Live from Las Vegas, it's theCUBE covering the AWS Accenture Executive Summit. Brought to you by Accenture. Welcome back everyone to theCUBE's live coverage of the AWS Executive Summit here at the Venetian. I'm your host, Rebecca Knight. We have two guests for this segment. We have Akhtar Saeed, VP Solution Delivery Southern Glazer Wine and Spirits, and Michael Noel, Managing Director Applied Intelligence at Accenture. Thank you so much for coming on the show. Thank you. >> Thank you for having us. I think this is going to be a fun one. We're talking about wine and spirits. Absolutely. So Akhtar, tell our viewers a little bit about Southern Glazer. Yeah, so Southern Glazer Wine and Spirits is a privately held company. We are in about 44 states, and we are the largest distributor of wine and spirits. Okay, and yeah, and 44 states, what was the business problem you were trying to solve in terms of the partnership you formed with Accenture? Yeah, so we started this initiative before Southern and Glazer merged, And that was in... It was 2016. So Southern was already looking at how to enhance our technology, how to provide better data analytics, and how to create one source of truth. So that's what drove this. And we were looking to partner with appropriate system digger and right technology to be able to help deliver value of the company, to be able to do analytics, and get analysis. So you had two separate companies merging together and I like this idea, one source of truth. What does that mean? What did that mean for you? Well what it means to us is that since you have quite a few data marks out there, and everybody is looking at a number differently, we spend lot of time trying, hey, is this right or is this right? So we want to bring all the data together saying this is what the data is. This is how we're going to standardize it. That's what we tried to do. Okay, so this one source, now Michael, in terms of that, is that a common, common issue, particularly among companies that are merging, would you say? No, absolutely. You have businesses that might be in the same industry, but they might have different processes to try to get to the same answer, right, and the answer's never really the same. So having this concept of a clean room that allows you to take, you know, your various aspects of a business and combine it from a data point of view, a business metrics point of view, and a business process point of view, this one source helps you consolidate and streamline that so you can see that integrated view across your new business model, really. So where do you begin? So you bring in Accenture and AWS, and where do you start? Yeah, as like you mentioned, 2016 Glazer and Southern Wine Spirits came together merge. It actually accelerated process because we needed what Mike mentioned is a clean room. Where we could put this data and wouldn't have to merge our data centers on day one, and have the reporting, common reporting plant from being available for the new SGWS. And that's what we started. So we said okay, what is the key performance indicators, they key metrics that we need going into day one? And that's what we want to populate the data with to begin with, to make sure that information is available when the day one for merger comes through. Okay, and so what were those indicators? There were several indicators. There were several business reports, people in the supply chain need to understand the data what the entry looks like, they need to know how we're doing across the markets. So all those indicators that put people together. Okay, okay. And so how do you work with a client in this respect? How do you and AWS sort of help the client, look at what the core business challenges are and then say, okay, this is how we're going to attack this problem? No, that's a good question. I think the thing is understanding what does the business need, and how is the technology going to support what the business needs? Right, that's first and foremost, right. And then getting in line and understanding that really what drives our roadmap to say here's what we're going to do, here's the order the order that we're going to do it in, and here's the value that we expect to get out of following these steps one by one. And I think one thing we learned is you have to be directionally correct. You may not, you may not be exact, but as long as we're making progress in the right direction you course correct as you need to, right, based upon as a business learns new things and as the market changes or whatnot. And that's really how we accomplish this. And is it a co-creative process or how closely are you working with Accenture and AWS? Oh, very closely with Accenture and AWS, it's very co-creative. I mean we are really working hand-in-hand. As Mike alluded, you start certain ways in journey and and you realize, gee, this may work but I have to change a little bit here. And there's several things, several times we had to change things direction how to get there and how to approach it, and to deliver value. Well, let's talk and let's get into the nitty gritty with the architecture and components. So what did this entail? Coming to this clean room, this one source of truth. Yeah, internal architecture is based on AWS platform or Accenture's AIP, Accenture Insights Platform which runs on AWS. And we have a, what we did from right from the beginning we said we're going to have a data link. We're going to have a Hadoop environment where we're going to put all our data in there. And for analytics, we said we're going to use Red Shift. On top of that, for reporting we use Tableau, and we have a home-grown tool called Compass for reporting also that we use. So that's how we initially started. Initially we were feeding data directly into it, because we needed to scan the system relatively quickly. The advantage to us, we didn't have different infrastructure, that was all set up at AWS. We just need to make sure we load our data and make sure we make the reports available. Were you going to add something to that? Yeah, the concept around, because of the merger is expediting this clean room which allows you to stand up in analytics as a service model to start bringing your data to start building our your reporting analytics quickly, right, which is really speed to market to understanding their position as an integrated company was so important. So, building the Accenture insides platform on the AWS platform was a huge success in order to allow them to start going down that path. Yeah I want to hear about some of the innovative stuff you're doing around data analytics, and really let's bring it back down to earth, too, and say actually, so this is what we could learn and see in terms of what was selling, what was not selling. What were you finding out? So at this point we have about 6000 users on the platform, approximately. Initially we had some challenges. I'll be very frank up front that, you know, everything does not go smooth. That's where we say, okay, what do I do differently? We started with dense storage loads, and we soon found it's not meeting our needs. Then we enhanced to go to dense cluster, and that helped us about by 70%. It drove the speed but the queue length was still long. It's still not getting the performance we needed. Then we went to second generation of dense computers, and clusters, we got some more leverage. But really the breakthrough came when we said we need to really re-evaluate how we've been doing our workload management. Some of our queries were very short and report queries real quick. Others were loading data that took a while. And that's the challenge we had to overcome. With the workload management, we were able to create where we were able to bump queries, and send them to different direction and create that capacity. And that's what really had a breakthrough in terms of technology for us. 'Til that time, we were struggling, I'll be honest. But once we got that breakthrough, we were able to comfortably deliver what business needed from data perspective and from business perspective. Mike, would you like to add? Yeah, in addition to AWS using Red Shift, right, has really been a really important I guess decision and solution in place here because not only are we using it for loading massive amounts of data, but it's also being used for power users to generate very adhoc and large queries. To be able to do some, to support other analytic-type needs, right. And I think Red Shift has allowed us to scale quickly as we needed to, based upon certain times of year or certain market conditions or whatever. Red Shift has really allowed us to do that in order to support what the business demands have really grown exponentially since we've been putting this in place. And it all starts with, you know, architecting and delivering all around the data. And then how do you enable the capabilities not just data as a foundation but, you know, real-time analytics. And looking at what could be, you know, forecasting and predicting what's happening in the future using artificial intelligence, machine learning. And that's really where the platform is taking us next. I want to talk about that but I want to ask you quickly about the skills challenge because introducing a new technology, there's going to be maybe some resistance and maybe simply your workers aren't quite up to speed. So can you talk a little bit about the, what you experienced and then also how you overcame it. Yeah, I mean, we had several challenges. I mean I'll put in two big buckets. One is just change management. Anytime you're changing technology on this many users, their comfortable something they know, a known commodity. Here's something new, that's a challenge. And one should not ignore, we need to pay a lot of attention how to manage change. That's one. Second challenge was within the technical group itself. Because we were changing technology in them, also, right, and we had to overcome the skill sets. We were not the company who were using Open Source a lot. So we had to overcome that and say how do we train our folks, how do we get knowledge, and in that case Accenture was a great partner with us. They helped us tremendously and AWS Professional Services, they were able to help us and we had a couple of folks from here at Professional Services that really helped us with their technology to help drive that change. So you have to attack it from both sides, but we're doing pretty well at this point. We have found our own place where we can drive through this thing now. In terms of what you were talking about earlier, in terms of what is next with predictive analytics and machine learning. Can you talk a little bit about the most exciting things that are coming down the pipeline in terms of Southern Glazer. I think that's a great question. I think there's multiple ways to look at it. From a business point of view, right, is how do they gain further insights by looking at as much different data sets as possible? Right, whether it be internal data, external data, how do we combine that to really understand the customers better, right, and looking at how they approach things from a future point of view with being able to predict what's going to happen in the marketplace. So I think it's about, you know, looking at all the different possible data sets out there and combining that to really understand what they can do from a possible point of view. Can you give us some examples in terms of combining data sets, so you're looking at, I mean...drinking patterns? Or what do we have here? Yeah you have terpie data, right? Yeah. TD links and those kind of, you pull that data in, then you have our own data. Then we have data from suppliers, right, so that's where we combine, say okay, what is this telling me? What story is this particular data telling me? I don't think we are there all the way. We have started on the journey. Right now we are at what I call the, this one source of truth. And we still have some more subjects that is loading to it, but that's the vision that how do we pull in all those, that information and create predictive analysis down the road, and be able to see what that means and how would we drive it. And so you're really in the infancy of this? Yes, I mean it's a journey, right. Some may say that you're not even in the middle somewhere, somebody say they're way ahead of us. It's all depending where you want to put us on that chart. But we at least have taken first steps, and we have one place where the data is available to us now, we're just going to keep adding to it. And now it's a matter of how we start to use it. In terms of, uh, lessons that you've learned along the way and you've been very candid in talking about some of the challenges that you've had to overcome. But what would you say are some of the biggest takeaways that you have from this process? Yeah, biggest takeaway for me would be I already mentioned change management. Don't ignore that, pay attention to that because that's what really drives it. Second one I'll say is probably have a broader vision, but when you execute make sure you look at the smaller things that you can measure, that you can deliver against because you'd have to take some steps to adjust to that. So those are the two things. And third, have the right partners with you. Because you can't go alone on this, you need to make sure you understand who you're going to work with, and create a relationship with them, and say hey, it's okay to have tough conversations. We have plenty of challenging conversations when we're having issues, but it's as a team how you overcome those and deliver value. High praise for you, Michael, and Accenture here. But what would you say in terms of, in terms of being a partner with Southern Glazer and having helped and observed this company. What would you say are some of the biggest learnings from your perspective? Yeah, oddly enough, the technology's the easier part of all this, right. I think that's fair to say without a doubt. But really, I think, really focusing on making the business successful. Right, if everything you do is tied around making the business successful, then the rest will just kind of, you know, go along the way, right, 'cause that's really the guiding principles, right. And then you solve it with technology, right. And that's really I think what we've learned most and foremost is, bringing the business along, right, educating them and understanding what they really need and focusing on listening and trying to answer those specific questions, right. I think, that's really the biggest, I think, factor I think I've, you know, we've learned, I think, over the past journey, yeah. And finally, so we're here at AWS Reinvent, 60,000 people descending here on Sin City. What most excites you about, why do you come, first of all, and what most excites you about the many announcements and innovations that we're seeing here this week? Yeah, so I'll be honest, this is the first time I've come to this conference. But it's been really exciting. What excites me about these things is the new innovation. What, you know, you learn new things. You say, hey, how can I go back and apply this and do something different and add more value back? That's what excites me. No, I think you're absolutely right. AWS is obviously a massive disruptor across any industry, and their commitment to new technology and new innovation and the practicality of how we can start using some of that quickly, I think is really exciting, right, because we've been working on this journey for a while and now there's some things that they've announced today I think that we can go back and apply pretty quickly, right, to really even further accelerate Southern Glazer's, you know, pivot to being you know a fully digital company. Yep. So a fully digital company, this is my last question, sorry. Your advice for a company that is like yours, about to embark on this huge transformation. As you said, don't ignore the change management, the technology can sometimes be the easy part. But do you have any other words of wisdom for a company that's in your shoes. Only words of wisdom I'll have is just I've already mentioned three things they probably need to focus on. Just take the first step. Right, that's the hardest part. Some companies just never take the first step. Take that first step, and you have to, this is where the industry is going, and data is going to be very important so you have to take the first step, say how do I get better handling the data. Excellent. Great. Well, Michael, Akhtar, thank you so much for coming on theCUBE. This has been a real pleasure. Thank you. >> Thank you for having us. Next time bring some alcohol. Absolutely. (laughs) It's Vegas. Yeah, thank you. 'Preciate. Great. I'm Rebecca Knight. We will have more of theCUBE's live coverage of the AWS Executive Summit coming up in just a few moments. Stay with us. (techno music)