>> Well, quick introductions for everybody kind of out there watching in the Data Summit. I'm Ali Tierney. I am the GVP. I run EMEA Sales for Snowflake, and I'm joined today with Michael Gillespie. Quick, just to introduce himself, what he does, and the DPE come structure as it goes. Go ahead, Micheal. >> Thanks, Ali. So as you said, I'm CDTO at Domino's Pizza Enterprises. So the company that I work for, we have the franchise rights and run Australia and New Zealand, France, Belgium, Netherlands, Germany, Japan, Luxembourg, and Denmark. And that's obviously Domino's Pizza for those markets. I look after four different verticals within the business. IT for the group, Strategy and Insights where our BI team resides and has a lot to do with Snowflake. Our Store Innovations Team, our Store Innovation Operations team which look at everything from robotics in store, how to use data better in store to be working at optimum level, and our digital team which is where I started in, actually, 13 years ago. And they're guiding our digital platform at a global level and how we localize it with the local marketing teams. >> Brilliant, I'm American and I grew up with Domino's Pizza, so help me understand, kind of, from a high structure. You've been there 13 years. My growing up experience was picking up a phone and pushing buttons and calling Domino's, and clearly a ton of modernization has come in the last 20 years, and you've been with the company for 13. What have you seen as you've grown into the DPE digital kind of space and you're driving that market? How are you guys using data? What have you seen happen over the last 13 years? >> Domino is itself, or at least DPE as well, has always been a data-driven business. What we've seen, though, as we've become more of a business that utilizes digital and technology to enhance, whether the customer experience or our store operations or our enterprise team. Is the availability of data to make decisions or to actually find insights. And if I look back, I've been lucky to go on a journey of 13 years with DPE. The power of analytics and data was apparent in a digital space. And it gave us a level of insight over a purchase that we never had before. So a great example of our first use of real data in a customer experience outside callbacks people are late, where we could give real-time feedback to a customer around their progression of their order through something called Pizza Tracker, which is shared across all and used across most Domino's in the world. And they're most common for most purchasing processes. Since then, we've gone from, I could count, very easily in between this call, how many orders would make in a day online, to now over 70% of our businesses online. We have a huge amount of data coming in from different, different areas of business. And now the challenge for myself and my team is how do we make this data readily available? To the local marketing teams, local operations teams. To really get better insights on the local market. So we've just gone from having a small pool of data to a tremendous quantum of data. >> So as you look to kind of localize your markets, right? I think you just mentioned seven or eight different markets that you're in. And I would assume then you have some data sharing that goes on within DPE, right? So Belgium wants something that's different than the Netherlands that was different than Japan, right? So how are you right now democratizing that data and giving it to your customers so that your end users can see how to use that, right? In local marketing in local, kind of, business uses. >> Correct. So, we have, we have nine markets now within DPE and all those markets, every market has unique needs and wants and challenges that they're trying to solve for. So our goal is to really try to simplify the access. And that's what we talk about democratizing data. We have a series of reports so we can build customized reports so that we don't have to do as many ad hoc requests. Then when giving those dashboards having the ability to customize and benchmark where you need to. And then when it comes down to a unique customer experience that's obviously going to be a localized marketing on them because different customers bought certain, certain volumes of pizza or sides and different market that's different. So we need to make the tools that each of them and or allow our marketing teams around the world to get access to the data that they can really help them make the most informed decisions to support their franchisees and stores. >> How much of your technology has moved in general to the cloud? And then secondarily to that question, as you've moved there, and I assume significant multi-clouds because you've got so many different regions and locations, how are using Snowflake to help move data into the cloud? >> I would say from a cloud perspective we're well advanced in being clouded for a majority of our platforms or at least moving in that direction. And we're being cloud friendly economic solution and some of that data solutions for quite a while. We still have some on-premise data, like most companies, and we're in the process of migrating. And we have to be aware that we operate within markets like Europe, where GDPR is there. And we have to, we have to be well across requirements from that ability that perspective. But regardless of GDPR or not with any form of customer data or employee data or any personal data we have, we know it's a privilege to hold. So anytime we are working with data we always want to make sure that we're storing it and accessing it in the most secure way. And then beyond that, we want to make sure that, as I talked about, we want to democratize data and make it more accessible. So, you know, I'm really looking forward to seeing as we build out and continue to build out our data strategy, how we continue to work with the likes of Snowflake to just bring faster and more insightful, you know, visibility into each particular market and at a global level as well. So that our global leaders can understand how the business is performing but also get micro where they need to. >> How, as you go through your cloud journey and then and with Snowflake specifically, how did you guys look to governance and how did you look to ensure your security around data? >> Yeah. So know for us, it's all about making sure we've got the right governance and controls and processes. So working with our security team, working with the right architects on data flow and processes, working with our legal team and representatives in each market and that's vital. You know, having policies and governance around any form of activity whether it be data or around changes on the website or changes even in any operational processes is important. So. >> Yeah >> And the greatest thing is if he can, you know, through, if you're making dashboards that are unquantifiable non-personal data, you know that's a lot easier to manage, as well. Because that's giving you a representation of groups not actually down to the particular customer. >> That makes perfect sense. How have you found migrating to Snowflake? Talk through that journey a little bit and I know you're relatively early in the journeys but talk at your experience has its been so far. >> You know, the BI team, my BI team and Strategy and Insights Team have definitely been huge fans of Snowflake and the support from the team there and and the partners we're using for integration. You know, one thing that I know that, that excites me from a strategic level, it's Snowflake's ability to be cloud agnostic and for us everything we build in the future we have chosen partners that we work with in the cloud space. We shouldn't be, we should always be having that ability to be flexible or we're always going to have some fragmented data sets and the ability to utilize a solution that can stretch out into those is very important. So you know, from a strategic level that's a great level of flexibility and from a micro level, and to look at how the team operate when they're coming with stories around greater efficiency, greater flexibility, reduced processing time, reduce, reduce time, reduction in costs and certain activities. That's a great story to be told. That's what I like about this story is that they were all wins. You know, I'm getting from the team that I can run more intensive workloads now. You know, that they can they can do more immediate action. You know, they are cutting down time, as I said, something down from hours to minutes down getting some early results and that's so important. >> So, tell me what kind of business insights you're delivering back to your stakeholders when you get through this process? The quick wins. >> Yeah, well I guess it's just us being able to get reports out faster. Get information out faster, Get access to any acts, build, build bespoke things quicker. It's all about Domino's as a business that's quite an entrepreneurial fast moving. So if you can find efficiencies that, like any business, that's, that's the point. But if we can find efficiencies within our team what it means is we've got a quantum of work the team can do or a service can do, or a bucket of costs can do. If we can reduce that quantum of whether it be cost or time and human effort, that means we can output more. One thing that we're also looking at is we talked about democratizing data earlier, but how can we empower, empower teams to get insights faster? Or to go, I always think there should be no one key holder. There should be key holders of obviously the security of the data and the, and the safety and the and the rules around it. But, in regards to broad insight data or in visibility of results, we should be trying to make that as accessible as possible so that teams can find the reading sites. You've got then thousands or hundreds of people that are looking. Whether it be franchisees at store or team members that had offices in different departments. If they can get greater visibility at a top level data and drill in micro and performance, imagine the insights you continue to do or if you can get reports in their hands faster. Time in a fast moving business a day or two of lost opportunity is huge. So how do you get to make those decisions faster? And how do you stay ahead of your game? >> So as you think of data cloud and as you think of how you're going to build out a DPE specific data cloud, where do you see that going? How, where do you get where's your nirvana and end goal from your data club? >> How do we make better use of that data? So, how do we win? We know that our data repositories are only going to continue to grow. You know, we're a business that was growing at a relatively strong rate. If you look at our previous results, we have a multitude of countries. We have 2,600 stores around the world pumping out pieces every night. And that's creating different forms of data. We have 70% of our customers online. When you're capturing a continuous amount of data. One thing that we want to do is not only manage it efficiently We know that capturing data is a privilege as well, so that we're capturing the right data. And then when you're capturing the right data we still know that the quantum of that will increase. So then how we are storing it and making sure that as we add more data to our repositories we are not actually making its harder to access or it's slower to access. So it's bringing down our reports that we're continuing to optimize and what we're seeing and I touched on when you're bringing time down from hours to minutes with a tool. We're doing that. We're bringing down those solutions. So being able to manage the increasing volume of data we're getting in a more efficient way. Being able to democratize the access of it in a safe, secure, but insightful way. But, you know, having the backing of a service like Snowflake in the background, supporting access and functioning about data. Hopefully, this just means that it will give us more ability to be nimble and do more in the future. >> As you've broken down data silos with using Snowflake and started to democratize data and put it all in one spot your ML becomes richer and more able to make better decisions because you got it all out of silos at this point. >> Yeah.We've got a better floral collection about data. And we can make those data repositories more accessible or no more efficient in accessing them. It's only going to enrich our models and it's going to challenge us. I can challenge and the business can challenge the strategy and insights and BI team to look at a multitude of ways as part of supporting the business. Because they've always got a backlog of reports or solutions they want to deliver. So, we had started a journey of being a data driven company. We have started the journey of a digital company many, many years ago. >> So as we leave today Michael and we wrap up. Last question I have for you is, as you know, everybody's coming and saying do the next bread is coolest next thing. What would you recommend the users of our conference? What would you say? Like how would you, how would you say to go to market and do it the right way? >> Yeah. Let's say the main thing is for those people to reflect upon their own business and understand the challenges at hand. it's very easy to be asked, why aren't we doing AI? Why aren't we doing machine learning? Why aren't we? But those are just solutions. You should be trying to take time to say okay, but what are some of that challenges? And then can we apply those technologies to it? or could a rudimentary approach, approach of just a simple report or a very basic algorithm solve for that. But if you could take your system to the next level with ML, don't do it for ML's sake or if you could take it with a complex data extract. Make sure you've got an angle inside of what you want to deliver. And then know, once you go down the path of anything more complicated, especially with things like machine learning, that it's a never-ending story. And you're probably not going to get the result you like in the first couple of weeks or month because that's what it is. It's a learning solution. It's a ever evolving beast and you can't just throw it out there and say, "Oh, everyone will be happy." So make sure you've got a fair commitment to getting into that game. And that you've got an envision in hand, and that envision will, I can tell you, usually move once you achieve it. Because you're only going to unlock more realities or more alternative solutions that'll grow from it. >> Absolutely. >> So be strong and want the challenges. >> I love that, and it's how we like to think about the data cloud in general, right? Is we are delivering to the business. At the end of the day, data is useless if you're not giving insights and ability for your business to make decisions and move forward. So I completely agree and I really appreciate the time you took today to sit down with me and educate me on Domino's and educate the world on how you're using data to make better decisions in the business. Thanks, Michael. >> Thanks for your time.