 Live from Las Vegas, it's theCUBE. Covering Splunk.conf 19, brought to you by Splunk. Welcome back to theCUBE everyone. I'm John Furrier with SiliconANGLE on theCUBE here in Las Vegas for Splunk.conf 19. It's their 10 years of their customer main event, all their top customers and partners are here. And of course theCUBE's been covering.conf for seven years. Got a great guest from Accenture, Mike Heinlein, Ecosystem Inventures Global Analytics, Plays and Offerings Lead, Accenture. Now, first of all, welcome to theCUBE. Thank you, John. Accenture always has long titles. So let's parse through that. That is a very long title. You're a lead. That's a mouthful. Offerings. Yes. This means to these titles at Accenture. Yeah, so I'm part of the Ecosystem Inventures Group which helps to incubate our various different channel partners and drive services with those partners. And then within the Splunk partnership, I'm focused on driving analytics offerings with various different practices that are already considering analytics and taking those to market. So you guys have a relationship with Splunk is evolving pretty quickly. It is. What's the future look like? What's the current path? As you may be aware, we recently renewed our partnership with Splunk back in February. After two and a half years, we had achieved most of our goals. And where we were starting to see is that our initial objective was to help our clients to get more cost takeout and risk associated with their IT and security operations. We also learned a few things along the way which is the Splunk analytics engine can also be used outside of IT and security. And we can start to take it into industry verticals. And so one of the exciting things that we're doing is we brought our digital practice into the tent with us. We renewed in February. We have a couple of years we're looking into the future. And we're going to not only double down in IT and security, but we're also going to start to build business analytics and IOT type solutions on top of, within the vertical industries that we're focused on. What are those industries? Can you share them? Yeah, yeah. So it would be things like energy utilities where power line analytics to reduce the amount of vegetation that might take out power lines, cause fires, cause outages, patient flow which would be how to help accelerate getting patients through the ER and also increase throughput for hospitals. Within supply chain, we're doing a number of different things. We have four different offerings that focus on technology, telecom, retail, consumer goods and manufacturing. So like industrial type clients. So pretty much standard vertical industries that you normally see in the business. So I want to get your thoughts on this because one of the observations I want to share with you and I want to get your reaction is, is that with cloud and with data, it's interesting the data is a really key part of all this. You mentioned IT and security, obviously that's pretty straightforward and you can see that. But it's interesting when you start adding machine learning and AI into things, the domain expertise of these verticals become the pacing item, the key IP if you will, with the scale of what's going on at the platform level. Are you seeing that this is a fertile ground for opportunities, how you guys see it? Can you share your reaction? Absolutely, I think where Accenture is strong is in our industry acumen, not just in IT and security, but within different industry verticals. And then you take our digital practice, which is where our data sciences live, where they're developing advanced analytics models and essentially working with a lot of the open source modeling tools like Python that integrates very well with Splunk. It gives us the opportunity to take that data that can be bundled up, it could be data at rest, maybe three years of sales data and we create a forecast with it and do that on top of Splunk. Or it may be something where within a supply chain or a flow within a hospital, we're able to use machine learning to start to move some of the compute and thought from human beings to machines. What are some of the innovative services you guys have built on top of Splunk because they're in data enabling platforms. So again, opportunities, what are you guys doing on the innovation side? So both in the retail and in the technology space, we've created a couple of replenishment engines. When you think of supply chain, I need to know what my forecast is, what do I plan to sell? How many items do I need to have in inventory in the warehouse and in the store? And then how am I going to get those items? And then how many should I order the next day? So we're using Splunk to figure all of that out. What are some of the surprises and learnings you've gotten in dealing with Splunk because there's always seems to be a new revelation when people get data and they start playing with it and they get insight. Beyond that, there's usually some sort of business breakthroughs or kind of weird things happen when you start playing with the data. Any anecdotal surprises or learnings you've seen? Oh well, a tremendous number. In fact, what happens is when you start to open up the silos. So most of our clients are stuck with a lot of legacy technologies that they've acquired over the last two or three decades and Splunk enables to open that up to get insights that we couldn't before. So it could be, I can get a patient through a particular process twice as fast as what historically had been able to do or maybe for example, something that Doug Merritt mentioned yesterday which is where we're partnering very closely with Splunk for human trafficking. We've created an offering where Splunk had already gone out and created a data lake of a lot of data from educational entities, NGOs, government agencies. And we took that, built some machine learning on top of it and able to identify high-value targets or establishments that have a high risk of human trafficking which is already starting to get results in Florida. You mentioned healthcare multiple times. Is that one of your key verticals? It is one that's emerging, it's very exciting and it's kind of evidence of where we're working really well with Splunk. In a lot of cases, we've developed things and we take it to Splunk and we go to market together. In this particular case, Splunk created patient flow, took it to us and now we're working to identify about a dozen different hospitals where we're going to go meet with their CEOs and talk to them about what we can do to help them increase profit and patient satisfaction at the same time. What's some of those conversations like when you go and knock on these doors and say, hey, I got a new secret weapon to solve your problems because there's new things if people have these problems that couldn't have attacked before in the past, now they have potential capabilities. What are some of those conversations like? They're like, come on in, educate me, I want to buy right away, or dorsal in your face. I mean, how do you get people's attention? So we just had a really exciting meeting with a very large grocer in the Midwest and as we were explaining the different things that we could do with Splunk, she actually, the head of supply chain actually said to me, it almost seems like fairy dust to me. In other words, the hardest challenge that I have sometimes is being able to say, look, you're used to doing this in 24 months, maybe 36 months, I think I can do it free in lesson six. And that's just so hard for them to absorb. So a lot of cases it's transitioning to, well, let us figure out how we can prove that to you and doing some kind of a proof of concept or a pilot. You know, what's interesting is that when you see people get set up with a data platform, it's kind of an iterative stage. Let's set the foundation, let's make sure everything's flowing in, Splunk, if you will. And then you start, they're getting some discoveries here and there and then they get business value. And then it kind of goes to another level. I think this is where I think I see you guys doing well and others here in the ecosystem floor. And that is that it's a workflow optimization issue. They go, wait a minute, we have all this data. Well, let's go do this. And that's a little bit more of a holistic business process or some sort of poor challenge. Is that how? Yeah, so I would say you always have a business process, at least in the industry verticals. And you have a lot of data that's siloed and then you crack those silos open and then it's really basically intersection of what we would call planning and execution, which is, for example, maybe I have an oil rig and I have a ship that is taking materials and people back and forth. And but now I know that I have actual things headed to that port where if I send the ship now, I'm going to have to come back in the next 24 hours. If I hold that ship off for two or three hours, then I can get more materials and people on board and I don't have to come back for another 48 hours. So now I've just reduced greatly my operating cost. And I think that's interesting is that you think about what you just said and go back 15 years and say, okay, what's the database schema to make that happen? The data's over there. It's over there. I got to write a query and got latency. It never happens. That's exactly right. So we're kind of out of the business of trying to fit square pegs into relational round holes, which takes the better part of maybe 50% of a lot of projects to implement those solutions. And so with Splunk, you're basically dumping the data in and you're layering your schema on top of it, which enables you to accelerate delivery. And additionally, I don't have to cobble together and stitch together multiple technologies to do ingestion, analytics, storage and visualization so I can mobilize teams much more quickly than it would traditional solutions. Mike, I'd like to get your thoughts on Accenture's transformation because in looking at what you guys have done as a company, it's been interesting. You got a lot of successes, but the firm's been around for a while, right? So in perhaps different names, going back to the old school, back on the mini computers, you guys were rolling out projects. Some of them had long horizons, multi-year. Now the speed game has completely changed. Cloud's here, you got data. How has the Splunk and these modern technologies changed Accenture's engagement practices? Yeah, I think you're touching on what we would probably call agile delivery, right? Or continuous delivery, where our clients don't want to push off from shore and do a big bang project where they don't get to see the results for 12 to 24 months. That's a lot of risk for them. So what Splunk enables us to do really is to do delivery and deliver value in agile sprints in three, 12, 16 week sprints where we're iteratively giving them value. We also don't have to understand all of the data. If you're using relational databases, you pretty much have to understand everything before you push off from shore. With Splunk, I can know a minimal amount and start and deliver value. And then as I go, I'm learning more about my data. I can deliver more use cases and more value. It's interesting, you know, we'll go back to the old enterprise sales model. You know, you do a pilot or a POC, or a POC, then a pilot, then the pilot's the data and that's what months to, right? And then the decision makes it and then you got to start over. By the time that it'll happen, and you're talking about months, maybe years, technology changes. That's right. You guys are doing essentially agile sprints that are kind of like little mini POCs. That's correct. But they're not POCs, they're actually real work. That's right. That's the new, seems like the new sales model. Well, I would say it's something that, with a rapid prototyping capability like a Splunk, it gives us that flexibility to do. Depending on what we're doing, we may not have that flexibility. We may be limited by the technology. How would you describe the strength of the Accenture Splunk partnership? I would say very strong. So like I mentioned before, we started to an app three years ago. We just renewed that relationship in February and we've added more practices from within Accenture like our digital practice. So now we have strategy, digital, technology and security. We're focusing and doubling down in security in our IT markets, but also then starting to explore new industry verticals and business analytics and IoT. As I explained earlier, we're bringing things to Splunk and they're helping us sell and they're bringing things to us and we're helping them sell. And there's a lot of excitement. I mean, I think it's really a combination of the right people with the right industry knowledge at the right time with the right technology. Final question, even in the industry for a while, you've seen the waves, pretty big wave we're on now. A lot of confluence coming together, multiple different dimensions, cloud, data scale, everything, speed. What's exciting you these days? What's the big story that people should pay attention to right now in this space? I think it really dovetails into Doug's theme and I don't mean to really piggyback on that, but it's true and that is that so many of our clients still have a lot of technical debt from decades ago and we get to come in there and say, look, in a matter of weeks and months, we can help you make sense of this, we can help you capture revenue, you couldn't capture before, drive out costs that you couldn't drive out before and reduce risk that you couldn't reduce before. So, I mean, it's probably the best time of my entire career, frankly. Yeah, it's interesting, you know, Kubernetes and certainly containers helps make those legacy workloads somewhat compatible with the modern infrastructure. But when you have those technical debt conversations, are the customers kind of realizing like, I'm on the verge of tech bankruptcy, what do I do? Is it more advisory? Do you guys have to come in? Is it more counseling slash get develop? Yeah, yeah, a lot of times it's helping them to come in and assess what their situation is, help them build a roadmap into the future. Sometimes it's rationalizing some of that technical debt. Sometimes it's how can we augment what you already have? And then in the future, as that reaches end of life, we almost just turn it off, but you're up and running on this other platform that we've augmented into that ecosystem. So, tech flow positive. There you go. Yeah, cash flow positive, take from technical debt, from tech bank receipt. I'll use that. Yeah, Mike, thanks for coming on, appreciate it. Thanks for the insights. Thanks for having me. Great insights. We're getting all the data and the insights here. The workflow is rocking the cube, second day of three days. I'm John Furrier, more coverage after this short break.