 Welcome to this CUBE Conversation. I'm Lisa Martin. Joining me next is Brian Kirchner, the Vice President of Strategy at DataStacks. Brian, welcome to the program. Thank you, glad to be here. Excited to unpack this survey that DataStacks recently did. This is with 500 or so IT executives, technology practitioners, talking about data strategy. Talk to me first of all about the state of the data race is the name of the survey. Why did DataStacks do this? What was the impetus behind that? Yeah, great question. Thank you. So, you know, we are in a race. Our company, every organization is in a race to find ways to use data in new ways to move the business forward, satisfy your customers and so on. It's okay to have a strategy to be a leader. It's probably okay to have a strategy to be a fast follower. It might even be okay to say we state in touch with best practices and once they're proven, we adopt them. But what's not okay is one to lose track of where you need to be relative to how the market's moving. Most importantly, your competitors, but in general, customer expectations, your employee partner expectations are gonna be set by companies potentially in different industries. So you need to be at the right spot in your journey. So that's why we do a lot of benchmarking. But as important is as your particular company's context and history and situation and technical architecture kind of comes in contact with a strategy that looks great on paper, you have to understand is something slowing us down that we didn't expect because of our culture or unspoken incentives or, you know, what is our next best step for us? So in this dataset, we really look to identify the leaders who are having the most success and then work back from the patterns and practices we saw with them to how different types of companies at different stages of their journey can find their next best step to make the right progress. So the show that a lot of companies have a data strategy, the execution piece is a different story. Talk to me about how this survey defines a data leader. What are some of the key characteristics? Yes, there are quite a few. In fact, what we've done over the last year that we fed into the survey was, you know, in the course of my work and my colleagues work, we talked with lots of CIOs, hands-on technical practitioners, CTOs and so on. And we put all that conversation and qualitative insight together into about 70 measures. And so that was all in the survey. And once we got the data back, we did a cluster analysis, bringing some data science, the data strategy, if you will, and that surfaced these segments. And for example, how much revenue you were generating from data was not part of the definition. So then we mapped these segments and these practices against that. And we said, oh, the leaders, generating the most revenue from data. So that gave us some confidence in using these patterns and practices to bucketize folks. And you found that the data of those companies in the data leadership category were able to attribute more than 20% of their data, excuse me, 20% of their revenue to data and analytics. Talk to me about that 20% benchmark. Is that considered where a lot of organizations need to aim to be? Because there's still a lot of money on the table. Yeah, that's right, that's right. So in common industry parlance as a standard, materiality on the balance sheet is 10%. And we've seen a pretty significant number of companies hit that mark. What we saw, which was interesting in our data was that's kind of a comfortable benchmark to pick. It's an industry standard, data's material. Hey, congratulations. But you actually drill down further and you look at that 20% mark and you say, well, 10% is probably not aiming nearly high enough because a significant proportion of these leaders have already gotten to that 20% mark. And so it's in part, again, about that benchmarking where you are, where's your destination? Your destination probably isn't, we're on the board. Your destination probably isn't its material. Your destination is probably, it's big and it keeps getting bigger. And where are these data leaders with respect to deploying a hybrid data strategy? What is it about how they're organized and structurally what they're doing that is positioning them to actually really drive incremental revenue from data? Yes, yeah, what stands out about the leaders is, and we see this in our data, you can see this in any number of analyst firms and other data sources. Hybrid cloud strategy is the dominant strategy for large enterprises, right? It's about preserving your flexibility to operate in multiple clouds and on-prem. So that's pretty well understood. What we saw in this data was overwhelmingly almost 100% of the data leaders also say they're pursuing a hybrid data strategy. So they're already doing that kind of same level of thoughtfulness and planning about how can we get and deploy apps and compute everywhere to how can we store and deploy and redeploy data everywhere. And there's a real steep curve to the extent where the folks who are just starting out who may have a strategy but have taken very little action, none of them strongly agree that they have that type of hybrid data strategy. And so the pattern, qualitative pattern we see is companies go down this hybrid cloud compute strategy for good reasons and it pays off, starts to pay off. And then they realize, oh, we should be doing the same thing for data. And that's giving these leaders, a lot of agility, control, flexibility and opportunities. One of the things I found interesting in the report from a statistics perspective is that those data leaders that you talked about that are able to attribute more than 20% of their revenue to data and analytics, twice as many of those are too, they're too X likely to be using a robust open source data stack. Talk to me about that as it plays into the computing strategy and the ability to convert data into revenue. That's right. So they're almost 100% comparable to the hybrid data strategy. Almost 100% are also increasing their use of open source software. And I kind of think about this from two dimensions, right? The hybrid cloud and hybrid data strategy gives you agility, optionality, flexibility for your infrastructure, for your compute, for your storage and so on. Then it's about really making sure you're using the best of breed tools for the job of creating value with data. And if you look backwards, the track record of open source technologies, Apache Cassandra, Kafka, Spark at some of just like the applications and experiences that have validated the massive impacts data can have on a business, the track record of open source is strong. And you look at the cycle of innovation and you see Kafka having emerged and now Pulsar emerging as sort of a newer, more cloud-friendly version of Kafka and Flank kind of emerging as potentially a successor to Spark. That cycle of innovation arguably is accelerating. And so as you think about what's unique to us as a company, it's the data you have, right? No one has the customer interactions you have. Nobody has the business processes you have. So what you want to do is take those best of breed tools and have flexibility about the infrastructure services to support them and focus your people on doing great things with the data. So don't try to solve a problem that the open source ecosystem has already solved, right? If you're writing that code instead of focusing on what differentiates your business, that's a miss. So when we see the leaders leaning hard into open source, it's because they've got the clarity about we differentiate by using these best of breed tools on our data, not reinventing the wheel. Are these companies, you mentioned culture a minute ago, and that's always something that I find intriguing because it's very hard to change. We've been in the last 16, 18 months and a very fast pace of change as we know. But are you seeing these data leaders that are companies that are reorienting towards a data culture where data is part of everyone's job? Yeah, absolutely, absolutely. So it's interesting, a majority of all companies said that reacting to the COVID crisis did increase their pace of innovation. But again, it's almost universal among those leaders. And one of the patterns that stands out is indeed, when you say making it everyone's job, I'll put a finer point on it. It's saying accountability for creating value, generating revenue with data is the line of business's accountability. In conversations, I've literally had CEOs say, it's not my problem anymore. It's my problem to help them execute on the ideas, right? And that can even raise the bar because now they're coming up with bolder, bigger ideas. But it's not about IT being the custodians of the data trying to go to the business and say, hey, could you use some data? It's business general managers, VP's now accountable for, how have you used data to drive revenue? How can it change the way you sell or the way you service customers and so on? And that in part, what we heard from some folks was in organizations with progressive CIOs, chief data officers, they have been going to the business side of things and saying, hey, I think we've got ways to do business better. But there wasn't pressure on the business. They're like, our business is going fine. But once COVID hit, it was like, okay, we need to take out costs. We need to find new ways to grow. And there's sort of that drove an organic embrace of, ah, I see. I want to pick up the reins and, you know, work with my technology partners to make it happen. But now I see we should be driving it on the business side. And have you seen in the COVID era, data strategy become really a board level initiative? And to your point, one of the things that you found is, is it's not just the culture of data being core to everyone's job. It's the accountability level at the line of business level. But I imagine that that data strategy is indeed a board level initiative. That's right. So with the biggest, when you mentioned culture, the biggest of the segments is a group whose biggest challenge is cultural change, about almost a third of all organizations. And you see there, there's this big drop, you know, compared to the leaders of whether the data strategy is a board level discussion, right? And you see this big drop in other metrics where, you know, do you have a data strategy, mild agreement? Like, oh yeah, we talk about data. Everybody talks about data. But it's really about getting that top down. This is a true corporate priority, which kind of circles back to our initial conversation. You know, if the goal is 20% or more of your revenue from data, it better be a board level conversation, right? And, you know, if you have an effective board, you want the board to be helping to drive toward that. So it really closes the loop on, you know, again, calibrating what's our aspiration? What's at stake? And if we believe in the data, you know, we shouldn't be hesitating to elevate this to the board level and get their attention on it. Right, give me an example of a customer that's doing this, that's a data leader, that's doing this really well and one that pivoted to be able to use data and extract value and revenue from it during the last year and a half. Yeah, I mean, I would say it's a little bit less the pivot and more of an amazing success story. Because if you look backwards a few years ago, Home Depot made a significant board level, you know, top-down company-wide commitment to a very bold digital and data strategy. And so, you know, by 2019, for one example, you know, Forrester ranked them as the top retail app for customers. And all that work, which is already paying off, right? They're making big investments but they're getting big payoffs, when COVID hits, Home Depot was able to deploy curbside delivery a service they did not have, a feature they did not have in weeks at scale, which drove even more outsized returns during COVID. And so it's a little, you know, it's a less of a pivot but more about the value of making that commitment because, you know, they weren't planning on deploying curbside delivery to the app in weeks, but when COVID hit, they were able to because they already had the cultural change, the infrastructure, the metrics, the technologies in place. And so, you know, it's really a message about don't wait, right? If you are going to fast follow, if you are going to be waiting for proven best practices, you don't want to start off the blocks at zero when something disruptive happens. You want to have some success stories, some practice added under your belt. So, you know, even if you're fortunate enough not to have been pushed into radical action because of COVID, don't let that stop you from season to day and actually starting to move. Now, I think I'll never have the same opinion of Humpty Bill again. I will always go under looking for light bulbs and batteries and flashlights, thinking of them as a data company, but it's a company that, to your point, committed to it and pushed that accountability out into those lines of business. How does, what did the survey show in terms of those data leaders embracing open source, embracing a hybrid data strategy? How does that facilitate that driving that accountability into the lines of business so that that revenue that's sitting on the table from data can be unpacked? Yeah, it's almost, I think, you know, if I look at it from the technology side, imagine, you know, in the past, you're the custodian of data, you know, as a CIO and your job is to kind of make, you know, data is not lost, we comply with regulations, you know, for the kind of way we run the business yesterday and today doesn't break tomorrow. And so if I think about this shift to where the lines of business are now accountable for finding new ways to use data, what are they to come up with? Like, you know, if you think about like, you know, innovating in business, taking data under the wing, right? Your job now as a general manager is innovate, innovate your business model, deliver something we never delivered before, deliver something no one in our industry delivers. So on the tech side, you know, it should be exciting, but it also means you may be on the hook for delivering some capability that your company had never thought about. So that really gets back to this idea of like, do you have access to, you know, the best infrastructure services through hybrid cloud and data strategy? Are you set up to use best of free tools? Even if, you know, last year, we didn't have a scenario that uses best of free tools. Well, now that the businesses are thinking really hard on how we differentiate with data, they're probably going to come up with some big bold ideas. Again, which should be exciting, but you got to be ready to, you know, invest in change and something new as opposed to keeping the lights on. Right, I think that pace of innovation, I don't know, maybe it's permanently altered because the scenario was one that nobody ever expected to be in. As we saw so much transformation in the last year and a half and the pace of innovation change and the places that are like the Home Depot being able to radically change so quickly. And so we saw a lot of other businesses that could not do that. What are some of the market trends that you're seeing as we're now coming around the corner into the second half of 2021? Yeah, I mean, the acceleration's a great point because when you're using data to deliver value to customers or create value for your business, things actually build on each other, right? So, you know, data doesn't get used up. It's one of the amazing things about digital data. It can be used and reused and recombined. So if you saw, for example, you know, leaders were well on the way before COVID, do you have real-time inventory? Well, sure, but then once COVID hit, do you have real-time inventory and can you make a recommendation for somebody that's out of stock became like, wow, we should get that done, you know, ASAP. So then as you see folks do some necessary things, you start to see, well, if we've got real-time inventory and we can make recommendations, why aren't we getting a 360-degree view of the customer from that data plus marketing data, right? And now the value gets unlocked whereas if you said, you know, two years ago, how can we justify creating a 360-degree view of the customer? Some organizations might have been like, well, we can't, you know, it's hard to do, we can't see the value, whereas once you're doing a couple of these use cases, it becomes obvious that they'd be better together, right? And so if you see, you know, the Home Depot, I think you're gonna see, you know, essentially every retailer that wants to stay competitive is gonna follow in that path. Do you think that those companies that become data leaders or are on the path to become data leaders that have the hybrid data strategy that are embracing OpenStack, is that mentality in your opinion gonna separate the winners and the losers going forward in the next year plus? Yeah, I mean, I think in a sense it has to because again, as I think, you know, there was a trend already in place for all of us as consumers, right? We love, for example, delightful recommendations, you know, companies and applications that know us and just make our lives better because they're smart, like Netflix and Spotify, right? The classic examples. But now you think about, for anything, so Cengage is an education, you know, platform company and they talk about being the Netflix of education. And, you know, retailers like Home Depot, like Target have gotten super smart about things like recommendations. And, you know, in the case of Home Depot, like connecting me with the data that explains how to do DIY projects and use the tools I'm trying to buy. So, you know, the bar just keeps getting raised to the point where, you know, you look at, you know, you look at the e-commerce site of the past, we just sort of a dumb e-commerce site where it's, I can pick things, put them in a cart and buy, you know, that's not acceptable by any stretch of the imagination today, right? Are there user reviews? Are there, you know, recommendations? We expect all of this. And I think you'll see it, you know, obviously, retails heavily disrupted by COVID, pointing into the sphere, so to speak. But I mean, telehealth is another example where, you know, I think the writing is on the wall. If you can't do telehealth as a health system or a hospital, you know, very soon you're going to have a big problem. Yeah, the consumer demand is incredible for, I want whatever it is, if it's I'm shopping on Amazon or if it's Home Depot, I want them to know what to recommend to me next, based on what I just thought. We have the expectation that the Netflix is and the Spotify is to your point have set. And we also have that expectation in our business life. So when folks are buying and interacting with software, they want the same thing, right? It's not just limited to healthcare and retailers. That's right. And that's that, there's a virtuous cycle, right? If you think about companies, you know, making that cultural change, leaning into using data to make things better, it's not just for your customers, it's for your employees, it's for your partners, it's for your business processes, right? And how are you going to be able to hire people who are super excited about making things better for customers? If you're also not, you know, internally making things better for your employees, right? They're just a real disconnect in terms of, you know, culture and personnel there. That's a great point. Those are, in my opinion, inextricably linked. Brian, it's been great to have you on the program. Thank you for sharing with us the state of the data race, very interesting sort of that you guys have done. Folks can get their hands on that. A lot of opportunity and a lot of money on the table for organizations in any industry. Thanks so much for joining me today, Brian. Thank you. For Brian Kirschner, I'm Lisa Martin. 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