 Live from Las Vegas, it's theCUBE! Covering AWS re-invent 2019. Brought to you by Amazon Web Services and Intel, along with its ecosystem partners. Welcome back to Las Vegas, everybody. We're here live at the Sands Convention Center. You're watching theCUBE, the leader in live tech coverage. We go out to the events and extract the signal from the noise, and this is re-invent 2019. The seventh year theCUBE has been here. I'm Dave Vellante with my co-host, Justin Warren. Sesh Ayers here, he's the managing director and senior partner at BCG, and he's joined by Alan Chen, he's the associate director of software engineering at BCG. Gents, welcome to theCUBE, good to see you. Thank you for having us. So we're going to talk about AI, we're going to talk about machine intelligence, digital transformation, but I want to start with this concept that you guys have put forth, and you're putting it to action with some of your clients, I'm sure, of this bionic organization. Yeah, it's a catchy term, but what's behind it? What's a bionic company? So if you think about the next 10 years, we believe that it's going to be the era of the bionic organization, where the bionic organization is essentially humans and machines coming together, the bio and the nick, right? We believe that we are at a point now where the power from AI, the power from machines, combined with the intrinsic human potential coming together delivers a very, very different set of outcomes. We get to outcomes largely on three fronts. The first is around customer experiences and relationships. You take that to a really new level. The second thing is in operations, you drive to a lot more productive set of operations with through automation. And the third thing is innovation. The rate of innovation is just going to increase significantly and we're seeing a lot of that today at Reinvent here. So you're optimists for the future, right? You don't want to pave the cow path, you don't want to protect the past from the future, but at the same time, people are concerned, right? Machines are replacing humans and they always have, but for the first time in history, it's with cognitive functions. So I'm sure you guys are having these conversations with your clients. Maybe that's one of the blockers, is that sort of perception that, you know, it's going to cause too much disruption, but maybe you could talk about that. How do I get to become a bionic organization? What are some of the barriers that I have to go through? I think the biggest thing is we are actually getting to an organization where technology continues to augment the human. So it's not substituting or replacing the human, it's really augmenting the human. So how do we take human performance and organizational performance to a next level by bringing them together? So it's always about them coming together. When we think about barriers, the real barriers actually are organizational models and old ways of working. They are legacy technologies. It's the lack of access to data that we can leverage to actually convert that into insightful outcomes using AI. And the lack of talent. So we really are at a point where, you know, we don't have enough digital and AI talent out there. Andy today talked about training as one of the core tenets of what you do to take an organization to leverage technologies that we have today. So those are the things that are barriers today that we're working with our clients on to overcome to be able to extract the full potential of what we can do. So Alan, maybe you could talk a little bit about BCG's AI business. How do you guys look at it? Maybe share that with our audience. I mean, as Sish mentioned, the Bionic organization really has two parts, right? It has the human element and it has the machine element. And AI is really the thing that underpins the backbone for the machine element. But you can't really disconnect it from the human because, you know, as we see with our clients, if you just do the algorithms themselves, the algorithms can't change the business, right? You can't remove the algorithms from the context of the business, the people who need to make the cultural changes, the organizational changes, the priority changes to actually put those algorithms into action. So we, of course, as a company that helps clients go through this transformation, we have to usher along the human change. But for the AI and machine learning change, you know, we bring a lot of the best talent that we have. You know, we've got 850 data scientists and engineers around the world helping our clients go through this transformation. And, you know, we build lots of really, really interesting technology. For example, we've got a platform called Source AI that we use to facilitate the building of these AI models and these advanced analytics use cases to accelerate at least the machine portion of that journey. Do you have a discrete AI business practice or is it part of sort of a client's digital transformation? Will you bring in that expertise? Yeah, so within BCG, we have a group called BCG Gamma, which is the arm of the company that focuses solely on AI and machine learning use cases. But the thing is, our model isn't just to kind of embed ourselves into your company and try to, like, take root and be there forever. We want to empower these companies to kind of kickstart their journey so we can go in, we help them get started, prove out a few use cases, and then we actually train and transfer them so that they can make sure that the programs that we helped plant the seeds for end up being long-term, sustainable programs for them. Teaching them the fish is exactly. When we think about what really drives impact and outcome at clients, it's all about bringing together the different capabilities that we have. So we have our heritage strategy consulting business. We have Gamma, which is our AI at scale, data analytics business. We have BCG Digital Ventures, which is all about incubating new companies and taking them out of market. And then we have our Platinian team, which is all about driving new architectures, new technologies in terms of driving adoption at clients. So all these capabilities typically come together at a client for us to deliver impact at the end of the day. Examples of where you've implemented some successes? I think one great example that we have is around when we think about customer experiences and customer engagement. We have recently done a piece of work with United Airlines that's actually getting showcased here at AWS Reinvent, where we really used personalization technology that we have with our partner, formation.ai, to really deliver a new level of customer experience and engagement for United customers. So we call it Miles Play. And you can actually, I don't know if you guys are United customers. I know you guys travel a lot. So Miles Play is a way in which we have actually really leveraged AI and gamification inside of the United app to really drive a different level of experience for customers. So that's one example that are many, many others. We are here at AWS Reinvent, as you point out. And the talk of transformation was part of the keynote this morning with Andy Jassy. A lot of that is around organizational change, but this is also a cloud show. So how does this work that BCG is doing with AI? How does that interact with the cloud? And how does that link into that idea of organizational transformation? So when we think about, again, I'll go back to the Bionic organization. We see, as we move towards this new organization that's bringing together data technology as well as organizational constructs, there are four things that we think of. We think about purpose at the core. So what is the reason that an organization exists and how do we make that alive and bring it alive? I think there's a second around data and technologies. So what can you do with AI? What can you do with data? How do you really drive modular technologies to adopt them to drive change? And then there's a third around people and organization. So how do you drive new organizational models to get an organization to deliver to the potential? And how do you bring new talent? And Andy talked about re-skilling today or training people. And then lastly, leadership. How do you bring in a different style of leadership? We call it jazz leadership, where you really have to bring different parts of your organization to, and help them orchestrate to get to an outcome rather than a more command and control style approach. So all of these are the pieces that we see coming together and that's what we work with our clients on to move them from where they are today to where they will be in the next five years. Alan, you have software in your title. So I'm curious as to what kind of tooling that you guys have built that you apply in your client situations. Yeah, so we work with a lot of different clients in a lot of different industries and a lot of different use cases and even though we treat every client as a unique situation, there are patterns that begin to emerge and we want to make sure that, in order to provide the most value to our clients, we want to be able to quickly prove out wins and use cases and one of the ways that we're able to do that is building software products that facilitate those things. And so, we've got data scientists that go through this whole machine learning pipeline, even though the use cases are different, the challenges are kind of the same no matter what. So you go through the process of how do you get access to data? Once you have access to data, how do you begin experimenting with models? Once you've experimented, how do you begin to consolidate the knowledge of the team to start evaluating models in a collaborative way? And once you have a model that you decide is good, how do you deploy that into a client environment? In many cases, it's going to be cloud because in order for these clients to really see the value of these AI programs, it's got a scale and so we work very closely with partners like AWS to ensure that we can bring the most scalable AI solutions to bear for our clients. And so we build platforms like Source AI to facilitate that entire journey from data access all the way to deployment and scale. And then depending on the verticals, we also have other products that are more use case specific, right? So we work with a lot of airlines to actually do airline scheduling for their airplanes, gate scheduling, routing bags and so while we have Source AI underpinning the platform, airlines have very, very unique problems of their own that are very, very interesting to solve and so we build products to cater to those industries specifically as well. One other piece that I would add is for the retail industry, for example, markdowns is a big topic. So how do you get the best price for the given inventory that you have? We again have AI based solutions that drive markdowns and take the profitability or the revenue of a client to a better level than that I think. One of the things that we see is many of our clients want to get increasingly close to their customer to have that one-on-one relationship that traditional marketing can never afford you, right? So with things like markdown and personalization, we can gather all this data, use the latest AI techniques and begin to start giving offers and discounts and promotions and offers to people on a one-to-one basis rather than marketing to a cohort of people. So a lot of these are functional areas that are like particular problem domains that have particular technological solutions and then the pace of technology continues to change. We've seen that for decades but it seems that this transformational agenda that we need to have has a lot to do with the humans and that problem doesn't really seem to have changed to me in the last several decades. I mean, BCG has been around for a very long time, became famous back in the 80s for doing a lot of the same sort of transformational ideas but how do you transform your organization? So what is it about cloud and AI today that's changed the nature of organizational change? It's a lot of change in there. My sense is if you think about, maybe there are two points to make here and then Alan, you should add on. I think one is it's always easy to bring AI and data and do a proof of concept, right? And to show that something has potential. Taking that potential to impact and outcomes requires it to move to being at scale, right? So one of the big changes that we are seeing is we have to take these AI technologies and really deliver them at scale. So that's one piece of it. I think the other piece that really becomes important is leveraging AI for the right context in which you're applying the solve for. So you need to go into targeted spaces. As Alan said, certain use cases that have huge impact and go after it and deliver value there as opposed to trying to do something a lot more expansively. So how do you now go into specific industries and identify unique areas that have a lot of promise and potential and then put your energy against that to get to again impactful outcomes, right? We had that example around markdowns. We've talked about airline optimization. We've talked about personalization. All of these are good examples of very targeted areas that have a lot of potential to really drive value. Yeah, like one of the things that I see that cloud has changed the transformation process is just the ability for us to very quickly experiment with new use cases, right? In terms of the types of tools and building blocks that cloud vendors like AWS provide us, you know, we could think of an idea, an AI-powered use case one day and we could start cranking the gears on it the next day. And if it works, we can just start scaling it up and if it doesn't, we turn it off and it's a very, very kind of low regret, low risk kind of thing, whereas back in the day where everybody is building data centers in order to try something new, you have to capitalize the cost of actually buying all this hardware, filling up your data center, staffing it and then if it turns out that that use case didn't pan out, well, now you've got loads of hardware that's just kind of costing you tons of money every day but with the cloud, you know, we can just move so much more quickly and take a lot more bold risks. It's the cost of, I think it's the cost of experiments and the speed with which you can bring teams to get to outcomes, right? So Andy, again, talked today about an integrated development environment for data scientists, right? How do you really bring data scientists, get them to start working on something, experiment with it, start to show some potential and then really scale it? Those are things that we believe, you know, cloud has really immensely changed. The other thing is access to massive, massive data sets, right? Andy today talked about how different data sets can be brought into Amazon and the ability to do that easily today. So how can you really create value from these billions and billions of rows of data that are sitting out there in your enterprise and converting that into something meaningful? So that approach and that philosophy of sort of low risk, pick a winner, scale it. First of all, the CFO loves it. I think generally the organization is going to see value. It's tangible. However, I think about digital disruption and if you think about the successful digital companies they've got data at the core. So my question to you is, are you helping these sort of incumbents, you mentioned United, I'm sure there are many others that you work with, are they able to sort of transform and put data at their core, become a digitally transformed organization before somebody disrupts them? Will those, maybe not quick hits, but those focused projects, will they ultimately lead to an outcome that transforms them in the way that Jassy was sort of putting forth today? I think so. I think that's the promise of the next five years. So if I think about, when we talk about a bionic organization we talk about 30 to 50 processes that that organization will have. I mean my sense is those processes will have 50 to 60% of the components that are driven by AI or data. If you think about an incumbent today working in manual processes, legacy systems, they are going to actually move to leveraging AI and data and new ways of working to transform that legacy environment into a next gen technological environment but also ways of working and then bringing all of that together to drive a very different level of engagement with the customer, experiences with the customer, how they actually run their operations, do it much faster, reduce cycle time, and then also the data and pace of innovation. You can see today the number of new features that got released on AWS and it's all been in a year and there were like 30 of them. So how do you really drive to that level of rate and pace of innovation? We'll see all of those happening in all of these traditional industries over the next five years. And if they don't move, they're going to probably be in big trouble. They're going to be in big trouble, they're going to die. All right, guys, thanks so much for coming to theCUBE. It was great, great conversation, great to have you. Thank you. Thank you so much for the time. All right, keep it right there, everybody will be back with our next guest. We're up to this short break, Dave Vellante for Justin Warren from AWS Reinvent 2019. Right back.