Transcript
Thank you for joining us so far on season two, we're nearly at the end. With me in the studio today, Ruben from Optimal, tell us what you're doing at the moment. Optimal is a user experience research platform, right? It's been around for 16 years. It's like the OG of UX testing, right? And it's been helping the biggest brands globally transform their experiences or build new digital products like Netflix, HSBC, right? Workday, Nike, they've all used Optimal to test concepts of new experiences with their users and get data back to make informed decisions. At the end of the day, AI is a wrapper for UX outcomes. Yep. So yes, UX is still important, but how we do that craft and how we, I guess, solve problems is going through a bit of a shift, okay? Because I would say the top three, the top two users of AI at the moment, the number one is data science and ML engineers, right? And the second one is engineering and DevOps, right? And so they're using a lot of compute, right? Specifically on AWS or hybrid cloud. Yep. And the third one, which is creeping up very fast is design and marketing. Okay. So automated image creation, video content creation, that sort of space? Yeah. So they're using AI tools because it's a bit more accessible, right? So there's also this shift between more people within the design profession and marketing profession are starting to do research, are starting to test their concepts because technology is more accessible. I'm going to keep that train of thought in terms of, okay, I can really start now. I can dive in really, really fast and I can re-engineer front ends, whatever it may be. You might go back to a cloud hat. You might keep your UX hat on for this one. But I often tell customers that are looking at, we've all seen AWS's 7Rs and there's so many treatment patterns. And what are we going to do? With how fast I can redevelop at the moment and take advantage of native services in cloud, what's your sort of advice and gut feel where people are sometimes, organizations are getting stuck and saying, even if I've only got 300 apps, what treatment am I going to put against them? How would you sort of advise them on saying, hey, these are the low hanging fruit that you can probably automate code to give you a front end on. And this is where you should start. What's the treatments can take a long time. It can often dissuade people from actually making a decision. Yeah, that's a good question. I think ultimately the first thing you have to do is to get context, right? And I would essentially benchmark your current applications first, right? So take your current applications, survey your customers, like a tool like Optimal, basically you can take them on a screenshot. So, you know, send the link out to your, on your current application and get feedback from your customers and understand all the pain points and which ones have, I guess, high pain point, low effort, more return and focus on that first. I think it's quite easy these days to go because you can just write a prompt and create a new experience that, hey, we're going to take all our applications and just, you know. I'm just going to automatically rewrite all of them. All of them, yeah. We're going to rewrite all of them or we're going to present new ideas for all of them. But I guess you still, UX foundations are still important, right? It still requires an individual or an enterprise to say, okay, where are we today, right? Take stock. What are our goals from a user perspective? What are our goals from a business perspective, right? And which applications should we focus on first? Are you seeing that different in sort of the three areas? If I said, say government, regulated and enterprise? What's going to be interesting for regulated enterprises is that there's a lot of individuals using like AI tools and so forth, right? To think about how they can redesign experiences. But not a lot of these applications out there. They may not be relevant for enterprise, for regulated enterprises, right? So they have to be careful with what tools they use. So yeah, I think looking at the tools you use that support regulated enterprises, is the security architecture within that tool robust enough? Does it comply with certain regulations? And I think with that rise of being able to analyze the applications really fast and then being able to modernize the right ones, I always bring it back to the ROI. What's my actual return on investment for taking any application through a treatment pattern? Because simply moving it into cloud or moving it into a different area, maybe it needs to be adjacent to Bedrock and the new UX services that you're running rather than having to re-architect and re-platform the entire thing. I can just redo the web front end, or I can just redo the database connection string, something like that at a minimal level. I think that's where they need to start. Don't try and boil the ocean. Just pick some subsets and then go against it. And you can do it a lot quicker than what you think you could previously. Yeah, and also one big thing that's happening at the moment is customer expectations, right? Your customers are expecting a lot more from you because right now they're on chat GPT. The interfaces may change. It might be more conversational, right? So if you're starting with how my customer expectations are changing, how am I designing for that? And then underneath the hood, what technology is going to support that customer experience? And more often than not, it's actually cloud infrastructure and platforms like AWS, Optimal sits on that. It's only going to make us move more faster. Keep up with demand, keep up with expectations, because we can go in there, prototype new things, test, build, deploy very quickly. And I think that's a critical piece because if you're stuck in a, let's say it's a term contract, or you're stuck with a seven year lease on a piece of equipment, and then you're turning around saying, or I really needed to use this feature set in the cloud, and I can't do it, or because I'm stuck over here for another five years, or I can't pipe that much data back and forth. Like you're really limiting where your organization can grow from a customer interaction perspective. So having that flexibility to be able to adopt those new services, just because they're there, that's great. And you can test them, but can you mass now roll this out at scale? So being flexible enough to do it is probably the next piece. We need to fix that. We need to improve this. Can you move fast? Yeah. Can you actually do it now? Can you actually do it? How fast can you move? What's your velocity like to cater for all that customer research? Because they're not just using Optimal, they're using Notebook LM, right? They're using ChatGPT, Perplexity. All these tools are basically research tools, right? And they're getting insight on how they should improve their customer experience. And so stakeholders, they're going to be bombarded with new things to do, right? Yeah. Let me ask you maybe a contentious question here. Because again, is that a complete right field? We speak a lot about the customer experience at a UX perspective. And again, everything's on the App Store. 90% of the applications we talk about in an enterprise, especially regulated enterprise, service internal. Do you think organizations spend enough time to say, hey, we need to optimize BPO and we need to optimize the experience for our staff? Not just our end customers, but our staff internally. At the end of the day, employees are also humans. Yeah, I agree. I'm not pointing any fingers, Nutanix, here at our internal software. Yeah. Employees, they still use ChatGPT. They use Grab in Singapore to get to places. Their experiences, their expectations are still the same, right? Now, what's fascinating is that, yes, some enterprises, forward-thinking ones, are improving employee experience by way of improving the technology that they deploy, right? So one of our biggest customers at Optimal is a major bank in the US. They use Optimal purely for benchmarking and re-evaluating the experience of their internal applications. They know they've got thousands of employees, right? If they are improving the user experience, productivity goes up, right? And it only needs to go up a single-digit percent when you're talking thousands of employees globally. Single-digit productivity percentage increase, top-line revenue for the customer is going to be huge. Having the same mindset that you are doing for a customer and customer-facing application where I need to be able to use the new AI and cloud services to modernize this workload really fast, keep it up-to-date, keep it modern, keep it fresh, apply the same principles to your own workloads that service the internal workforce because they need to be just as happy. Yeah, definitely. I think also just the way that technology is moving and how developers are coding applications where they're being supported by co-pilot apps, it's only going to developers and designers that can have more time on their hands to focus on employee applications, right? Where, yeah, you're right. Sometimes it's more prioritized on the customer experience, but they are getting more time back, right? And so they might say, hey, look, let's carve out 30% and let's revamp all our internal tools. Yeah. Yeah, just on that, Michael, what I've noticed is that 70% to 72% of design and marketing are using AI tools at the moment, right? So there's a huge adoption of AI tools. Yeah. I've often been thinking about regulated enterprises, right? And a lot of those regulated enterprises, their compute is on-prem. Yeah, 95%, I'd say, is still running on-prem. Yeah, which is crazy, right? Yeah, and so you've got this workforce that is now starting to be more compute intensive, especially design and marketing, because they're going to be defining new experiences. But if they're on-prem, how do they adopt cloud? You're flipping it, we're swapping seats at the moment. Okay, yeah, I think the first part is where I sort of guide enterprises to go, especially regulated enterprises, is you don't need to boil the ocean of every single workload that you're running today to try and assess the right fit for the perfect service in the perfect cloud. You're still going to be here 10 years from now. It's funny going back to enterprise customers that I've worked with for 10 or 15 years, they're still running the same workloads again and again. It doesn't really change. So I think for us, and this is where Nutanix works really well in terms of getting that journey right. So we always say, get hybrid cloud done right, so that you can take advantage and adopt the native services. So for us, we start really easy. We build the landing zoning to the cloud, and then we go and stretch. Okay, so we can keep all of the IP addresses, the MAC addresses, everything stays the same. We don't need to transform huge datasets. We just move it up. So for a few of the customers we've been doing, it's been literally racks at a time moving into AWS over a weekend, not individual VMs or individual workloads being modernized to take advantage of what you guys are doing on the native side. So I think from that point, Nutanix comes in, we say, don't boil the ocean. Let's start small. Let's start moving the workloads up. So all the security policies that you've spent a decade building on prem, we can just stretch those up into the cloud. So we're not having to try and re-architect everything in the cloud to conform to the security policies on prem, because they've been there for a long time and matured. Yeah. So you're basically optimizing the current experience. Yes, yes. Nutanix optimal. Yeah, I like where that went. Yeah. Now that's good. Yeah. Because I think at the moment, it's only going to get faster, right? This adoption of compute and tools is only going to get faster. And even for optimal, we're investing heavily in AI. Yeah. We're hiring AI engineers. We're building more capability around AI at the moment, because we know that our customers want to do things faster and have more time back in their day. And so we have to think about, okay, in terms of our AWS, how are we going to scale that to meet the demand? You know, I was thinking about it the other day, like an analogy to give someone, because we're going to keep everything on premises and we can build our own AI service. And I was sort of thinking about it in terms of a mortgage on your house. So I've got 50% of my house, I'm going to put on a fixed mortgage and the other 50%, I'm going to have a variable because I don't know what's going to go on. Maybe it's going to go down. So I'm sort of hedging both sides. So if I am going to spike, and I am going to need a whole heap of cloud infrastructure or GPUs or AI, whatever it may be, I can now at least move half of my fleet up in and take advantage of it. I don't need to go and hire a hundred data scientists and AI engineers and everything else to go and build that on-prem. So that was sort of the closest I could figure as to, you know, how Nutanix looks at it. We can help you hedge your bets so you don't have to have a huge commitment that's going to stop you from being able to do it within five years. But yeah, I think you're right. Like you have to find a way to support where you're going and especially in today's world. And you need to be on the, have a strategy to enable that, right? Because if you're locked into a certain way of working and all of a sudden the world changes beneath you, like even your employees, the tools that they use, they have different expectations. They're not going to stay with you. Yeah. And then they're probably going to leave. They're going to go pretty, pretty quick. Yeah. Like I've seen people that I've worked with in engineering move companies because they want to go use the coolest tools, the coolest tech. I think is my bit of advice with it and how Nutanix helps to say, yeah, edge today, core tomorrow, next week it's in cloud. And then in six months, if that strategy pivots, you can just go reverse it. Yeah. I think it's like, do you have a ramp? Yeah. Where is the ramp? Where's the ramp? If you have no ramp, then someone's going to go past you. Someone else is building the ramp. This is sort of the big piece of advice. If you're not doing it, guarantee someone else is doing it. Yeah, definitely. Ruben, thank you for joining me today, mate. You are actually the last guest that we're having on season two for the podcast. So thank you very much. Yeah, I wanted to be the last guest. So thanks for inviting me. Good bookend. Yeah, good bookend. Thanks for joining us for this episode of the Nutanix cloud interlock podcast. We've heard from some fantastic speakers over this series of season two, and make sure you tune in and subscribe for the next episode with Maxim and myself, where we're going to tie it all up and show you exactly how to get hybrid cloud done right. This is the Nutanix cloud interlock podcast.
