(gentle upbeat music) >> Hello, everyone, welcome to theCUBE's coverage of International Women's Day. I'm John Furrier host here in Palo Alto, California. theCUBE's second year covering International Women's Day. It's been a great celebration of all the smart leaders in the world who are making a difference from all kinds of backgrounds, from technology to business and everything in between. Today we've got a great guest, Dominique Bastos, who's the senior Vice President of Cloud at Persistent Systems, formerly with AWS. That's where we first met at re:Invent. Dominique, great to have you on the program here for International Women's Day. Thanks for coming on. >> Thank you John, for having me back on theCUBE. This is an honor, especially given the theme. >> Well, I'm excited to have you on, I consider you one of those typecast personas where you've kind of done a lot of things. You're powerful, you've got great business acumen you're technical, and we're in a world where, you know the world's coming completely digital and 50% of the world is women, 51%, some say. So you got mostly male dominated industry and you have a dual engineering background and that's super impressive as well. Again, technical world, male dominated you're in there in the mix. What inspires you to get these engineering degrees? >> I think even it was more so shifted towards males. When I had the inspiration to go to engineering school I was accused as a young girl of being a tomboy and fiddling around with all my brother's toys versus focusing on my dolls and other kind of stereotypical toys that you would give a girl. I really had a curiosity for building, a curiosity for just breaking things apart and putting them back together. I was very lucky in that my I guess you call it primary school, maybe middle school, had a program for, it was like electronics, that was the class electronics. So building circuit boards and things like that. And I really enjoyed that aspect of building. I think it was more actually going into engineering school. Picking that as a discipline was a little bit, my mom's reaction to when I announced that I wanted to do engineering which was, "No, that's for boys." >> Really. >> And that really, you know, I think she, it came from a good place in trying to protect me from what she has experienced herself in terms of how women are received in those spaces. So I kind of shrugged it off and thought "Okay, well I'm definitely now going to do this." >> (laughs) If I was told not to, you're going to do it. >> I was told not to, that's all I needed to hear. And also, I think my passion was to design cars and I figured if I enroll in an industrial engineering program I could focus on ergonomic design and ultimately, you know have a career doing something that I'm passionate about. So yeah, so my inspiration was kind of a little bit of don't do this, a lot of curiosity. I'm also a very analytical person. I've been, and I don't know what the science is around left right brain to be honest, but been told that I'm a very much a logical person versus a feeler. So I don't know if that's good or bad. >> Straight shooter. What were your engineering degrees if you don't mind sharing? >> So I did industrial engineering and so I did a dual degree, industrial engineering and robotics. At the time it was like a manufacturing robotics program. It was very, very cool because we got to, I mean now looking back, the evolution of robotics is just insane. But you, you know, programmed a robotic arm to pick things up. I actually crashed the Civil Engineering School's Concrete Canoe Building Competition where you literally have to design a concrete canoe and do all the load testing and the strength testing of the materials and basically then, you know you go against other universities to race the canoe in a body of water. We did that at, in Alabama and in Georgia. So I was lucky to experience that two times. It was a lot of fun. >> But you knew, so you knew, deep down, you were technical you had a nerd vibe you were geeking out on math, tech, robotics. What happened next? I mean, what were some of the challenges you faced? How did you progress forward? Did you have any blockers and roadblocks in front of you and how did you handle those? >> Yeah, I mean I had, I had a very eye-opening experience with, in my freshman year of engineering school. I kind of went in gung-ho with zero hesitation, all the confidence in the world, 'cause I was always a very big nerd academically, I hate admitting this but myself and somebody else got most intellectual, voted by the students in high school. It's like, you don't want to be voted most intellectual when you're in high school. >> Now it's a big deal. (laughs) >> Yeah, you want to be voted like popular or anything like that? No, I was a nerd, but in engineering school, it's a, it was very humbling. That whole confidence that I had. I experienced prof, ooh, I don't want to name the school. Everybody can google it though, but, so anyway so I had experience with some professors that actually looked at me and said, "You're in the wrong program. This is difficult." I, and I think I've shared this before in other forums where, you know, my thermodynamic teacher basically told me "Cheerleading's down the hall," and it it was a very shocking thing to hear because it really made me wonder like, what am I up against here? Is this what it's going to be like going forward? And I decided not to pay attention to that. I think at the moment when you hear something like that you just, you absorb it and you also don't know how to react. And I decided immediately to just walk right past him and sit down front center in the class. In my head I was cursing him, of course, 'cause I mean, let's be real. And I was like, I'm going to show this bleep bleep. And proceeded to basically set the curve class crushed it and was back to be the teacher's assistant. So I think that was one. >> But you became his teacher assistant after, or another one? >> Yeah, I gave him a mini speech. I said, do not do this. You, you could, you could have broken me and if you would've done this to somebody who wasn't as steadfast in her goals or whatever, I was really focused like I'm doing this, I would've backed out potentially and said, you know this isn't something I want to experience on the daily. So I think that was actually a good experience because it gave me an opportunity to understand what I was up against but also double down in how I was going to deal with it. >> Nice to slay the misogynistic teachers who typecast people. Now you had a very technical career but also you had a great career at AWS on the business side you've handled 'em all of the big accounts, I won't say the names, but like we're talking about monster accounts, sales and now basically it's not really selling, you're managing a big account, it's like a big business. It's a business development thing. Technical to business transition, how do you handle that? Was that something you were natural for? Obviously you, you stared down the naysayers out of the gate in college and then in business, did that continue and how did you drive through that? >> So I think even when I was coming out of university I knew that I wanted to have a balance between the engineering program and business. A lot of my colleagues went on to do their PEs so continue to get their masters basically in engineering or their PhDs in engineering. I didn't really have an interest for that. I did international business and finance as my MBA because I wanted to explore the ability of taking what I had learned in engineering school and applying it to building businesses. I mean, at the time I didn't have it in my head that I would want to do startups but I definitely knew that I wanted to get a feel for what are they learning in business school that I missed out in engineering school. So I think that helped me when I transitioned, well when I applied, I was asked to come apply at AWS and I kind of went, no I'm going to, the DNA is going to be rejected. >> You thought, you thought you'd be rejected from AWS. >> I thought I'd be, yeah, because I have very much a startup founder kind of disruptive personality. And to me, when I first saw AWS at the stage early 2016 I saw it as a corporation. Even though from a techie standpoint, I was like, these people are insane. This is amazing what they're building. But I didn't know what the cultural vibe would feel like. I had been with GE at the beginning of my career for almost three years. So I kind of equated AWS Amazon to GE given the size because in between, I had done startups. So when I went to AWS I think initially, and I do have to kind of shout out, you know Todd Weatherby basically was the worldwide leader for ProServe and it was being built, he built it and I went into ProServe to help from that standpoint. >> John: ProServe, Professional services >> Professional services, right. To help these big enterprise customers. And specifically my first customer was an amazing experience in taking, basically the company revolves around strategic selling, right? It's not like you take a salesperson with a conventional schooling that salespeople would have and plug them into AWS in 2016. It was very much a consultative strategic approach. And for me, having a technical background and loving to solve problems for customers, working with the team, I would say, it was a dream team that I joined. And also the ability to come to the table with a technical background, knowing how to interact with senior executives to help them envision where they want to go, and then to bring a team along with you to make that happen. I mean, that was like magical for me. I loved that experience. >> So you like the culture, I mean, Andy Jassy, I've interviewed many times, always talked about builders and been a builder mentality. You mentioned that earlier at the top of this interview you've always building things, curious and you mentioned potentially your confidence might have been shaken. So you, you had the confidence. So being a builder, you know, being curious and having confidence seems to be what your superpower is. A lot of people talk about the confidence angle. How important is that and how important is that for encouraging more women to get into tech? Because I still hear that all the time. Not that they don't have confidence, but there's so many signals that potentially could shake confidence in industry >> Yeah, that's actually a really good point that you're making. A lot of signals that women get could shake their confidence and that needs to be, I mean, it's easy to say that it should be innate. I mean that's kind of like textbook, "Oh it has to come from within." Of course it does. But also, you know, we need to understand that in a population where 50% of the population is women but only 7% of the positions in tech, and I don't know the most current number in tech leadership, is women, and probably a smaller percentage in the C-suite. When you're looking at a woman who's wanting to go up the trajectory in a tech company and then there's a subconscious understanding that there's a limit to how far you'll go, your confidence, you know, in even subconsciously gets shaken a little bit because despite your best efforts, you're already seeing the cap. I would say that we need to coach girls to speak confidently to navigate conflict versus running away from it, to own your own success and be secure in what you bring to the table. And then I think a very important thing is to celebrate each other and the wins that we see for women in tech, in the industry. >> That's awesome. What's, the, in your opinion, the, you look at that, the challenges for this next generation women, and women in general, what are some of the challenges for them and that they need to overcome today? I mean, obviously the world's changed for the better. Still not there. I mean the numbers one in four women, Rachel Thornton came on, former CMO of AWS, she's at MessageBird now. They had a study where only one in four women go to the executive board level. And so there's still, still numbers are bad and then the numbers still got to get up, up big time. That's, and the industry's working on that, but it's changed. But today, what are some of the challenges for this current generation and the next generation of women and how can we and the industry meet, we being us, women in the industry, be strong role models for them? >> Well, I think the challenge is one of how many women are there in the pipeline and what are we doing to retain them and how are we offering up the opportunities to fill. As you know, as Rachel said and I haven't had an opportunity to see her, in how are we giving them this opportunity to take up those seats in the C-suite right, in these leadership roles. And I think this is a little bit exacerbated with the pandemic in that, you know when everything shut down when people were going back to deal with family and work at the same time, for better or for worse the brunt of it fell on probably, you know the maternal type caregiver within the family unit. You know, I've been, I raised my daughter alone and for me, even without the pandemic it was a struggle constantly to balance the risk that I was willing to take to show up for those positions versus investing even more of that time raising a child, right? Nevermind the unconscious bias or cultural kind of expectations that you get from the male counterparts where there's zero understanding of what a mom might go through at home to then show up to a meeting, you know fully fresh and ready to kind of spit out some wisdom. It's like, you know, your kid just freaking lost their whatever and you know, they, so you have to sort a bunch of things out. I think the challenge that women are still facing and will we have to keep working at it is making sure that there's a good pipeline. A good amount of young ladies of people taking interest in tech. And then as they're, you know, going through the funnel at stages in their career, we're providing the mentoring we're, there's representation, right? To what they're aspiring to. We're celebrating their interest in the field, right? And, and I think also we're doing things to retain them, because again, the pandemic affected everybody. I think women specifically and I don't know the statistics but I was reading something about this were the ones to tend to kind of pull it back and say well now I need to be home with, you know you name how many kids and pets and the aging parents, people that got sick to take on that position. In addition to the career aspirations that they might have. We need to make it easier basically. >> I think that's a great call out and I appreciate you bringing that up about family and being a single mom. And by the way, you're savage warrior to doing that. It's amazing. You got to, I know you have a daughter in computer science at Stanford, I want to get to that in a second. But that empathy and I mentioned Rachel Thornton, who's the CMO MessageBird and former CMO of AWS. Her thing right now to your point is mentoring and sponsorship is very key. And her company and the video that's on the site here people should look at that and reference that. They talk a lot about that empathy of people's situation whether it's a single mom, family life, men and women but mainly women because they're the ones who people aren't having a lot of empathy for in that situation, as you called it out. This is huge. And I think remote work has opened up this whole aperture of everyone has to have a view into how people are coming to the table at work. So, you know, props are bringing that up, and I recommend everyone look at check out Rachel Thornton. So how do you balance that, that home life and talk about your daughter's journey because sounds like she's nerding out at Stanford 'cause you know Stanford's called Nerd Nation, that's their motto, so you must be proud. >> I am so proud, I'm so proud. And I will say, I have to admit, because I did encounter so many obstacles and so many hurdles in my journey, it's almost like I forgot that I should set that aside and not worry about my daughter. My hope for her was for her to kind of be artistic and a painter or go into something more lighthearted and fun because I just wanted to think, I guess my mom had the same idea, right? She, always been very driven. She, I want to say that I got very lucky that she picked me to be her mom. Biologically I'm her mom, but I told her she was like a little star that fell from the sky and I, and ended up with me. I think for me, balancing being a single mom and a career where I'm leading and mentoring and making big decisions that affect people's lives as well. You have to take the best of everything you get from each of those roles. And I think that the best way is play to your strengths, right? So having been kind of a nerd and very organized person and all about, you know, systems for effectiveness, I mean, industrial engineering, parenting for me was, I'm going to make it sound super annoying and horrible, but (laughs) >> It's funny, you know, Dave Vellante and I when we started SiliconANGLE and theCUBE years ago, one of the things we were all like sports lovers. So we liked sports and we are like we looked at the people in tech as tech athletes and except there's no men and women teams, it's one team. It's all one thing. So, you know, I consider you a tech athlete you're hard charging strong and professional and smart and beautiful and brilliant, all those good things. >> Thank you. >> Now this game is changing and okay, and you've done startups, and you've done corporate jobs, now you're in a new role. What's the current tech landscape from a, you know I won't say athletic per standpoint but as people who are smart. You have all kinds of different skill sets. You have the startup warriors, you have the folks who like to be in the middle of the corporate world grow up through corporate, climb the corporate ladder. You have investors, you have, you know, creatives. What have you enjoyed most and where do you see all the action? >> I mean, I think what I've enjoyed the most has been being able to bring all of the things that I feel I'm strong at and bring it together to apply that to whatever the problem is at hand, right? So kind of like, you know if you look at a renaissance man who can kind of pop in anywhere and, oh, he's good at, you know sports and he's good at reading and, or she's good at this or, take all of those strengths and somehow bring them together to deal with the issue at hand, versus breaking up your mindset into this is textbook what I learned and this is how business should be done and I'm going to draw these hard lines between personal life and work life, or between how you do selling and how you do engineering. So I think my, the thing that I loved, really loved about AWS was a lot of leaders saw something in me that I potentially didn't see, which was, yeah you might be great at running that big account but we need help over here doing go to market for a new product launch and boom, there you go. Now I'm in a different org helping solve that problem and getting something launched. And I think if you don't box yourself in to I'm only good at this, or, you know put a label on yourself as being the rockstar in that. It leaves room for opportunities to present themselves but also it leaves room within your own mind to see yourself as somebody capable of doing anything. Right, I don't know if I answered the question accurately. >> No, that's good, no, that's awesome. I love the sharing, Yeah, great, great share there. Question is, what do you see, what do you currently during now you're building a business of Persistent for the cloud, obviously AWS and Persistent's a leader global system integrator around the world, thousands and thousands of customers from what we know and been reporting on theCUBE, what's next for you? Where do you see yourself going? Obviously you're going to knock this out of the park. Where do you see yourself as you kind of look at the continuing journey of your mission, personal, professional what's on your mind? Where do you see yourself going next? >> Well, I think, you know, again, going back to not boxing yourself in. This role is an amazing one where I have an opportunity to take all the pieces of my career in tech and apply them to building a business within a business. And that involves all the goodness of coaching and mentoring and strategizing. And I'm loving it. I'm loving the opportunity to work with such great leaders. Persistent itself is very, very good at providing opportunities, very diverse opportunities. We just had a huge Semicolon; Hackathon. Some of the winners were females. The turnout was amazing in the CTO's office. We have very strong women leading the charge for innovation. I think to answer your question about the future and where I may see myself going next, I think now that my job, well they say the job is never done. But now that Chloe's kind of settled into Stanford and kind of doing her own thing, I have always had a passion to continue leading in a way that brings me to, into the fold a lot more. So maybe, you know, maybe in a VC firm partner mode or another, you know CEO role in a startup, or my own startup. I mean, I never, I don't know right now I'm super happy but you never know, you know where your drive might go. And I also want to be able to very deliberately be in a role where I can continue to mentor and support up and coming women in tech. >> Well, you got the smarts but you got really the building mentality, the curiosity and the confidence really sets you up nicely. Dominique great story, great inspiration. You're a role model for many women, young girls out there and women in tech and in celebration. It's a great day and thank you for sharing that story and all the good nuggets there. Appreciate you coming on theCUBE, and it's been my pleasure. Thanks for coming on. >> Thank you, John. Thank you so much for having me. >> Okay, theCUBE's coverage of International Women's Day. I'm John Furrier, host of theCUBE here in Palo Alto getting all the content, check out the other interviews some amazing stories, lessons learned, and some, you know some funny stories and some serious stories. So have some fun and enjoy the rest of the videos here for International Women's Days, thanks for watching. (gentle inspirational music)

(bright music) >> Well, hey, everybody. John Walls here with theCUBE continuing coverage at AWS re:Invent '22. It has been three really fantastic days here at the Venetian in Las Vegas. And we still have more to come with us to talk about Persistent Systems, the Senior Vice President of Cloud at Persistent Dominique Bastos. Dominique, good to see you. >> Pleasure to see you. >> Thanks for joining us here on the queue. >> Thank you for having me. >> Oh, you bet. You bet. >> Thank you. All right. Tell us about Persistent Systems. So, first off, core focus, what you're up to and then we'll jump in from there. >> Sure, sure. So Persistent Systems is a digital engineering solutions and services provider. They've been around for 32 years doing software engineering, innovating in several areas within different verticals. There's over 22,500 people at Persistent now as of my last count. We're in 18 countries. >> Mm. >> And in October we hit the $1 billion annualized recurring revenue mark. >> Oh, that's a good number right there. >> It's a good number. It's a great company. It's been such an interesting journey. I was with AWS for almost seven years before recently joining Persistent, and it almost felt like a such a logical transition in terms of bringing what I've seen in my entire career of interacting with customers and businesses to what Persistent can provide as people are looking to make their journey to the cloud whatever stage they might be at so. >> Right. And we should point out is that SVP of Cloud, but your focus is AWS. >> My focus AWS. >> Other options, other opportunities. >> Right. >> But you're AWS all the way. >> Right. It's a multicloud company because, you know, we really don't believe in dictating to a customer what they need. I think the benefit, one of the differentiators for Persistent is the amount of legacy history that they have across these industries and customers. I mean, 32 years is a lot, and in terms of like software engineering. So it's like really doing the hard work, the heavy lifting. And then seeing what can actually be commoditized, repeatable building solutions within these verticals to help customers accelerate their transformations. >> Mm hmm. >> So... >> You know, when we talk about cloud, I mean, this has been something that's been on the forefront feel like a long time. Right? But yet there are still many and maybe you can help me out with that percentage, whatever of companies who are either haven't begun yet, are just beginning, they're really in a nascent stage of this transformation. And yeah, I found it curious this week as we've talked with different people about where are you in your journey and so and so forth. A lot of people are way back just starting pass go, and aren't as mature as I would've thought. I mean, do you find that to be the case? >> Absolutely. And there's many reasons for that. I mean, I think what I've started, I mean I've been seeing it over the years, but we all know IT and business back then was very much kept separate. >> Two separate animals. >> Two separate animals. >> Yeah. >> IT made the decisions, not in a vacuum, but almost in a vacuum, right? Now, obviously companies who know it's necessary and have embraced it, bring together the function of looking at the technological solutions that they're adopting to solve a business problem. Right? But that business problem really is dictated by the customer need. >> Mm hmm. >> So I think I have seen, you know, in terms of like the life cycle of a business adopting technology, post cloud, there's a lot of enterprises that are still, they've made such big investments in their legacy infrastructure. >> Mm hmm. >> And in actually, you know, the developers and the people that are maintaining those systems, and the different connections to put it in layman's terms between their systems and their customers systems, right? So, that entire scenario makes it very difficult for them to move. >> Mm hmm. >> It's like moving a mountain. So, I would say there's like three ways of looking at it. You have those that kind of want to revitalize their technology, right? Their backend systems, they want to optimize costs, they want to, and my background in technology is specifically in data, kind of I came up as a DBA and built data models, and I've always loved data before it was a thing to love data. (John chuckles) So... >> You were so far ahead of the curve. >> I was ahead of the curve. I was a trendsetter. >> What a trendsetter? >> I'm a trendsetter. (Dominique chuckles) So I think from that perspective they're looking at, you know, these enormous of amounts of data that they've been capturing in these legacy systems that they're so heavily invested in, but they're not able to derive the insights to better serve their customers or to even innovate new revenue streams from that data. But, they're taking the first step to say, look, you know, we can actually operate more smoothly at a lower cost by moving to the cloud. >> Mm hmm. >> So there's that. Then there are those that are looking to actually innovate and create new revenue streams, monetize their data, look at opportunities to integrate feedback that they've been getting from their customers to provide new services. So they're using the cloud journey, they've probably already moved into the cloud. They're starting to look at analytics, and potentially using AIML to facilitate creating these solutions and services. And then there's those that, you know, want to pioneer, and break into new inventions and ways of solving the big world problems. >> Mm hmm. >> Right? I mean, I think that's one thing I noticed in this re:Invent that I thought was so special is there's like a really big focus on humanity, on humans, on you know, as we were talking earlier everything and I myself have like holding books and I don't like people being on their phone when we're having a conversation. (John chuckles) >> Right. But I think, you know, we are where we are. The reality is the world has evolved in such a way that community is no longer, it takes a small village, all, you know everybody knows each other. You have face to face interactions. You're not doing that with your customers either. There's digitally native businesses that have for a long time cropped up in the FinTech space in you know, you name the space, there's a startup that was born in the cloud that can reach customers immediately, and can provide a service that an enterprise that's kind of like weighed down with their legacy systems. They can't pivot fast enough. So, I think, you know, the pioneers think beyond that. How do we use quantum computing? You know, how do we use 3D simulation to anticipate solving big world problems? Whether it's, you know, people no longer, I don't know what the statistics are, but it's very sad. That elderly people, you know, the amount of human contact that they have is very little. You know, and if you could provide, I don't know, an experience, an immersive experience where their memories are triggered, you know, to help them with dementia, or Alzheimer's. >> Sure. >> I mean, those types of things, those are the things that I think that's what excites me about the launches that I see at re:Invent. And I think the innovation, you know, you have to take that journey. Unless you're born in the cloud, you do have to kind of take that journey. >> You got to get there. >> You have to get there. >> Right. Sure. >> But it's so worth it. >> So how about, let's just say, if I'm a health sciences company, or I'm a pharmaceutical or whatever, and so I've got this desire to create this new opportunity you know, with a human, I say, but yeah, but if you're also Persistent Systems and you're working with you know, somebody in FinTech, or somebody in EEG or whatever, you can't really understand my challenges or my problems. I mean, how do you wear those different hats so you can identify not only what the focus of that client is, but also their technology and how you're going to get them to marry up so they can achieve their goals? >> Well, the beauty of being, you know, in a company with teams of people that you work with, I cut across industries. Right? So we have vertical leaders that have very deep subject matter expertise in any number of those areas. You know, we're working with genomics for example. So, for example, you know, we engage with a customer that we've been helping over the past 32 years use technology to bring services to their customers. And now we are seeing an opportunity to help them innovate to keep up for their business for obvious reasons, but also to supply their customers with the new innovative solutions within that industry, right? 'Cause you need that vehicle to kind of deploy and deliver what customers need. The way we do it is from end to end, right? So, we have in the partnership with AWS, we're a partner of AWS, and as such we are able to collaborate with AWS and their customers or bring our customers to the cloud for all the way from assessment to planning to execution. And even within Persistent, we have ways to main operationalize the maintenance of these solutions. So it's really very easy managed services type framework that we work under. In terms of like migration planning, we have competencies within AWS. For looking at migrations we have AIML, we have DevOps. So we have the various competencies aligned with AWS to be able to execute at whatever stage the customer is. But also in terms of like the accelerators that we provide or the frameworks to look at total cost, that cuts across, right? And then we don't kind of like, here's what you needed and buy, never speak to us again. (John chuckles) I mean, I think the beauty of this company and what I really loved when I was first speaking to them is the depth of the relationships with their customers and the longevity of them. So they've really seen their customers grow. And you can only do that if you're there for the long run. >> You've got to be present. >> You have to be present. >> Sure. So how do you handle if people are making this transformation and they're moving into the cloud, but the people they have on staff might not be familiar with it, right? They have great expertise in what they've been doing on these legacy systems, but now you're moving, you're migrating to a new world, new culture, new environment, and you got to get 'em up to speed. And that's not easy. >> No. >> Right? So what do you do, or what does Persistent suggest or what are you doing and with regard to closing that gap into making that bridge so that they can maintain a little bit on their own. >> Yeah. >> They can execute and implement on their own. >> Yep. >> A little bit. They don't need somebody there to stand over their shoulder the whole time. >> I won't geek out on having joined AWS in professional services way back when to migrate a major company to the cloud, and having lived through painstakingly all those problems and blockers and adoption roadblocks that you speak of. >> Mm hmm. >> You know, I think the way Persistent handles it is what I would've done myself, right? If I were to start a company and say how do we help customers simplify their cloud journey, and remove the complexity? I think that's what Persistent Systems does. We, there's training programs that we are aligned to with AWS. So there's up-skilling of development teams, application developers. We collaborate from the top down with executives to look at the resources that they have available. Obviously mission critical systems that cannot sacrifice having engineers pulled away for a new project. You know, you take that into account. I think, you know, when I spoke earlier about assessments, you're not just assessing what needs to be lifted and shifted or refactored or rearchitected, you're looking at, you know, all these applications that are going to move to the cloud. Who owns them? >> Mm hmm. >> You know, do you have a CI/CD pipeline, or a data pipeline built? Well, we're going to need that, right? So, the continuous integration, continuous development of applications, that type of DevOps, obviously security also DevSecOps, we look at it from end to end as well. We have a very strong security practice. So, all those advisory pieces we have, but we also have the capability to execute on it. Where we're not just coming in and saying well this is what you should do. We're kind of in there saying, this is what you should do, here's how we can get you started. And then, you know, it's a collaborative effort with our customers to see how much they still want us to stay versus how much they want to take over. >> Right. It's nice to have a friend. >> Yeah. (John laughs) Who doesn't need a friend. (Dominique laughs) And Persistent Systems is your friend. Dominique, thanks for the time. >> Oh, my pleasure. >> I appreciate it. >> Thanks again for having me. >> Thanks for being here on theCUBE. You bet. >> Absolutely. >> You are watching theCUBE as you well know the leader in high tech coverage. (soft music)

>> (lively music) >> Narrator: From around the globe it's theCUBE, with digital coverage of IBM Think 2021. Brought to you by IBM. >> Welcome to theCUBE's coverage of IBM Think 2021, the digital event experience. I'm your host, Lisa Martin. I've got an alumni joining me and a brand new guest to the CUBE please welcome Paul Papas, the Global Managing Partner, for IBM Global Business Services, this is transformation services. Paul, welcome back to the virtual CUBE. >> Thanks Lisa great to be here with you today. And Dominique Dubois is here as well. She is the Global Strategy and Offerings Leader in business transformation services or BTS at IBM. Dominique, welcome to the program. >> Thanks Lisa, great to be here. So, we're going to be talking about accelerating business transformation with intelligent workflows. We're going to break through all that, but Paul we're going to start with you. Since we last got together with IBM, a lot has changed so much transformation, so much acceleration of transformation. Talk to me from your perspective, how have you seen the way that businesses running change and what some of the changes in the future are going to be? >> Well, you hit on two key words there Lisa and thanks so much for that question. Two key words that you hit on were change and acceleration. And that's exactly what we see. We were seeing this before the pandemic and if anything, with the pandemic did when things started started kind of spreading around the world late or early last year, around January, February timeframe we saw that word acceleration really take hold. Every one of our clients were looking for new ways to accelerate the change that they had already planned to adapt to this new, this new normal or this new abnormal, depending on how you view it. In fact, we did a study recently, an IBV study that's our Institute of Business Value and found that six out of 10 organizations were accelerating all of their transformation initiatives they had already planned. And that's exactly what we're seeing happening right now in all parts of the world and across all industries. This acceleration to transform. >> So, one of the things that we've talked about for years, Paul, before the pandemic was even a thing, is that there was a lot of perceived technical barriers in terms of like the tech maturity for organizations and employees being opposed to change. People obviously it can be a challenge. They're used to doing things the way they are. But as you just said, in that IBV survey, nearly 60% of businesses say we have to accelerate our transformation due to COVID, probably initially to survive and then thrive. Talk to me about some of those, those barriers that were there a little over a year ago and how businesses 60 plus percent of them have moved those out of the way. >> You know at IBM we've got a 109 year history of being a technology innovation company. And the rate of pace of technical change is always increasing. It's something that we love and that we're comfortable with. But the rate and pace of change is always unsettling. And there's always a human element for change. And the human element is always the rate, the rate setter in terms of the amount of change that you can have in an organization. Our former chairman Ginni Rometty, used to say that growth and comfort cannot co-exist. And it's so true because changing is uncomfortable. It's unsettling. It can be, it can be nerve-racking. It can instill fear and fear can be paralyzing in terms of driving change. And what we also see is there's a disconnect, a lot of times and that IBV study that I was referring to before, we saw results coming back where 78% of executives feel that they have provided the training and enablement to help their employees transform to new required skills and new ways of working but only half of the people surveyed felt the same way. Similarly, we saw a disconnect in terms of companies feeling that they're providing the right level of health and wellness support during the pandemic. And only half of the employees responded back they feel that they're getting that level of support. So, the people change aspect of doing a transformation or adapting to new circumstances is always the most critical component and always the hardest component. And when we talk about helping our clients do that in IBM that's our service as organization. That's the organization that Dominique Dubois is representing here today. I'm responsible for business transformation services within our organization. We help our clients adapt using new technologies, transforming the way they work, but also addressing the people change elements that could be so difficult and hitting them head on so that they can make sure that they can survive and thrive in a meaningful and lasting way in this new world. >> One of the hardest things is that cultural transformation regardless of a pandemic. So, I can't imagine I'd love to get one more thing, Paul from you before we head over to Dominique. IBM is on 109 year old organization. Talk to me about the IBM pledge. This is something that came up last year, huge organization massive changes last year, not just the work from home that the mental concerns and issues that people had. What did IBM do like as a grassroots effort that went viral? >> Yeah, so, it's really great. So, when the pandemic started, we all have to shift it, We all have to shift to working from home. And as you mentioned, IBM's 109 year old company, we have over 300,000 employees working in 170 countries. So, we had to move this entire workforce. It's 370,000 humans to working in a new way that many of which have never done before. And when we started experiencing, the minute we did that, within a few weeks, my team and I were talking Dominique is on my team and we were having conversations where we were feeling really exhausted. Just a few weeks into this and it was because we were constantly on Webex, we were constantly connected and we're all used to working really hard. We travel a lot, we're always with our clients. So, it wasn't that, you have a team that is adapting to like working more hours or longer hours, but this was fundamentally different. And we saw that with schools shutting down and lock downs happening in different of the world the home life balance was getting immediately difficult to impossible to deal with. We have people that are taking care of elderly parents, people that are homeschooling children, other personal life situations that everyone had to navigate in the middle of a pandemic locked at home with different restrictions on when you can go out and get things done. So, we got together as a group and we just started talking about how can we help? How can we help make life just a little bit easier for all of our people? And we started writing down some things that we would, we would commit to doing with each other. How we would address each other. And when that gave birth to was what we call the IBM Work From Home Pledge. And it's a set of principles, all grounded in the belief that, if we act this way, we might just be able to make life just a little bit easier for each other and it's grounded in empathy. And there are parts of the Plex that are pledging to be kind. Recognizing that in this new digital world that we're showing up on camera inside of everyone's home. We're guests in each other's homes. So, let's make sure that we act appropriately as guests at each other's home. So, if children run into the frame during the middle of a meeting or dog started barking during the middle of a meeting, just roll with it. Don't call out attention to it. Don't make people feel self-conscious about it. Pledged the support so your fellow IBM by making time for personal needs. So, if someone has to, do homeschooling in the middle of the day, like Dominique's got triplets she's got to do homeschooling in the middle of the day. Block that time off and we will respect that time on your calendar. And just work around it and just deal with it. There are other things like respecting that camera ready time. As someone who's now been on camera every day it feels like for the last 14 months we want to respect the time that people when they have their cameras off. And not pressure them to put their cameras on saying things like, Hey, I can't see you. There's no reason to add more pressure to everyone's life, if someone's camera's off, it's all for a reason. And then other things like pledging to checking on each other, pledging to set boundaries and tend to our own self-care. So, we published that as a group, we just again and we put it on a Slack channel. So it's kind of our communication method inside the company. It was just intended to be for my organization but it started going viral and tens of thousands of IBM members started taking, started taking the pledge and ultimately caught the attention of our CEO and he loved it, shared it with his leadership team, which I'm a part of. And then also then went on LinkedIn and publicly took the pledge as well. Which then also got more excitement and interaction with other companies as well. So, grassroots effort all grounded in showing empathy and helping to make life just a little bit easier for everyone. >> So important, I'm going to look that up and I'm going to tell you as a person who speaks with many tech companies a week. A lot of businesses could take a lead from that and it gets really important and we are inviting each other into our homes and I see you're a big Broadway fan I'll have to ask you that after we wrap (giggles) Dominique I don't know how you're doing any of this with triplets. I only have two dogs (Dominique laughs) but I'd love to know this sense of urgency, that is everywhere you're living it. Paul talked about it with respect to the acceleration of transformation. How from your lens is IBM and IBM helping customers address the urgency, the need to pivot, the need to accelerate, the need to survive and thrive with respect to digital transformation actually getting it done? >> Right, thanks Lisa, so true our clients are really needing to and ready to move with haste. That that sense of urgency can be felt I think across every country, every market, every industry. And so we're really helping our clients accelerate their digital transformations and we do that through something that we call intelligent workflows. And so workflows in and of themselves are basically how organizations get work done. But intelligent workflows are how we infuse; predictive properties, automation, transparency, agility, end to end across a workflow. So, pulling those processes together so they're not solid anymore and infusing. So, simply put we bring intelligent workflows to our clients and it fundamentally reinvents how they're getting work done from a digital perspective, from a predictive perspective, from a transparency perspective. And I think what really stands apart when we deliver this with our clients in partnership with our clients is how it not only delivers value to the bottom line, to the top line it also actually delivers greater value to their employees, to the customers, to the partner to their broader ecosystem. And intelligent workflows are really made up of three core elements. The first is around better utilizing data. So, aggregating, analyzing, getting deeper insight out of data, and then using that insight not just for employees to make better decisions, but actually to support for emerging technologies to leverage. So we talked about AI, automation, IOT, blockchain, all of these technologies require vast amounts of data. And what we're able to bring both on the internal and external source from a data perspective really underpins what these emerging technologies can do. And then the third area is skills. Our skills that we bring to the table, but also our clients deep, deep expertise, partner expertise, expertise from the ecosystem at large and pulling all of that together, is how we're really able to help our clients accelerate their digital transformations because we're helping them shift, from a set of siloed static processes to an end-to-end workflow. We're helping them make fewer predictions based on the past historical data and actually taking more real-time action with real time insights. So, it really is a fundamental shift and how your work is getting done to really being able to provide that emerging technologies, data, deep skills-based end to end workflow. >> That word fundamental has such gravity. and I know we say data has gravity being fundamental in such an incredibly dynamic time is really challenging but I was looking through some of the notes that you guys provided me with. And in terms of what you just talked about, Dominique versus making a change to a silo, the benefits and making changes to a spectrum of integrated processes the values can be huge. In fact, I was reading that changing a single process like billing, for example might deliver up to 20% improved results. But integrating across multiple processes, like billing, collections, organizations can achieve double that up to 40%. And then there's more taking the intelligent workflow across all lead to cash. This was huge. Clients can get 50 to 70% more value from that. So that just shows that fundamental impact that intelligent workflows can make. >> Right, I mean, it really is when we see it really is about unlocking exponential value. So, when you think about crossing end to end workflow but also, really enhancing what clients are doing and what companies are doing today with those exponential technologies from kind of single use the automation POC here and AI application POC here, actually integrating those technologies together and applying them at scale. When I think intelligent workflows I think acceleration. I think exponential value. But I also really think about at scale. Because it's really the ability to apply these technologies the expertise at scale that allows us to start to unlock a lot of that value. >> So let's go over Paul, in the last few minutes that we have here I want to talk about IBM garage and how this is helping clients to really transform those workflows. Talk to me a little bit about what IBM garage is. I know it's not IBM garage band and I know it's been around since before the pandemic but help us understand what that is and how it's delivering value to customers. >> Well, first I'm going to be the first to invite you to join the IBM garage band, Lisa so we'd love to have you >> I'm in. no musical experience required... >> I like to sing, all right I mean (laughs) We're ready, we're ready for. So, let me talk to you about IBM garage and I do want to key on two words that Dominique was mentioning speed and scale. Because that's what our clients are really looking for when they're doing transformations around intelligent workflows. How can you transform at scale, but do that with speed. And that really becomes the critical issue. As Dominique mentioned, there's a lot of companies that can help you do a proof of concept do something in a few weeks that you can test an idea out and have something that's kind of like a throw away piece of work that maybe proves a point or just proves a point. But even if it does prove the point at that point you'd have to restart a new, to try to get something that you could actually scale either in the production technology environment or scale as a change across an organization. And that's where IBM garage comes in. It's all a way of helping our clients co-create, co-execute and then cooperate, innovating at scale. So, we use methods like design thinking inside of IBM we've trained several hundred thousand people on design thinking methods. We use technologies like neural and other things that help our clients co-create in a dynamic environment. And what's amazing for me is that, the cause of the way we were, we were doing work with clients in a garage with using IBM garage in a garage environment before the pandemic. And one of our clients Frito-Lay of North America, is an example where we've helped them innovate at scale and speed using IBM garage over a long period of time. And when the pandemic hit, we in fact were running 11 garages across 11 different workflow areas for them the pandemic hit and everyone was sent home. So, we all instantly overnight had to work from home together with relay. And what was great is that we were able to quickly adapt the garage method to working in a virtual world. To being able to run that same type of innovation and then use that innovation at scale in a virtual world, we did that overnight. And since that time which happened, that happened back in March of last year throughout the pandemic, we've run over 1500 different garage engagements with all of our clients all around the world in a virtual, in a virtual environment. It's just an incredible way, like I said to help our clients innovate at scale. >> That's fantastic, go ahead Dominique. >> Oh, sorry, was just said it's a great example, we partnered with FlightSafety International, they train pilots. And I think a great example of that speed and scale right is in less than 12 weeks due to the garage methodology and the partnership with FlightSafety, we created with them and launched an adaptive learning solution. So, a platform as well as a complete change to their training workflow such that they had personalized kind of real-time next best training for how they train their pilots for simulators. So, reducing their cycle time but also improving the training that their pilots get, which as people who normally travel, it's really important to us and everyone else. So, just a really good example, less than 12 weeks start to start to finish. >> Right, talk about acceleration. Paul, last question for you, we've got about 30 seconds left I know this is an ecosystem effort of IBM, it's ecosystem partners, it's Alliance partners. How are you helping align right partner with the right customer, the right use case? >> Yeah, it's great. And our CEO Arvind Krishna has really ushered in this era where we are all about the open ecosystem here at IBM and working with our ecosystem partners. In our services business we have partnerships with all the major, all the major technology players. We have a 45 year relationship with SAP. We've done more SAP S 400 implementations than anyone in the world. We've got the longest standing consulting relationship with Salesforce, we've got a unique relationship with Adobe, they're only services and technology partner in the ecosystem. And we just recently won three, procedures Partner Awards, with them and most recently we announced a partnership with Celonis which is an incredible process execution software company, process mining software company that's going to help us transform intelligent workflows in an accelerated way, embedded in our garage environment. So, ecosystem is critical to our success but more importantly, it's critical to our client success. We know that no one alone has the answers and no one alone can help anyone change. So, with this open ecosystem approach that we take and global business services and our business transformation services organization, we're able to make sure that we bring our clients the best of everyone's capabilities. Whether it's our technology, partners, our services IBM's own technology capabilities, all in the mix, all orchestrated in service to our client's needs all with the goal of driving superior business outcomes for them. >> And helping those customers in any industry to accelerate their business transformation with those intelligent workloads and a very dynamic time. This is a topic we could keep talking about unfortunately, we are out of time but thank you both for stopping by and sharing with me what's going on with respect to intelligent workflows. How the incremental exponential value it's helping organizations to deliver and all the work that IBM is doing to enable its customers to be thrivers of tomorrow. We appreciate talking to you >> Paul: Thanks Lisa. >> Dominique: Thank you >> For Paul Papas and Dominique Dubois I'm Lisa Martin. You're watching the CUBE's coverage of IBM Think the digital event experience. (gentle music)

>> Announcer: From around the globe, it's theCUBE, with digital coverage of IBM Think 2021, brought to you by IBM. >> Hey, welcome to theCUBE's coverage of IBM Think, the digital event experience. I'm your host, Lisa Martin, welcoming back to the program one of our CUBE alumn. Dominique Dubois joins me. She's the Global Strategy and Offerings Executive in the Business Transformation Services of IBM. Dominique, it's great to talk to you again. >> Hi Lisa, great to be with you today. >> So we're going to be talking about the theme of this interview. It's going to be the ROI of AI for business. We've been talking about AI emerging technologies for a long time now. We've also seen a massive change in the world. I'd love to talk to you about how organizations are adopting these emerging technologies to really help transform their businesses. And one of the things that you've talked about in the past, is that there's these different elements of AI for business. One of them is trust, right, the second is ease of use, and then there's this importance of data in all of these important emerging technologies that require so much data. How do those elements of AI come together to help IBM's clients be able to deliver the products and services that their customers are depending on? >> Yeah. Thank you, Lisa. So, when we look at AI and AI solutions with our clients, I think how that comes together is in the way in which we don't look at AI, or AI application solution, independently, right. We're looking at it and we're applying it within our customer's operations with respect to the work that it's going to do, with respect to the part of the operations and the workflow and the function that it sits in, right. So the idea around trust and ease of use and the data that can be leveraged in order to kind of create that AI and allow that AI to be self-learning and continue to add value really is fundamental around how we design and how we implement it within the workflow itself. And how we are working with the employees, with the actual humans, that are going to be touching that AI, right, to help them with new skills that are required to work with AI, to help them with what we call the new ways of working, right, 'cause it's that adoption that really is critical to get the use of AI in enterprises at scale. >> That adoption that you just mentioned, that's critical. That can be kind of table stakes. But what we've seen in the last year is that we've all had to pivot, multiple times, and be reactionary, or reactive, to so many things out of our control. I'm curious what you've seen in the last year in terms of the appetite for adoption on the employees front. Are they more willing to go, all right, we've got to change the way we do things, and it's probably going to be, some of these are going to be permanent? >> Yeah. Lisa, we've absolutely seen a huge rise in the adoption, right, or in the openness, the mindset. Let's just call it the mindset, right. It's more of an open mindset around the use of technology, the use of technology that might be AI backed or AI based, and the willingness to, and I will say, the willingness to try is really then what starts that journey of trust, right. And we're seeing that open up in spades. >> That is absolutely critical. It's just the willingness, being open-minded enough to go, all right, we've got to do this, so we've got to think about this. We don't really have any other choices here. Things are changing pretty quickly. So talk to me, in this last year of change, we've seen massive disruptions and some silver linings for sure, but I'd love to know what IBM and the state of Rhode Island have done together in its challenging time. >> Yeah, so, really interesting partnership that we started with the state of Rhode Island. Obviously, I think this year, there's been lots of things. One of them has been speed, so everything that we had to do has been with haste, right, with urgency. And that's no different than what we did with the state of Rhode Island. The governor there, Gina Raimondo, she took very swift action, right, when the pandemic started. And one of the actions she took was to partner with private firms, such as IBM and others, to really help get her economy back open. And that required a lot of things. One of them, as you mentioned, trust, right, was a major part of what the governor there needed with her citizenships, with her citizens, excuse me, in order to be able to open back up the economy, right. And so, a key pillar of her program, and with our partnership, was around the AI-backed solutions that we brought to the state of Rhode Island, so inclusive of contact tracing, inclusive of work that we had provided around AI-based analytics that allowed really the governor to speak to citizens with hard facts quickly, almost real time, right, and start to build that trust, but also competence, and competence was the main, one of the main things that was required during this pandemic time. And so, there were, through this, the AI-based solutions that we provided, which were, there were many pillars, we were able to help Rhode Island not only open their economy, but they were one of the only states that had their schools open in the fall, and as a parent, I always see that as a litmus, if you will, of how our state is doing, right. And so they opened in the fall, and they, as far as I know, have stayed open. And I think part of that was from the AI-based contact tracing, the AI-backed virtual, sorry, AI analytics, the analytics suite around infections and predictions and what we were able to provide the governor in order to make swift decisions and take action. >> That's really impressive. That's one of the challenges I've had living in California, is you (mumbles) you are going to be data-driven than actually be data-driven, but the technology, living in Silicon Valley, the technology is there to be able to facilitate that, yet there was such a disconnect, and I think that's, you bring up the word confidence, and customers need confidence, citizens need confidence, knowing that what we've seen in the last year has shown in a lot of examples that real time isn't a nice-to-have anymore, it's a requirement. I mean, this is clearly life-and-death situations. That's a great example of how a state came to IBM to partner and say, how can we actually leverage emerging technologies like AI to really and truly make real-time data-driven decisions that affect every single person in our state. >> Mm-hmm. Absolutely, absolutely! Really, really, I think, a great example of the public-private partnerships that are really popping up now, more and more so because of that sense of urgency and that need to build greater ecosystems to create better solutions. >> So that's a great example in healthcare, one that our government in public health, and I think everybody, it will resonate with everybody here, but you've also done some really interesting work that I want to talk about with AI-driven insights into supply chain. We've also seen massive changes to supply chain, and so many organizations having to figure out, whether they were brick-and-mortar only, changing that, or really leveraging technology to figure out where do we need to be distributing products and services, where do we need to be investing. Talk to me about Bestseller India, and what it is that you guys have done there with intelligent workflows to really help them transform their supply chain. >> Yeah, Bestseller India, really great, hugely successful fashion forward company in India, and that term fashion forward always is mind boggling to me because basically, these are clothing retailers who go from runway to store within a matter of days, couple of weeks, which always is just hugely impressive, right, just what goes into that. And when you think about what happens in a supply chain to be able to do that, the requirements around demand forecasting, what quantities, of what style, what design, to what stores, and you think about the India market, which is notoriously a difficult market, lots of micro-segments, and so very difficult to serve. And then you couple that what's been happening from an environmental sustainability perspective, right. I think every industry has been looking more about how they can be more environmentally sustainable, and the clothing industry is no different. And when, and there is a lot of impact, right, so a stat that really has hit home with me, right: 20% of all the clothes that are made globally goes unsold. That's all a lot of clothing, that's a lot of material, and that's a lot of environmental product that goes into creating it. And so, Bestseller India really took it to heart to become not only more environmentally sustainable, but to help itself and be digitally ready for things like the pandemic that ultimately hit. And they were in a really good position. And we worked with them to create something called Fabric AI. So Fabric AI is India's only, first and only, AI-based platform that drives their supply chain, so it drives not only their decisions on what design should they manufacture, but it also helps to improve the entire workflow of what we call design to store. And the AI-based solution is really revolutionary, right, within India, but I think it's pretty revolutionary globally, right, globally as well. And it delivered really big impact, so, reductions in the cost, right, 15-plus reduction in cost. It helped their top line, so they saw a 5% plus top line, but it also reduced their unsold inventory by 5% and more, right. They're continuing to focus on that environmental sustainability that I think is a really important part of their DNA, right, the Bestseller India's DNA. >> And it's one that so many companies and other industries can learn from. I was reading in that case study on Bestseller India on the IBM website that I think it was 40 liters of water to make a cotton shirt. And to your point about the percentage of clothing that actually goes unsold and ends up in landfills, you see there the opportunity for AI to unlock the visibility that companies in any industry need to determine what is the demand that we should be filling, where should it be distributed, where should we not be distributing things. And so I think it was an interesting kind of impetus that Bestseller India had about one of their retail lines or brands was dropping in revenue, but they had been able to apply this technology to other areas of the business and make a pretty big impact. >> Yeah, absolutely. So they had been been very fortunate to have 11 years of growth, right, in all of their brands. And then one of their brands kind of hit headwinds, but the CIO and head of supply chain at that time really had the foresight to be able to say, you know what, we're hitting a problem, one of our brands, but this really is indicative of a more systemic problem. And that problem was lack of transparency, lack of data-driven, predictive, and automation to be able to drive a more effective and efficient kind of supply chain in the end, so, really had the forethought to dive into that and fix it. >> Yeah. And now talk to me about IBM Garage Band, and how's that, how did that help in this particular case? >> Yeah. So, in order to do this, right, it was, they had no use of AI, no use of automation, at the time that we started this. And so to really not only design and build and execute on Fabric AI, but to actually focus on the adoption, right, of AI within the business, we really needed to bring together the leaders across many lines of businesses, IT and HR, right. And when you think about pulling all of these different units together, we used our IBM Garage approach, which really is, there are many attributes and many facets of the IBM Garage, but I think one of the great results of using our IBM Garage approach is being able to pull from across all those different businesses, all of which may have some different objectives, right, they're coming from a different lens, from a different space, and pulling them together around one focus mission, which for here was Fabric AI. And we were able to actually design and build this in less than six months, which I think is pretty dramatic and pretty incredible from a speed and acceleration perspective. But I think even more so was the adoption, was the way in which we had, through all of it, already been working with the employees 'cause it's really touched almost every part of Bestseller India, so really being able to work with them and all the employees to make sure that they were ready for these new ways of working, that they had the right skills, that they had the right perspective, and that it was going to be adopted. >> That, we, if we unpack that, if we had time, that can be a whole separate conversation because the important, the most important thing about adoption is the cultures of these different business units have to come together. You said you rolled this out in a very short period of time, but you also were taking the focus on the employees. They need to understand the value in it. why they should be adopting it. And changing that culture, that's a whole other separate conversation, but that's an, that's a very interesting and very challenging thing to do. I wish we had more time to talk about that one. >> Yeah. It really is an, that the approach of bringing everyone together, it makes it just very dynamic, which is what's needed when you have all of those different lenses coming together, so, yeah. >> It is, 'cause you get a little bit of thought diversity as well when we're using AI. Well, Dominic, thank you for joining me today. Talked to me about what you guys are doing with many different types of customers, how you're helping them to integrate emerging technologies to really transform their business and their culture. We appreciate your time. >> Well, thank you, Lisa. Thanks >> For Dominique Dubois, I'm Lisa Martin. You're watching theCUBE's coverage of IBM Think, the digital event. (upbeat music)

(lively music) >> From around the globe it's theCUBE, with digital coverage of IBM Think 2021. Brought to you by IBM. >> Welcome to theCUBE's coverage of IBM Think 2021, the digital event experience. I'm your host, Lisa Martin. I've got an alumni joining me and a brand new guest to the CUBE please welcome Paul Papas, the Global Managing Partner, for IBM Global Business Services, this is transformation services. Paul, welcome back to the virtual CUBE. >> Thanks Lisa great to be here with you today. And Dominique Dubois is here as well. She is the Global Strategy and Offerings Leader in business transformation services or BTS at IBM. Dominique, welcome to the program. >> Thanks Lisa, great to be here. So, we're going to be talking about accelerating business transformation with intelligent workflows. We're going to break through all that, but Paul we're going to start with you. Since we last got together with IBM, a lot has changed so much transformation, so much acceleration of transformation. Talk to me from your perspective, how have you seen the way that businesses running change and what some of the changes in the future are going to be? >> Well, you hit on two key words there Lisa and thanks so much for that question. Two key words that you hit on were change and acceleration. And that's exactly what we see. We were seeing this before the pandemic and if anything, with the pandemic did when things started started kind of spreading around the world late or early last year, around January, February timeframe we saw that word acceleration really take hold. Every one of our clients were looking for new ways to accelerate the change that they had already planned to adapt to this new, this new normal or this new abnormal, depending on how you view it. In fact, we did a study recently, an IBV study that's our Institute of Business Value and found that six out of 10 organizations were accelerating all of their transformation initiatives they had already planned. And that's exactly what we're seeing happening right now in all parts of the world and across all industries. This acceleration to transform. >> So, one of the things that we've talked about for years, Paul, before the pandemic was even a thing, is that there was a lot of perceived technical barriers in terms of like the tech maturity for organizations and employees being opposed to change. People obviously it can be a challenge. They're used to doing things the way they are. But as you just said, in that IBV survey, nearly 60% of businesses say we have to accelerate our transformation due to COVID, probably initially to survive and then thrive. Talk to me about some of those, those barriers that were there a little over a year ago and how businesses 60 plus percent of them have moved those out of the way. >> You know at IBM we've got 109 year history of being a technology innovation company. And the rate of pace of technical change is always increasing. It's something that we love and that we're comfortable with. But the rate and pace of change is always unsettling. And there's always a human element for change. And the human element is always the rate, the rate setter in terms of the amount of change that you can have in an organization. Our former chairman Ginni Rometty, used to say that growth and comfort cannot co-exist. And it's so true because changing is uncomfortable. It's unsettling. It can be, it can be nerve-racking. It can instill fear and fear can be paralyzing in terms of driving change. And what we also see is there's a disconnect, a lot of times and that IBV study that I was referring to before, we saw results coming back where 78% of executives feel that they have provided the training and enablement to help their employees transform to new required skills and new ways of working but only half of the people surveyed felt the same way. Similarly, we saw a disconnect in terms of companies feeling that they're providing the right level of health and wellness support during the pandemic. And only half of the employees responded back they feel that they're getting that level of support. So, the people change aspect of may doing a transformation or adapting to new circumstances is always the most critical component and always the hardest component. And when we talk about helping our clients do that in IBM that's our service as organization. That's the organization that Dominique Dubois are representing here today. I'm responsible for business transformation services within our organization. We help our clients adapt using new technologies, transforming the way they work, but also addressing the people change elements that could be so difficult and hitting them head on so that they can make sure that they can survive and thrive in a meaningful and lasting way in this new world. >> One of the hardest things is that cultural transformation regardless of a pandemic. So, I can't imagine I'd love to get one more thing, Paul from you before we head over to Dominique. IBM is on 109 year old organization. Talk to me about the IBM pledge. This is something that came up last year, huge organization massive changes last year, not just the work from home that the mental concerns and issues that people had. What did IBM do like as a grassroots effort that went viral? >> Yeah, so, it's really great. So, when the pandemic started, we all have to shift it, We all have to shift to working from home. And as you mentioned, IBM's 109 year old company, we have over 300,000 employees working in 170 countries. So, we had to move this entire workforce. It's 370,000 humans to working in a new way that many of which have never done before. And when we started experiencing, the minute we did that, within a few weeks, my team and I were talking Dominique is on my team and we were having conversations where we were feeling really exhausted. Just a few weeks into this and it was because we were constantly on Webex, we were constantly connected and we're all used to working really hard. We travel a lot, we're always with our clients. So, it wasn't that, you have a team that is adapting to like working more hours or longer hours, but this was fundamentally different. And we saw that with schools shutting down and lock downs happening in different of the world the home life balance was getting immediately difficult to impossible to deal with. We have people that are taking care of elderly parents, people that are homeschooling children, other personal life situations that everyone had to navigate in the middle of a pandemic locked at home with different restrictions on when you can go out and get things done. So, we got together as a group and we just started talking about how can we help? How can we help make life just a little bit easier for all of our people? And we started writing down some things that we would, we would commit to doing with each other. How we would address each other. And when that gave birth to was what we call the IBM Work From Home Pledge. And it's a set of principles, all grounded in the belief that, if we act this way, we might just be able to make life just a little bit easier for each other and it's grounded in empathy. And there are parts of the Plex that are pledging to be kind. Recognizing that in this new digital world that we're showing up on camera inside of everyone's home. We're guests in each other's homes. So, let's make sure that we act appropriately as guests at each other's home. So, if children run into the frame during the middle of a meeting or dog started barking during the middle of a meeting, just roll with it. Don't call out attention to it. Don't make people feel self-conscious about it. Pledged the support so your fellow IBM by making time for personal needs. So, if someone has to, do homeschooling in the middle of the day, like Dominique's got triplets she's got to do homeschooling in the middle of the day. Block that time off and we will respect that time on your calendar. And just work around it and just deal with it. There are other things like respecting that camera ready time. As someone who's now been on camera every day it feels like for the last 14 months we want to respect the time that people when they have their cameras off. And not pressure them to put their cameras on saying things like, Hey, I can't see you. There's no reason to add more pressure to everyone's life, if someone's camera's off, it's all for a reason. And then other things like pledging to checking on each other, pledging to set boundaries and tend to our own self-care. So, we published that as a group, we just again and we put it on a Slack channel. So it's kind of our communication method inside the company. It was just intended to be for my organization but it started going viral and tens of thousands of IBM members started taking, started taking the pledge and ultimately caught the attention of our CEO and he loved it, shared it with his leadership team, which I'm a part of. And then also then went on LinkedIn and publicly took the pledge as well. Which then also got more excitement and interaction with other companies as well. So, grassroots effort all grounded in showing empathy and helping to make life just a little bit easier for everyone. >> So important, I'm going to look that up and I'm going to tell you as a person who speaks with many tech companies a week. A lot of businesses could take a lead from that and it gets really important and we are inviting each other into our homes and I see you're a big Broadway fan I'll have to ask you that after we wrap (giggles) Dominique I don't know how you're doing any of this with triplets. I only have two dogs (Dominique laughs) but I'd love to know this sense of urgency, that is everywhere you're living it. Paul talked about it with respect to the acceleration of transformation. How from your lens is IBM and IBM helping customers address the urgency, the need to pivot, the need to accelerate, the need to survive and thrive with respect to digital transformation actually getting it done? >> Right, thanks Lisa, so true our clients are really needing to and ready to move with haste. That that sense of urgency can be felt I think across every country, every market, every industry. And so we're really helping our clients accelerate their digital transformations and we do that through something that we call intelligent workflows. And so workflows in and of themselves are basically how organizations get work done. But intelligent workflows are how we infuse; predictive properties, automation, transparency, agility, end to end across a workflow. So, pulling those processes together so they're not solid anymore and infusing. So, simply put we bring intelligent workflows to our clients and it fundamentally reinvents how they're getting work done from a digital perspective, from a predictive perspective, from a transparency perspective. And I think what really stands apart when we deliver this with our clients in partnership with our clients is how it not only delivers value to the bottom line, to the top line it also actually delivers greater value to their employees, to the customers, to the partner to their broader ecosystem. And intelligent workflows are really made up of three core elements. The first is around better utilizing data. So, aggregating, analyzing, getting deeper insight out of data, and then using that insight not just for employees to make better decisions, but actually to support for emerging technologies to leverage. So we talked about AI, automation, IOT, blockchain, all of these technologies require vast amounts of data. And what we're able to bring both on the internal and external source from a data perspective really underpins what these emerging technologies can do. And then the third area is skills. Our skills that we bring to the table, but also our clients deep, deep expertise, partner expertise, expertise from the ecosystem at large and pulling all of that together, is how we're really able to help our clients accelerate their digital transformations because we're helping them shift, from a set of siloed static processes to an end-to-end workflow. We're helping them make fewer predictions based on the past historical data and actually taking more real-time action with real time insights. So, it really is a fundamental shift and how your work is getting done to really being able to provide that emerging technologies, data, deep skills-based end to end workflow. >> That word fundamental has such gravity. and I know we say data has gravity being fundamental in such an incredibly dynamic time is really challenging but I was looking through some of the notes that you guys provided me with. And in terms of what you just talked about, Dominique versus making a change to a silo, the benefits and making changes to a spectrum of integrated processes the values can be huge. In fact, I was reading that changing a single process like billing, for example might deliver up to 20% improved results. But integrating across multiple processes, like billing, collections, organizations can achieve double that up to 40%. And then there's more taking the intelligent workflow across all lead to cash. This was huge. Clients can get 50 to 70% more value from that. So that just shows that fundamental impact that intelligent workflows can make. >> Right, I mean, it really is when we see it really is about unlocking exponential value. So, when you think about crossing end to end workflow but also, really enhancing what clients are doing and what companies are doing today with those exponential technologies from kind of single use the automation POC here and AI application POC here, actually integrating those technologies together and applying them at scale. When I think intelligent workflows I think acceleration. I think exponential value. But I also really think about at scale. Because it's really the ability to apply these technologies the expertise at scale that allows us to start to unlock a lot of that value. >> So let's go over Paul, in the last few minutes that we have here I want to talk about IBM garage and how this is helping clients to really transform those workflows. Talk to me a little bit about what IBM garage is. I know it's not IBM garage band and I know it's been around since before the pandemic but help us understand what that is and how it's delivering value to customers. >> Well, first I'm going to be the first to invite you to join the IBM garage band, Lisa so we'd love to have you >> I'm in. no musical experience required... >> I like to sing, all right I mean (laughs) We're ready, we're ready for. So, let me talk to you about IBM garage and I do want to key on two words that Dominique was mentioning speed and scale. Because that's what our clients are really looking for when they're doing transformations around intelligent workflows. How can you transform at scale, but do that with speed. And that really becomes the critical issue. As Dominique mentioned, there's a lot of companies that can help you do a proof of concept do something in a few weeks that you can test an idea out and have something that's kind of like a throw away piece of work that maybe proves a point or just proves a point. But even if it does prove the point at that point you'd have to restart a new, to try to get something that you could actually scale either in the production technology environment or scale as a change across an organization. And that's where IBM garage comes in. It's all a way of helping our clients co-create, co-execute and then cooperate, innovating at scale. So, we use methods like design thinking inside of IBM we've trained several hundred thousand people on design thinking methods. We use technologies like neural and other things that help our clients co-create in a dynamic environment. And what's amazing for me is that, the cause of the way we were, we were doing work with clients in a garage with using IBM garage in a garage environment before the pandemic. And one of our clients Frito-Lay of North America, is an example where we've helped them innovate at scale and speed using IBM garage over a long period of time. And when the pandemic hit, we in fact were running 11 garages across 11 different workflow areas for them the pandemic hit and everyone was sent home. So, we all instantly overnight had to work from home together with relay. And what was great is that we were able to quickly adapt the garage method to working in a virtual world. To being able to run that same type of innovation and then use that innovation at scale in a virtual world, we did that overnight. And since that time which happened, that happened back in March of last year throughout the pandemic, we've run over 1500 different garage engagements with all of our clients all around the world in a virtual, in a virtual environment. It's just an incredible way, like I said to help our clients innovate at scale. >> That's fantastic, go ahead Dominique. >> Oh, sorry, was just said it's a great example, we partnered with FlightSafety International, they train pilots. And I think a great example of that speed and scale right is in less than 12 weeks due to the garage methodology and the partnership with FlightSafety, we created with them and launched an adaptive learning solution. So, a platform as well as a complete change to their training workflow such that they had personalized kind of real-time next best training for how they train their pilots for simulators. So, reducing their cycle time but also improving the training that their pilots get, which as people who normally travel, it's really important to us and everyone else. So, just a really good example, less than 12 weeks start to start to finish. >> Right, talk about acceleration. Paul, last question for you, we've got about 30 seconds left I know this is an ecosystem effort of IBM, it's ecosystem partners, it's Alliance partners. How are you helping align right partner with the right customer, the right use case? >> Yeah, it's great. And our CEO Arvind Krishna has really ushered in this era where we are all about the open ecosystem here at IBM and working with our ecosystem partners. In our services business we have partnerships with all the major, all the major technology players. We have a 45 year relationship with SAP. We've done more SAP S 400 implementations than anyone in the world. We've got the longest standing consulting relationship with Salesforce, we've got a unique relationship with Adobe, they're only services and technology partner in the ecosystem. And we just recently won three, procedures Partner Awards, with them and most recently we announced a partnership with Celonis which is an incredible process execution software company, process mining software company that's going to help us transform intelligent workflows in an accelerated way, embedded in our garage environment. So, ecosystem is critical to our success but more importantly, it's critical to our client success. We know that no one alone has the answers and no one alone can help anyone change. So, with this open ecosystem approach that we take and global business services and our business transformation services organization, we're able to make sure that we bring our clients the best of everyone's capabilities. Whether it's our technology, partners, our services IBM's own technology capabilities, all in the mix, all orchestrated in service to our client's needs all with the goal of driving superior business outcomes for them. >> And helping those customers in any industry to accelerate their business transformation with those intelligent workloads and a very dynamic time. This is a topic we could keep talking about unfortunately, we are out of time but thank you both for stopping by and sharing with me what's going on with respect to intelligent workflows. How the incremental exponential value it's helping organizations to deliver and all the work that IBM is doing to enable its customers to be thrivers of tomorrow. We appreciate talking to you >> Thanks Lisa. >> Thank you >> For Paul Papas and Dominique Dubois I'm Lisa Martin. You're watching the CUBE's coverage of IBM Think the digital event experience. (gentle music)

(serene music) >> From around the globe, it's theCUBE, with digital coverage of IBM Think 2021, brought to you by IBM. >> Hey, welcome to theCUBE's coverage of IBM Think, the digital event experience. I'm your host, Lisa Martin, welcoming back to the program one of our CUBE alumn. Dominique Dubois joins me. She's the Global Strategy and Offerings Executive in the Business Transformation Services of IBM. Dominique, it's great to talk to you again. >> Hi Lisa, great to be with you today. >> So we're going to be talking about the theme of this interview. It's going to be the ROI of AI for business. We've been talking about AI emerging technologies for a long time now. We've also seen a massive change in the world. I'd love to talk to you about how organizations are adopting these emerging technologies to really help transform their businesses. And one of the things that you've talked about in the past, is that there's these different elements of AI for business. One of them is trust, right, the second is ease of use, and then there's this importance of data in all of these important emerging technologies that require so much data. How do those elements of AI come together to help IBM's clients be able to deliver the products and services that their customers are depending on? >> Yeah. Thank you, Lisa. So, when we look at AI and AI solutions with our clients, I think how that comes together is in the way in which we don't look at AI, or AI application solution, independently, right. We're looking at it and we're applying it within our customer's operations with respect to the work that it's going to do, with respect to the part of the operations and the workflow and the function that it sits in, right. So the idea around trust and ease of use and the data that can be leveraged in order to kind of create that AI and allow that AI to be self-learning and continue to add value really is fundamental around how we design and how we implement it within the workflow itself. And how we are working with the employees, with the actual humans, that are going to be touching that AI, right, to help them with new skills that are required to work with AI, to help them with what we call the new ways of working, right, 'cause it's that adoption that really is critical to get the use of AI in enterprises at scale. >> That adoption that you just mentioned, that's critical. That can be kind of table stakes. But what we've seen in the last year is that we've all had to pivot, multiple times, and be reactionary, or reactive, to so many things out of our control. I'm curious what you've seen in the last year in terms of the appetite for adoption on the employees front. Are they more willing to go, all right, we've got to change the way we do things, and it's probably going to be, some of these are going to be permanent? >> Yeah. Lisa, we've absolutely seen a huge rise in the adoption, right, or in the openness, the mindset. Let's just call it the mindset, right. It's more of an open mindset around the use of technology, the use of technology that might be AI backed or AI based, and the willingness to, and I will say, the willingness to try is really then what starts that journey of trust, right. And we're seeing that open up in spades. >> That is absolutely critical. It's just the willingness, being open-minded enough to go, all right, we've got to do this, so we've got to think about this. We don't really have any other choices here. Things are changing pretty quickly. So talk to me, in this last year of change, we've seen massive disruptions and some silver linings for sure, but I'd love to know what IBM and the state of Rhode Island have done together in its challenging time. >> Yeah, so, really interesting partnership that we started with the state of Rhode Island. Obviously, I think this year, there's been lots of things. One of them has been speed, so everything that we had to do has been with haste, right, with urgency. And that's no different than what we did with the state of Rhode Island. The governor there, Gina Raimondo, she took very swift action, right, when the pandemic started. And one of the actions she took was to partner with private firms, such as IBM and others, to really help get her economy back open. And that required a lot of things. One of them, as you mentioned, trust, right, was a major part of what the governor there needed with her citizenships, with her citizens, excuse me, in order to be able to open back up the economy, right. And so, a key pillar of her program, and with our partnership, was around the AI-backed solutions that we brought to the state of Rhode Island, so inclusive of contact tracing, inclusive of work that we had provided around AI-based analytics that allowed really the governor to speak to citizens with hard facts quickly, almost real time, right, and start to build that trust, but also competence, and competence was the main, one of the main things that was required during this pandemic time. And so, there were, through this, the AI-based solutions that we provided, which were, there were many pillars, we were able to help Rhode Island not only open their economy, but they were one of the only states that had their schools open in the fall, and as a parent, I always see that as a litmus, if you will, of how our state is doing, right. And so they opened in the fall, and they, as far as I know, have stayed open. And I think part of that was from the AI-based contact tracing, the AI-backed virtual, sorry, AI analytics, the analytics suite around infections and predictions and what we were able to provide the governor in order to make swift decisions and take action. >> That's really impressive. That's one of the challenges I've had living in California, is you (mumbles) you are going to be data-driven than actually be data-driven, but the technology, living in Silicon Valley, the technology is there to be able to facilitate that, yet there was such a disconnect, and I think that's, you bring up the word confidence, and customers need confidence, citizens need confidence, knowing that what we've seen in the last year has shown in a lot of examples that real time isn't a nice-to-have anymore, it's a requirement. I mean, this is clearly life-and-death situations. That's a great example of how a state came to IBM to partner and say, how can we actually leverage emerging technologies like AI to really and truly make real-time data-driven decisions that affect every single person in our state. >> Mm-hmm. Absolutely, absolutely! Really, really, I think, a great example of the public-private partnerships that are really popping up now, more and more so because of that sense of urgency and that need to build greater ecosystems to create better solutions. >> So that's a great example in healthcare, one that our government in public health, and I think everybody, it will resonate with everybody here, but you've also done some really interesting work that I want to talk about with AI-driven insights into supply chain. We've also seen massive changes to supply chain, and so many organizations having to figure out, whether they were brick-and-mortar only, changing that, or really leveraging technology to figure out where do we need to be distributing products and services, where do we need to be investing. Talk to me about Bestseller India, and what it is that you guys have done there with intelligent workflows to really help them transform their supply chain. >> Yeah, Bestseller India, really great, hugely successful fashion forward company in India, and that term fashion forward always is mind boggling to me because basically, these are clothing retailers who go from runway to store within a matter of days, couple of weeks, which always is just hugely impressive, right, just what goes into that. And when you think about what happens in a supply chain to be able to do that, the requirements around demand forecasting, what quantities, of what style, what design, to what stores, and you think about the India market, which is notoriously a difficult market, lots of micro-segments, and so very difficult to serve. And then you couple that what's been happening from an environmental sustainability perspective, right. I think every industry has been looking more about how they can be more environmentally sustainable, and the clothing industry is no different. And when, and there is a lot of impact, right, so a stat that really has hit home with me, right: 20% of all the clothes that are made globally goes unsold. That's all a lot of clothing, that's a lot of material, and that's a lot of environmental product that goes into creating it. And so, Bestseller India really took it to heart to become not only more environmentally sustainable, but to help itself and be digitally ready for things like the pandemic that ultimately hit. And they were in a really good position. And we worked with them to create something called Fabric AI. So Fabric AI is India's only, first and only, AI-based platform that drives their supply chain, so it drives not only their decisions on what design should they manufacture, but it also helps to improve the entire workflow of what we call design to store. And the AI-based solution is really revolutionary, right, within India, but I think it's pretty revolutionary globally, right, globally as well. And it delivered really big impact, so, reductions in the cost, right, 15-plus reduction in cost. It helped their top line, so they saw a 5% plus top line, but it also reduced their unsold inventory by 5% and more, right. They're continuing to focus on that environmental sustainability that I think is a really important part of their DNA, right, the Bestseller India's DNA. >> And it's one that so many companies and other industries can learn from. I was reading in that case study on Bestseller India on the IBM website that I think it was 40 liters of water to make a cotton shirt. And to your point about the percentage of clothing that actually goes unsold and ends up in landfills, you see there the opportunity for AI to unlock the visibility that companies in any industry need to determine what is the demand that we should be filling, where should it be distributed, where should we not be distributing things. And so I think it was an interesting kind of impetus that Bestseller India had about one of their retail lines or brands was dropping in revenue, but they had been able to apply this technology to other areas of the business and make a pretty big impact. >> Yeah, absolutely. So they had been been very fortunate to have 11 years of growth, right, in all of their brands. And then one of their brands kind of hit headwinds, but the CIO and head of supply chain at that time really had the foresight to be able to say, you know what, we're hitting a problem, one of our brands, but this really is indicative of a more systemic problem. And that problem was lack of transparency, lack of data-driven, predictive, and automation to be able to drive a more effective and efficient kind of supply chain in the end, so, really had the forethought to dive into that and fix it. >> Yeah. And now talk to me about IBM Garage Band, and how's that, how did that help in this particular case? >> Yeah. So, in order to do this, right, it was, they had no use of AI, no use of automation, at the time that we started this. And so to really not only design and build and execute on Fabric AI, but to actually focus on the adoption, right, of AI within the business, we really needed to bring together the leaders across many lines of businesses, IT and HR, right. And when you think about pulling all of these different units together, we used our IBM Garage approach, which really is, there are many attributes and many facets of the IBM Garage, but I think one of the great results of using our IBM Garage approach is being able to pull from across all those different businesses, all of which may have some different objectives, right, they're coming from a different lens, from a different space, and pulling them together around one focus mission, which for here was Fabric AI. And we were able to actually design and build this in less than six months, which I think is pretty dramatic and pretty incredible from a speed and acceleration perspective. But I think even more so was the adoption, was the way in which we had, through all of it, already been working with the employees 'cause it's really touched almost every part of Bestseller India, so really being able to work with them and all the employees to make sure that they were ready for these new ways of working, that they had the right skills, that they had the right perspective, and that it was going to be adopted. >> That, we, if we unpack that, if we had time, that can be a whole separate conversation because the important, the most important thing about adoption is the cultures of these different business units have to come together. You said you rolled this out in a very short period of time, but you also were taking the focus on the employees. They need to understand the value in it. why they should be adopting it. And changing that culture, that's a whole other separate conversation, but that's an, that's a very interesting and very challenging thing to do. I wish we had more time to talk about that one. >> Yeah. It really is an, that the approach of bringing everyone together, it makes it just very dynamic, which is what's needed when you have all of those different lenses coming together, so, yeah. >> It is, 'cause you get a little bit of thought diversity as well when we're using AI. Well, Dominic, thank you for joining me today. Talked to me about what you guys are doing with many different types of customers, how you're helping them to integrate emerging technologies to really transform their business and their culture. We appreciate your time. >> Well, thank you, Lisa. Thanks >> For Dominique Dubois, I'm Lisa Martin. You're watching theCUBE's coverage of IBM Think, the digital event. (upbeat music)

>> Live from Orlando, Florida It's the que covering accelerate nineteen. Brought to you by important >> Welcome back to the Cube. Live from Orlando, Florida at Fortinet Accelerate twenty ninety nine. Lisa Martin Joining and welcoming to the queue for the first time, the CEO and president of Novy Flow. Dominique Jordan. Dominic. Great to have you joining on the Cube at accelerate. So here we are in Orlando, talking about all things cyber security. I just came from the keynote session where Fortinet was talking about how much they're innovating. What? How they're leading from a competitive perspective. What customers air saying why their security fabric is so differentiated? No, the flow is one of their security fabric ready partners. But before we talk about that, why don't you take a minute or two to describe to our audience who know the flow is and what you guys are doing in cybersecurity? >> Yeah, way We came in a little bit by accident. The cyber security. We we've been founded seven years ago, and the idea was to create the very programmable networks. It's very much in line with what we heard today on the keynote, and we became a technology leader in that field as the and software defined networking. And three, four years ago, customers started to use our product, obviously for cybersecurity application. We didn't even know about that. They don't necessarily tell us, and we spend a bit more focus into it. And over time we started to work with fortunate, for example. And now we have a developing. Is Greg relationship great solutions? Also for the for the customers. >> So one of the things that we understand from Fortinet and from all of the conversations that the Cube has globally is is that digital transformation is fundamental to every business to compete right. But as is secure transformation and security transformation, very challenging to do as businesses. And you think of any industry, financial services, retail, consumer packaged goods. As they expand digitally, so does the attack surface. So one of the things that fourteen it talks about is it's not enough anymore to have these point solutions pointed at different, you know, on Prem Cloud edge that the entire infrastructure as it's changing and they attacked services expanding has got to be protected more from an integrated perspective. This notion of the of the security fabric. Talk to us about a fabric ready partnership. What that means to know that though I know that's only in the last six months or so. So walk us through what you did to become a fabric ready partner and what it is that you in forging that are seeing in the market as challenges that you're helping to results. >> Yeah, what we see. Actually, I like to decide the defined that as a battlefield, the attacks are being waged, really, and and the band we feel is the networks of those carriers. There was a government agencies, large enterprise, etcetera, and those those companies are not really taking advantage of their position because, in fact, with the right network fabric the right tools to be able to react, they could actually be very much more powerful. So this is where we are working with forty nine to equip those customers with solutions that are much more agile, more programmable because the network is also evolving. It's not only that the attacks are broader, they also changing the nature of it is changing, and the fact that we came from a background of working at the edge of the networks mostly. Well, I wouldn't mention that before we deployed. Typically at the large tier one carriers all around the world are mentioned. A few tell Strike group, wait deployed at the Hutchison Group Young law, etcetera. And also a two of these five eyes. So government agencies that are engage in fighting these attacks. So So we come with a background of working in a decentralized approach anyway, So it was a very natural evolution. Work was done with Fortinet so far. So what we built so far together we built some integrated solutions s So far, we have two solutions that we are demonstrating two customers. The first one is to allow the large. It tends to be the larger customer fortunate that are making the transition from a in existing appliance to virtual eyes solutions. That's an area where we are very effective at helping them to scale. And those would be for customers that would have say, hundred gig of traffic or more. So we're fortunate we built a and undermanned solution. It's an integrated solution that enables those carriers to are. Those customers could be other kind of customers to gradually grow the number of the EMS that are used in real time for doing whatever Sabbath security job they have to do. And if they the demand comes down, these v EMS were released in the customer data centers. To do some other jobs like this is one of the products that we built together, and we are demonstrating. The second one is a. A feature of that is that we can process about the way this is Ah is able to scale all the way up to six point five terra bits per second. I'Ll repeat that six point five terror bits per second. This is a unheard of and this is, I think one of the interests of Fortinet is working with no visible. We already have developed not really the metal ring system, but all the O. N m features that you demand as a customer to be deployed in the real world. So so that's that. That's the base on. The second option is that we developed is a carry Great Nat again. Same idea. We can scale the Terra great net analysis up to one point six terabit per second. Former, very powerful. They're powerful solutions to meet this this raising the man which you talked about? They say this literally a wave of attacks coming more and more. >> So you mentioned some customers by name. Telstra, for example. CEO to CEO conversations tells, has been around for a long time as the organization expands digitally. And we talked about a minute ago as this the attack surface. What are some of the conversations that you're having with the scene? The C suite about security? It's not just talking to, you know, network security admits. Right? What are those conversations that you're having with the CEO in the C suite that are where they're saying these are my business problems? Dominic, help us solve these problems. >> Well, it comes to two words, basically its scale and are slow flexibility. It comes to that simple. Is this so they are struggling to see how they can cope with the especially the ones that are virtual izing because you end up. Imagine the model is that you go from a very powerful appliance and once you virtual eyes this appliance, you might end up with thirty different servers, you know, running in parallel, you have to have low balancers in front of it. That makes for a very complex and very expensive solution. So that's that's are they searching for? How can we reduce the complexity, for example, one of the advantages of our product working side by side with fortunate. Since we worked at six point five terabytes per second, we do some of the pre processing of the traffic before it hits the virtualized solution forty gate, for example. We have built some blacklist white list we can do also the load balancing. No need to install some additional law balancing can have. That is a kind of a black box I get that does all the required feature to increase the scaling off those those combined solution and the second, the second party flexibility. You got to be able to evolves your solution in time as these attacks are revolving now or product is built from bottom up, and it's built on and infrastructure typically white boxes that are running chips that are programmable by us. So the software, the NASA's it's Gone, is complemented by some very easy to use porting layers if you like. So the Fortinet solution could be easily adapted to this platform and And that's how we can achieve this kind of throughput. And in fact, I will tell to your viewers that we already have built live demos of those solutions in the Sofia anti police lab in France. The labs of Fortinet, Where were you? We're doing demos for the for customers of those solutions. >> So I'MA tell Stir, though, and you said speed and flexibility scale rather the other sailor disability scale. Inflexibility. What are some? How does my business? What am I looking to achieve? A. My looking to scale to x number of users X number of regions. How does how is that measured from, say, a Telstra's perspective as a big business impact that Novy Flow and Fortinet are helping to them to achieve? >> Yeah, the It's really all dimensions way have some challenge just by handling the raw volume of traffics. Sometimes some customers are pumping terra bits of traffic between one country and the other, so that's one. And but it's also geography because your attack and come and any anywhere in your network that the periphery or inside your network so you have to be able to in a centralized away once you detect there's an attack you have to be able to respondent and in some time, and that's how we can do with our programmable infrastructure can actually reprogrammed those air routing tables. You can take some mitigation action, for example, some of some of the bad traffic on the blacklist. If you've looked at it, perhaps you could put it on a white list for serpent of time. Don't don't look at it over and over. Just wait, maybe a little bit those kind of off measures to alleviate the load. So, in fact, it's work more intelligently with the raw volume of traffic that comes to you. So this is one of the real advantage of is the end. So after defined networking applied to a cyber security problem, >> what are some of the other industries that you are seeing that have potential to dramatically benefit from suffer to find networking in cyber security? Knowing that he d threat landscape, it is exponentially growing. Yes, we've got tools like a I and Machine Learning, which we'LL talk about later on the program today with respective forty Gar labs, for example. But of course, so do the attackers have access to utilize artificial intelligence to create even smarter attacks. But from your perspective, what are some of the other industries that are really right to take advantage of SGN and cyber security practices? >> You know, I think all industries are moving to data. There's no exception. I was talking to some guy, an interpreter in Montreuil yesterday's doing farming, but it's high tech farming with several earlier. It's all based on a I. It's all based on data, even those industry that the forming industry thing that may be so every industry will rely on data, and that means it will rely on a network, and it all comes down to the network. You gotta be able to build a cyber security network ready fabric from the bottom up so that your network is one of the key features is actually stop the attacks, and that doesn't matter in which industry you are. I think they you can think about the industry where you have vast volumes of data. They will be most likely the first one to take benefit of these. You know, we talk about countries before, and this is one such an industry, but it certainly where you process the vast amount of traffic. So they taking advantage of our technology, for example. And but I think it will be probably most of the industry will be affected by that shorter later >> and hopefully sooner rather than later, considering how fast all of these opportunities, good and bad, are growing. One of the things sporting that talked a lot about this morning during this section and some of the press releases is this growth that they've experienced growing twenty percent year on year from last year one point eight billion in revenue over three hundred eighty five thousand customers. You're one of the fabric ready partners, of which there are fifty seven. So a lot of growth, a lot of potential. What excites you as the head of no be Flo and your recent and developing partnership with Fortinet for twenty nineteen and beyond were gonna latch onto that growth trajectory. >> Absolute well, you know, when you mentioned high volume of traffic that plays to our cards. So the market is actually coming where we are way have our product runs at six for five terabytes per second, and that's today because we have a *** plans to move to twelve Tara bits and so forth. So for us, it's exciting because we feel we have the right scaling platform and the right program ability. So our customers, fortunate customers together with us can start with the existing. They're powerful platform. But should that evolved, they'LL be able to move to a new level of software new capacity gradually over time. So that's very exciting for us. >> But what about some of the announcements that came out this morning? Over three hundred new features added, for example, that's a tremendous amount of innovation since last year's accelerate. >> Yeah, well, the's features needs also have the right, I would say filtered level of data to be able to do it more efficiently. And that's where we commend we're not inside the subway Security company. We are really complimenting the product of forty nine by playing upstream and doing a pre filtering controlled by the policy management of the Fortunate, the equipment but nevertheless taking up some of the load of it so that the equipment could be more efficient. But just as an example, I read in a magazine a couple days ago that Google is building a A two hundred fifty terabyte cable between North America and Europe. Think about that. It's it's mindboggling is three time Library of Congress per second. And those are the kind of volume of data did you see coming so suddenly? Six point five terabytes per second doesn't sound so big, does it? But in fact, that's the world win today, and we're lucky it may be flow. We invested early on in the software layer that runs on top of these extremely powerful white boxes and were taking advantage of it with Fortinet. >> Gotta deliver that scale, that flexibility and his son's more and more like Speed. Dominic, thank you so much for stopping by the Cuban joining me on the program today, talking about Novy float what you're doing with Fortinet and what excites you about the year ahead >> was a pleasure, Liza. Thank you for >> mine as well. I want to thank you for watching the Cube Lisa Martin live on the Cube from Fortinet Accelerate twenty nineteen in Orlando. Thanks for watching

>> From Tavern on the Green in Central Park, New York it's theCUBE. Covering Veritas Vision Solution Day, brought to you by Veritas. >> Welcome back to New York City everybody. We're here in the heart of Central Park at Tavern On the Green, a beautiful facility. I'm surrounded by Yankee fans so I'm like a fish out of water. But that's okay, it's a great time of the year. We love it, we're still in it up in Boston so we're happy. Dave Vellante here, you're watching theCUBE, the leader in live tech coverage. Nathan Hall is here, he's the field CTO at Pure Storage. Nathan, good to see you. >> Good to see you too. >> Thanks for coming on. >> Thanks. >> So you guys made some announcements today with Veritas, what's that all about? >> It's pretty exciting and Veritas, being the market leader in data protection software. Now our customers are able to take Veritas's net backup software and use it to drive the policy engine of Snapshots for our FlashArrays. They're also able to take Veritas and back up our data hub, which is our new strategy with FlashBlade to really unify all of data analytics onto a single platform. So Veritas really is the solution net back up that's able to back up all the workloads and Pure is the solution that's able to run all the workloads. >> So what if I could follow-up on that, maybe push you a little bit? A lot of these announcements that you see, we call them Barney deals, I love you, you love me, we go to market together and everything's wonderful. Are we talking about deeper integration than that or is just kind of press release? >> Absolutely deeper integration. So you'll see not just how-to guides, white papers, et cetera, but there's actual engineering-level integration that's happening here. We're available as an advanced disk target within that back up, we've integrated into CloudPoint as well. We certify all of our hardware platforms with Veritas. So this is deep, deep engineering-level integration. >> Yeah, we're excited about Pure, we followed you guys since the early days. You know we saw Scott Dietzen, what he built, very impressive modern architecture, you won't be a legacy for 20, 25 years so you've got a lot going for you. Presumably it's easier to integrate with such a modern architecture, but now at the same time you got to integrate with Veritas, it's been around for about 25 years. We heard a lot about how they're investing in API-based architectures, and microservices, and containers and the like, so what is that like in terms of integrating with a 25-year-old company? >> Well I think, from Pure's perspective we are API first, we're RESTfull APIs first. We've done a ton of integrations across multiple platforms whether it's Kubernetes, Docker, VMware, et cetera, so we have a lot of experience in terms of how to integrate with various flavors of other infrastructure. I think Veritas has done a lot of work as well in terms of maturing their API to really be this kind of cloud-first type of API, this RESTful API, that made our cross-integration much easier. >> You guys like being first, there were a number of firsts, you guys were kind of the first, or one of the first with flash for block. You were kind of the first for file. You guys have hit AI pretty hard, everybody's now doing that. You guys announced the first partnership with NVIDIA, everybody's now doing that. (laughs) You guys announced giving away NVME as part of the Stack for no upcharge, everybody's now doing that. So, you like to be first. Culturally, you've worked at some other companies, what's behind that? >> Well culturally, this is best company I've worked at in terms of culture, period, and really it all starts with the culture of the company. I think that's why we're first in so many places and it's not just first in terms of first to market. It's really about first in terms of customer feedback. If you look at the Gartner Magic Quadrant we're up, we've been at leaders quadrant for five years in a row. But this year, we're indisputably the leader. Furthest to the right on the X-axis, furthest north on the Y-axis and that's all driven by just a customer-obsessed culture. We've got a Net Promoter Score of 86.6 which is stratospheric. It's something that puts us in the top 1% of all business-to-business companies, not just tech companies. So, it's really that culture about customer obsession that drives us to be first. Both to market, in a lot of cases, but also just first in terms of customer perception of our technology. >> You guys were a first at really escape velocity, the billion dollar unicorn status, and now you're kind of having that fly-wheel effect where you're able to throw off different innovations in different areas. Can you talk more about the data hub and the relevance to what you're doing with Veritas and data protection? Let's unpack that a little bit. >> Sure, sure, the data hub, we had a great keynote this morning with Jyothi the VP of Marketing for Veritas and he had an interesting customer tidbit. He had some sort of unnamed government agency customer that actually gets penalized when they're unable to retrieve data fast enough. That's not something that many of our customers have, but they do get penalized in terms of opportunity costs. The reason why is 'cause customers just have their data siloed into all these different split-up locations and that prevents them from being able to get insight out of that data. If you look at AI luminaries like Andrew Ng or even people like Dominique Brezinski at Apple, they all agree that you have to, in order to be successful with your data strategy, you have to unify these data silos. And that's what the data hub does. For the first time we're able to unify everything from data warehousing, to data lakes, to streaming analytics, to AI and now even backup all onto a single platform with multidimensional performance. That's FlashBlade and that is our data hub, we think it's revolutionary and we're challenging the rest of the storage industry to follow suit. Let's make less silos, let's unify the data into a data hub so that our customers can get real actionable information out of their data. >> I was on a crowd chat the other day, you guys put out an open letter to the storage community, an open challenge, so that was kind of both a little controversial but also some fun. That's a very important point you're making about sort of putting data at the core. I make an observation, it's not so much true about Facebook anymore 'cause after the whole fake news thing their market value dropped. But if you look at the top five companies in terms of market value, include Facebook in there, they and Berkshire keep doing this, but let's assume for a second that Facebook's up there. Apple, Google, Facebook, Microsoft, and Amazon, top five in terms of US market value. Of course markets ebb and they flow, but it's no coincidence that those are data companies. They all have a lot of hard assets at those companies. They've got data at their core so it's interesting to hear you talk about data hub because one of the challenges that we see for traditional companies, call them incumbents, is they have data in stovepipes. For them to compete they've got to put it in the digital world, they've got to put data at their core. It's not just for start-ups and people doing Greenfield, it's for folks that are established and don't want to get disrupted. Long-winded question, how do they get, let's think of traditional company, an incumbent company, how do they get from point A to point B with the data hub? >> I think Andrew Ng has a great talked-point on this. He basically talks about your data strategy and you need to think about, as a company, how do you acquire data and then how do you unify into a single data hub? It's not just around putting it on a single platform, such as FlashBlade. A valuable byproduct of that is if you have all the stove-piped data, though you probably in terms of your data scientist trying to get access to it, now have to, they have 10 different stovepipes you've got 10 different VPs that you have to go talk to in order to get access to that data. So it really starts with stopping the bleeding and starting to have a data strategy around how do we acquire and how do we make certain or storing data in the same place and have a single unified data hub in order to maximize the value we are able to get out of that data. >> You know when I talked to, I'll throw my two cents in, I talk to a lot of chief data officers. To me, the ones that are most insightful talk about their five imperatives. First of all, is they got to understand how data contributes to monetization. Whether it's saving money or making money, it's not necessarily selling your data. I think a lot of people make that mistake, oh I'm going to monetize my data, I mean I'm going to sell my data, no, it's all about how it contributes to value. The second is, what about data sources? And then how do I get access to data sources? There's a lot implied there in terms of governance and security and who has access to that. And in the same time, how do I scale up my business so that I get the right people who can act on that data? Then how do I form relationships with a line of business so that I can maximize that monetization? Those are, I think, sensible steps that aren't trivial. They require a lot of thought and a lot of cultural change and I would imagine that's what a lot of your customers are going through right now. >> I think they are and I think as IT practitioners out there, I think that we have a duty to get closer to our business and be able to kind of educate them around these data strategies. To give them the same level of insight that you're talking about, you see in some chief data officers. But if I looked out at the, there's a recent study on the Fortune 50, the CXOs, and these aren't even CIOs, they're actually, we think as IT practitioners that the cloud is the most disruptive thing that we see, but the CEOs and the CFOs are actually five times more likely to talk about AI and data as being more disruptive to their business. But most of them have no data strategy, most of them don't know how AI works. It's up to us as IT practitioners to educate the business. To say here's what's possible, here's what we have to do in order to maximize the value out of data, so that you can get a business advantage out of this. It's incumbent on us as IT leaders. >> So Nathan, I think again, that's really insightful because let's face it, if you're moving at the speed of the CIO, which is what many companies want to do, because that's the so called, fat middle and that's where the money is. But you're behind, I mean we're moving into a new era, the cloud era, no pun intended, is here, it's solid but we're entering that data of machine intelligence and we built the foundation with the dupe even, there's a lot of data now what do we do with it? We see, and I wonder if you could comment on this, is the innovation engine of the future changing it? It use to be Moore's Law, we marched to the cadence of Moore's Law for years. Now it's data applying machine intelligence and then, of course, using the cloud for scale and attracting start-ups and innovation. That's fine because we want to program infrastructure, we don't want to deploy infrastructure. If you think about Pure, you got data for sure. You're going hard after machine intelligence. And cloud, if I understand your cloud play, you sell to cloud providers whether they're on-prem or in the public cloud but what do you think about those? That innovation sandwich that I just described and how do you guys play? >> Well, cloud is where we get over 30% of our revenue so we're actually selling to the cloud, cloud service providers, et cetera. For example, one of the biggest cloud service providers out there that I think today's announcement helps them out a lot from a policy perspective actually used FlashBlade to reduce their SLAs, to reduce their restore time from, I think, it was 30 hours down to 38 minutes. They were paying money before to their customers. What we see in our cloud strategy is one of empowering cloud providers, but also we think that cloud is increasingly, at the infrastructure layer, going to be commoditized and it's going to be about how do we enable multicloud? So how do we enable customers to get around data gravity problems? I've got this big, weighty database that I want to see if I can move it up to the cloud but that takes me forever. So how do we help customers be able to move to one cloud or even exit a cloud to another or back to on-prem? We think there's a lot of value in applying our, for example deduplication technology, et cetera, to helping customers with those data gravity problems, to making a more open world in terms of sharing data to and from the cloud. >> Great, well we looked at Pure and Veritas getting together, do some hard core engineering, going to market, solving some real problems. Thanks Nathan for hanging out, this iconic beautiful Tavern on the Green in the heart of New York City. Appreciate you coming on theCUBE. >> Thanks Dave. >> All right, keep it right there everybody, Dave Vallante. We'll be right back right after this short break. You're watching theCUBE from Veritas Solutions Day, #VeritasVision, be right back. (digital music)