, and I don't know why. But, it's important to have people to look up to and for you, role models are really important. But I think the active thing of championing or sponsoring or even being a more active coach or advisor, is a little bit more hands-on and willing to challenge, you know, you're not just a role model, you're really saying, "Tell me what you're dealing with, and let me see how I can help." I just got off a phone call from one of my advisees, she just raised the money, great news, you know, now she's freaking out about how to spend it. (laughing) >> Maybe with your next problem. >> Yeah. (laughter) >> Been there, done that. >> Right, right. >> You know. >> Well, it's good, good for helpin' them out, and Fran, thanks for taking a few minutes. >> Sure. Lot of fun. >> Absolutely. Track Fran down if you're a budding entrepreneur. She's been there, she's got the scars and the wounds from the early days, and learned from it on the success with TRUSTe. >> Thank you. >> And, some great videos on the web, by the way. I was watching them, the whole story on the Match thing was pretty funny. You'll enjoy it, so take the time ... >> There's one of them where I start to cry, I hate that, but what can you do? >> I didn't get to the crying part, but that's okay. >> Yeah, yeah, that's all right. >> That's what happens in Jerry McGuire all the time. All right, well thanks a lot Fran. >> Thanks so much. >> I'm Jeff Frick, you are watching The Cube. We are in Phoenix, Arizona, at the Girls in Tech Catalyst Conference. (rhythmic music)