 Hey, welcome back to theCUBE. It's live coverage of Snowflake Summit 23, live in Las Vegas, a Seizure's Forum, Lisa Martin and Dave Vellante. This is the second full day of CUBE coverage of this event. We've been talking a lot about all the announcements. We've been talking a lot about industry trends. We're going to be talking about the telecom industry day. We got the chance to be at Mobile World Congress a few months ago, immersed in telecom. It's a very rapidly changing industry that we all depend on. Yeah, it was our first physical event. We had SuperCloud in January, then we went to Barcelona. It was a great event. 100,000 plus people. Seems like a long time ago. It does, I know. Lots of change in the telecom industry. One of our alumni is back, who was with us at Mobile World Congress. Phil Kiffin is here in the global head of the telecom industry for Snowflake. And Colol Dutta, group lead for data automation at Spark New Zealand. Gentlemen, welcome to the program. Thank you. Good to be here. Thank you. Give us, Phil and Colol, both of your perspectives. When you look at the telecom industry as a whole, what are some of the data trends in particular that you're seeing that organizations are facing? I think many service providers are really looking at what data they have and how to use it. As simple as that may sound, that's where most of our service providers are at. But there's also some really innovative pockets of work going on in all different GEOs. And I think Spark is obviously one that's leading the charge here with some very innovative stuff that's going on there. We're seeing a lot of customer experience, a lot of marketing, and then certainly as well now, we're starting to see some network. When we look at what use cases and what our service providers are actually looking for. So I think it's different depending on which GEO you go to, but there's just a whole lot going on some early and then some innovators such as Spark as well. Yeah, because you got kind of a nuke telco, old telco. You're a nuke telco, I'm inferring, right? And leaning into the cloud, leaning into modern software platforms, but describe a little bit about the company. Yes, so we are Spark New Zealand. We are the largest telecom provider in New Zealand. We provide mobile broadband managed data, but we also a digital company. We provide cloud services, digital transformation, data analytics. And you know, if New Zealand, if you describe New Zealand, New Zealand is between Australia and Antarctica. So we are sort of compete for talent as well as resources. And that drives innovation, that constraints drive innovation, and we had to change. And we, like three years back, there was a conversation with the leadership and the board and say, what do you do with data? Can we make data as a source of competitive advantage? And that's where our journey started. And we essentially looked at data and the use cases. We started in marketing. We picked the one or two use cases and we then developed this whole lot of capability to make value out of data. Okay, started marketing to drive sales, right? Was that kind of, or was it to drive brand? Yeah, good question. So every telco starts somewhere. So we started with marketing, some start with network, some start with product. But it all converges into one, which is improve the customer experience because if you are happy customers, that drives more sales in a simple way. So we started with marketing, but we essentially took the problem in terms of we are sending too many messages to the customers. Can we be send the right message to the right customer at the right time? And for that, we had to get the data together. And we got the data together by unified data platform. That's what we call our snowflake instance. We made snowflake the heart of our data. And then we put AI and ML capabilities on that so as to find the right customer at the right time. That drove the conversions by 17%. On the same time, the marketing cost reduced by 16%. That was a huge success. And that laid the foundation for what we are doing now, what we call as data-driven everywhere, which is take the data-driven operating model to all parts of the business. We are doing one in network. Where we are essentially doing network planning with data so that we have the right network for the right customer and the experience is optimized for them. And that's what they expect, right? We expect to be as consumers, we expect to be connected wherever we are. Doesn't matter. New Zealand, Antarctica, Las Vegas. And that customer experience is critical because customers have twice, they'll churn. So obviously you made some huge business impacts with marketing. Driving retention, driving conversions, you said. I imagine sales is like awesome marketing. Thank you. That's also a challenge with our organizations is sales and marketing and connection, disconnection, alignment is key there. I imagine that was one of the benefits that came out of what you've just started doing even with the marketing use case. Yes, and I think the marketing was the start. What we looked at, that started the journey to look at operations and customer experience benefits. How do you make the processes frictionless by finding the opportunity to automate and make it easy for our customers? And while we do that, we also had to change our operating model in terms of how you enable that data to show up for our customers. And we essentially partnered with Snowflake to bring in the data capability across B2B, SME, network, and now we are taking that to finance. To finance. Phil, when we were at MWC, I talked about the disaggregation to the telco stack, how that's taking a long time, obviously. I started by saying old telco, new telco, or even long-term telco, but innovative mindset, growth mindset. Since we've talked, what are you seeing? Has it moved at all? Yes, actually it has, strangely enough. It's only been a short period of time. But what we have seen is we've started to see a lot of consolidation between the chief data office and the CIO with the network teams. And that's big. I mean, so some of our providers have started to look at bringing together product and technology. Others have been looking to bring CDO closer to the chief data office, closer to the network team. There is a lot of change going on right now. And it's a big shift, for sure. So it'll take them a little bit of time to get through that, but that's certainly what we're trying to help them with. We're trying to bring a platform to market and help our service providers go into the network teams and help them become data folks, as opposed to just expecting the chief data office to do it. And then when they're both speaking the same language, they can collaborate together and make things happen. Do you, Kalal, are you envisioning developing applications on Snowflake? So obviously using Snowflake in the cloud. Are you using the cloud in other ways? Are you putting BSS systems, OSS systems? Maybe you could give us a census to paint a picture, if you would. So when we looked at data, we were building data in a sort of what we call a service model. Ask me what you want, and I'll build it for you. And we realized that that's not sustainable. We need to build it in like a product. So we essentially created a vision, created a team across it, created measurement KPIs so that we change from being a cost center to being a growth center of the business. And that essentially enabled us to create products. And one of our most successful product is called Brain. Now what does Brain stand for? It was a product which was named by the squad itself. It stands for Build Robust AI for Next Best Action. And we did that essentially to manage the multiple models we have to find the right customer at the right time. And the Brain consists of a decisioning engine. It consists of a data layer, but also a measurement layer to find the uplift we can do with our use cases. And that has been a really big story for us. Now the company has sort of had that as a core platform to enable that to go across the company and realize the same vision across multiple areas. Look at your website and see that Spark is the first large company in New Zealand to go all in with Agile. Talk about that and how is Snowflake a facilitator of that Agile operational model? We were one of the first companies to do whole Agile in the world. And with that operating model change, it meant that our teams get closer to customers and we broke the boundaries of business units and of organizational friction which creates in the hierarchical model. And that enabled us to create cross-functional teams which brought the capability across. For example, the data teams, the ID team, the network teams, the business teams to build capability together. And they were enabled by the unified data layer which Snowflake built. And we used the unified data layer then to have one view of customers, one view of the product, which then we used to create apps for people to use and experience across our network. That's a huge cultural change. Absolutely. How did you do that and how was Snowflake a facilitator? I imagine when you talk about service providers, that's something that you have to facilitate. Yeah, yeah, it's definitely different. I mean, service providers, back let's say circa seven years ago, saw applications and the opportunity to develop applications and bring those applications to the market and grow their place in the value chain. It wasn't in their DNA. So not a lot of them took advantage of that and apps came and went. So when we look at data now, it's the next frontier. And we are seeing many service providers take it seriously, but I think certainly what Spark's done is incredibly innovative and they've been able to operationalize around something that many others haven't been able to. And I think that will certainly be one of their sustainable competitive advantages as they move forward. When did you start building brain? It has been a three year journey. So it, because we had to not only change our model, our data was all across the enterprise. We had a data warehouse, we had a data lake, we had an operational data store, we had a feature store, you name it, we had got it. But it was all in disparate systems. So we had to get that all together in Snowflake over time. We are nearly there, not fully there, in six months we will be completely on cloud or our code stack. And our plan is to take it to subsidiaries. And I remember the Frank conversation is how being an app and a product enables us to reuse what we have got and we will take it into our subsidiaries so that they can't, don't have to go to another three years of pain to get there. That's the leverage is much faster. Those disparate systems were all on-prem or was it a combination of on-prem and on-prem? All were on-prem. So we had to move them all into cloud at the same time, curate them, aggregate them, and make it usable. AWS or Azure? Azure. Like I said, that's massive. Talk about like the buy-in from the C-suite level that was needed to make that happen because that obviously doesn't happen overnight but it sounds like you made it happen pretty quickly. Fantastic question. I think if we see, there are two major things which made this successful. One was the leadership board and the executive buy-in on this. They were fully on it from day one and they supported us. And it is a long-term vision because we do look to give value in a short term but it takes three, four years to go through the whole transformation and they were across us. And that helped us to create a sustainable strategy but we also had a light to that. Another part which was very important for this success was what we call as start small but start deep. Start small in minimal viable data to start but start deep is do one or two use case really well and to ensure the value and go to next one rather than spread yourself in. And these two were probably the key reasons we are here talking about brain and the next evolution of that. That's huge because you guys are in the minority in terms of the digital transformation projects that are successful but you mentioned two of the things that we were talking about earlier that are critical for that. The C-suite buy-in and culture for sure can't have a successful transformation journey without those two components. It's fascinating what they've been able to do. What's even more fascinating to me is how they're changing the way that they build their models where they extract their data from and so building applications is one level of complexity. You can go up in complexity certainly as you start building custom capabilities or user defined functions. What they've done is they've created a brand new model that looks at these non-traditional data sources and starts to pull from those data sources interesting information about their subscribers that then they can go and increase the accuracy of their prediction models in serving customers ads. So you've got so much innovation going on in here all up and down the stack and it is, it's been fascinating to watch them go and they're doing some great stuff so far today. Eight months from now you guys both be at MWC? Absolutely. Sure. You will? Yeah, you're going to go? All right, we've got the same spot in between halls four and five. Awesome. All right, the cube will be there. So we'll see you there. I'll stand up to have you back on. Awesome guys, we're looking forward to hearing more. I'm sure there will be tremendous amount of changes in the telecom industry in just that short period of time. But we thank you both for sharing the spark story, the innovation, congratulations on what you've done so far. This is an awesome story guys, thank you. That's Danny. Thanks guys, have a good show. All right, thank you. For our guests and for Dave Vellante, I'm Lisa Martin. You're watching the cube, up next Zoom Info. Going to be talking with Capital One on how they're maximizing the benefits of B2B data for future successes. You can find all of our content on the cube.net, editorial analysis on siliconangle.com. You're watching the cube, the leader in live tech coverage.