(upbeat music) >> Everybody, welcome to this special digital presentation where we're tracking the rebirth of Oracle Consulting. And my name is Dave Vellante, and we're here with Aaron Millstone who's the senior vice president of Oracle Consulting. Aaron, thanks for coming on, good to talk to you. >> Dave, appreciate you having me and I like the introduction of a rebirth of Oracle Consulting. >> Well, it really is I mean, you know, you guys have gone from staff augmentation to being much more of a strategic partner and we're going to talk about that. But I want to start with this theme that you have about empowering the autonomous enterprise. Sounds good, you know, nice little marketing tagline. But give us what's behind that, put some meat on the bone? >> Sure, so you know, what we define as autonomous enterprise is really using artificial intelligence, using machine learning and using it to cognitively understand your actual data and processes you're using for your enterprise. And then really embedding that into everything you're doing as a company, and using it to be both drive optimization and costs, and increasing revenue. And I know that's a lot of kind of consulting speak. So, we tend to think about what we've been talking about in terms of what we call tri-modal IT. This is probably the most exciting space that I've really thought through with my team, as we build up a new consulting business, you pull it out, but this is really about pivoting away from the systems of record and the systems of interaction, and really building up the systems of intelligence capabilities that we see all enterprises needing to invest in heavily, if they're not already investing there already. >> Well, I want to talk about a couple of things there. You know, one is that notion of lowering cost or increasing revenue and you're right people say, Oh, yeah, that's consultancy people, but a good consultant digs in and starts peeling the onion. Well, how do you actually make money? You know, where are the inefficiencies in your business? And that's really what you're talking about, and that's what every business wants to know, right? That's the end game, but the how to is really what separates the good consultants from the pack. >> Right right. And we're, you know, again, we're on this journey now, we've been, you mentioned it right. I'm two years into Oracle Consulting. Myself, I spent 23 plus years at Accenture, where I was a managing director with them and part of their North American leadership team. When I came over to Oracle consulting we did, we pivoted from what you called staff augmentation business to a basic set of offerings, which were things that you recognize right migration, services of workloads to cloud or integration or security work or even, step paths for SAS augmentation that we would do, but you know, pretty basic services. We're now pivoting again into sort of two areas infrastructure and transformation, which is really our bold costs take out play, as you just said, and sort of good consultants know how to do that. And really what that is, is we're going and looking at companies that still have traditional data centers, or maybe they've got some things on clouds, and something's still in traditional data centers. And we're coming in, and we're saying there's a business case here, that looks at your total cost of ownership. And we think we can take out between 40 and 65% of your run rate costs, and that's everything from, facilities, fire suppression systems, through to the actual compute cost, through to the labor that's required to do the physical hands on activities in the data center. So, we have that sort of capability and we're pushing customers hard in that space at the moment, and then driving that into a secondary conversation system and by the way, with all these savings, you kind of have to choices. You can pocket the savings, obviously or we would propose that you go into what we're calling the autonomous enterprise space, and really building up your artificial intelligence machine learning capability with centralized capabilities, centralized data, versus letting every line of business, every department do it on their own. >> Now, the other thing a good consultant does is they make the initiative self funding, and that's a win win you keep getting paid, the customer makes money, that's a good thing. But I like the idea, you're starting with the obvious business case of cost, and I think I heard you really attacking OPPEX, labor is obviously big component of that, but it's not just labor, and then you transition if they don't pocket the gain to a gain sharing going forward to look for new revenue. Did I get that I get that right? >> Yeah, you actually got that right. And actually, what I'll tell you too, is I think the labor piece, again, you know, I came from Accenture, Accenture is big outsourcing company, big technology consulting, big strategy consulting. You know, I went in for years and did pitches on outsourcing arrangements which were fundamentally lower cost bodies running in a more effective way. What we're finding or what I'm finding with customer conversations over the last two years at Oracle has been actually I think, data centers are not, there's nothing competitively advantageous about having a data center if you're a company, there is a lot of advantageous. There's an advantage to having cloud and what we're seeing is that companies that might have outsourced their data center are just the lowest cost provider are now considering insourcing or co-sourcing as they pivot the cloud. So the funny thing is actually labor savings is not the big driver of that 40 to 65%, that plays a role of course, that's how you get to the 65%. But even go into the 40% you can get there by insourcing your labor and bringing them in house and recognizing that the speed at which you can operate on your cloud gives you a competitive advantage. >> So this requires a whole new skill set for Oracle, you mentioned, you came in from Accenture where I talked to another number of other folks in Oracle's North America Consulting Operation that came from, brand name firms, we're going to be talking to Deloitte we have and will continue. So there I know, a big part of you talk about the skills transformation that you've affected inside of Oracle Consulting. >> Sure, yeah I mean, it started when I showed up. It was primarily a staff augmentation business in our commercial space in particular, you know, if you need a DBA, here's a DBA. If you need a SAS admin, here's a SAS admin. Here's the hourly rates and quite frankly, very, very talented group of people, very talented, but focused on doing, you know, sort of nuts and bolts level work, very deep work on the Oracle technology stack, but also weren't particularly cloud certified. So we started by focusing on getting the team certified in our cloud products, invested a ton of hours, thousands and thousands of hours in training. It takes you know, we're doing something like six months investment initially to get people up and certified on multiple cloud products that Oracle is selling. And then right from there, we started putting together our basic offerings, again moved from staff augmentation to saying, look, would you like to move a workload. To move a workload is going to cost a fixed price, whatever that is 100, $200,000 move away from rate card conversations with augmentation. And we shifted the commercial contracts that had payments based on outcomes so they don't move successfully, there's no payment. And so you know that was really the focus. >> I'm going to come back to this notion of gain sharing and particularly focus on the revenue side for a moment. You mentioned a what I'll call a buzzword tri-modal IT and a buzzword because Gartner kind of with bimodal IT popularized that concept. And I think part of the problem that people had with bimodal IT was kind of had the legacy systems of record and then you had all the new cool stuff, the big data and you know now AI and systems of engagement and so forth. And everybody wanted to go to the ladder and run away from the former. But now, if I understand tri-model IT, you're talking about bringing machine intelligence to both of those spheres such that people can stay current, stay relevant and add new value to their organization. >> Yeah, that's exactly it. And we're trying to bring it to both but we're trying to make it its own sphere, independent of the other two. So, again, as we looked at this consulting evolution, I didn't come over to Oracle and Oracle is not interested in us, creating a consulting business, that's a me too consulting business that kind of looks like whatever everyone else is doing. So the goal really was okay. So if we started with sort of staff augmentation, and you know, really Oracle's legacy, a system of record stuff, we sell big back office systems, we have mission critical databases. Like it's the clunky stuff that has to work, but really at the end of the day, that's our heritage, going over to the systems of interaction which is, where the bimodal IT really came in from Gartner. That's a pretty saturated place, so again, coming from the background, I had a consulting, I looked at all the eight design agencies that were out there that were all selling digital, and we looked at the digital sales tactics going on, we're like, well, that's pretty saturated, it's not really a smart place for us to go make a lot of headway into. And so we looked and said, well really, the next layer, the next evolution of IT is this third sphere systems of intelligence. And really, since Oracle is, our heritage is mission critical and data, fundamentally, the logical step for us was to go okay, systems intelligence are powered by data, and they serve artificial intelligence as the primary consumer. So again, our thought process was you have a system of record which is process centric and really geared towards the CFO or a head of HR, you have systems of interaction, which is really geared towards the users, it's trying to make business frictionless. Those users can be consumers, they can be employees, whomever. And then systems intelligence is around artificial intelligence is the primary consumer of it. I mean really pivoting to that, and then making that something that is pervasive and structurally place across both those other two spheres, really felt like where we should be differentiating. When I brought in the talent rate that we looked to bring in, we were getting kind of affirmation that, yeah, the best talent in the market was starting to see this trend and so we kind of knew we were onto something there. >> Yeah, I mean, that makes a lot of sense, because as you as you point out, some of those new workloads, many of them are very consumer oriented, that's kind of you know, not your wheelhouse. I mean, that's your customers are, selling to consumers, but Oracle's B2B, hardcore data mission critical. But let me ask you, to that make sets, but by your cloud, you were sort of a later entrant into cloud. So where does cloud fit into this? How do you respond to when customers say, yeah, but you know, you guys were late on the cloud. >> Yeah, we are definitely late coming to cloud, like there's no two ways about it. I mean, what we've got is we have what we call a Generation 2 Cloud. And I jokingly tell customers that we have a late mover advantage. And that late mover advantage basically means that we've looked at what the first generation clouds have done. And quite frankly, they're great at what they do, they're fierce competitors, they're tough to compete with, they've got a lot of mindshare, but they fundamentally were about targeting consumers, or targeting enterprise collaboration tools, so if you want cat videos, if you want to watch humorous videos that people filmed and posted on social media, those are great clouds for that stuff. But if you want really mission critical enterprise cloud workloads, that's where we come into play. And so when you start to look at really the key differentiators in our cloud and through out, at least this is how I describe it to customers. So, we look at sort of three layers, we have an autonomous capability both on our operating system and our database. What that basically means is that we have machine learning and artificial intelligence that's driving the key, administrative activities in our cloud, we then have our Exadata platform. So Exadata for us is a secret weapon, we think that it is a differentiator in our products. And so, Exadata for those watching that doesn't know what it is, so Exadata emerged out of the Sun acquisition that Oracle did. It is purpose built hardware that is engineered for our software products, specifically our databases. And now we've taken that concept and moved it into our cloud and so customers can come in and take very intensive enterprise, mission critical workloads, run them straight in our cloud. And then, when we look at the last point, it's probably security where, again, we have total segmentation of our security layers from the customer workloads. So again, we've taken the concepts that first generation cloud providers have implemented, and they've scaled it globally. So it's really tough for them to walk back on it, it's a huge investment and we're now gone into a Generation 2 Cloud and quite frankly, I think that's what this is the frontier that everyone's racing to kind of grab. >> You know, we actually in our community, talk to a lot of Exadata customers and they get very intense, they do some really hardcore things with with Exadata. To me, the key to your cloud strategy, and specifically Exadata is you've got the same exact infrastructure, control plane, data plane, software, either on prem or in the cloud. So that's your same same narrative. But the real key, new key anyway is what autonomous, tell me if you agree with this. What autonomous gives you a scale, because as you say, you're related to cloud, you're not a hyper scalar in that sense, you're not selling just, race to the bottom infrastructure as a service. You're bringing applications and mission critical applications, so eponymous gives you the ability to scale and compete more effectively with some of those other, earlier movers. You buy that? >> Yeah, absolutely. So scaling and scaling in terms of, what has been historically human activities, when I say human activities, we're not replacing the humans, we're making some of the human activities that were highly repetitive way more efficient. So easy example I can give you is patching. Like security(mumbles) bases are very time consuming, I've talked to customers as recently as a couple weeks ago, that are three years behind on their patching. And when I look at that, it's you're like, why wouldn't you consider autonomous, they have their board of directors and their auditors are actually now demanding that they do something different about their patching problems. And they're talking about, man months, people months of trying to roll out this patching, and they're worried about breaking stuff, and they're worried about human error. Like when you look at something like autonomous, that patching would take place, pretty much instantaneous with no downtime. And we've seen it in our own cloud and our own services internally and we're able to patch, thousands and thousands of cores very, very quickly. >> So we got to wrap but I wanted to close on sort of the, I mean, again, we talked about good consultants and good consultants have continuous improvement mindset. They got a North star that they really never get through and that keeps moving because you got to keep innovating, you got to keep disrupting yourself, so maybe you could end by sort of talking about some of the things you're watching, some of the milestones you want to hit and some of that transformation that you want to keep going. How are you going to achieve that? >> Yeah, and it will skip some of it, when we hit the Deloitte segment too, but like we're definitely we've moved from, we've definitely move from the staff augmentation to basic offerings. We're now beyond that we're starting to sell the infrastructure lead transformation plays. What's exciting to me about that with our customers is, you know, Oracle's a big complex enterprise, as you'd expect with a company that has a tremendous amount of technology. We're now bringing holistic approaches to our customer say, let us help you optimize everything end to end, let's look at your data center, let's not look at a narrow slice, let's not look at just SAS admins and DBAs, we're looking at things comprehensively. So moving there has been a pretty big milestone for us to hit, we've started to get some good momentum with our customers. Our next milestone is really going to be taking that autonomous enterprise and blowing it out. We're in use case and incubation period right now with that, but again we've got some, I would argue we have the best talent in the world right now that thinks about this stuff and not just thinks about it from a pure technology standpoint, but thinks about how to actually make it effective for the business. And so once we get some of those motions going, like the use case for the autonomous enterprise that's artificial intelligence driven, it should have a continuous pace of change, and it's going to start to evolve in areas that you know, quite frankly, we can't even predict yet. But we're excited to see where it leads. >> Alright, thanks for spending some time with us. I am very excited to talk about that sort of collision course between your deep tech capabilities as Oracle as a product company and this, the Global SI, Deloitte, we're going to bring in those guys in a moment. So thanks very much for taking us through the transformation and great job, good luck. >> Thank you, appreciate it. >> All right, and thank you, everybody for watching. Keep right there, we'll be back with more coverage of Oracle's transformation. Right after the short break, you're watching the CUBE. (upbeat music)