 From New York, it's theCUBE. Covering Inforum 2016, brought to you by Inforum. Now, here are your hosts, Dave Vellante and George Gilbert. Welcome back everybody, this is theCUBE. We go out to the events, we extract the signal from the noise, Corey Tollefson is here, he's the Senior Vice President and General Manager of Infor Retail. Corey, welcome to theCUBE. Happy to be here, thanks for having me guys. So you came to Infor just about around the New Orleans show last year. Just after the New Orleans show, it's been a wild ride. So about roughly 18 months. What brought you here? Well, first of all, I think the culture, the culture's amazing, I think the culture that Charles and Duncan, Stefan, Pam, have brought to the table has been so invigorating. And the passion of being disruptive and conventional thinking is really what drove me here and more importantly, a lot of the people have come with over the course of the last 18 months. So New Division, big thrust into retail, hot area, obviously. But one that's kind of being challenged, being disrupted. Talk about the division, what your goals are for the business unit. Well, the market needs it. So we're just mirroring the market. So for the last, if you look at the prevailing legacy solutions that have been out there for years, it's pre-mobile, pre-social, pre-internet. A lot of the retail ERP per se have been written in the 90s, late 1997 for SAP, mid-90s for Oracle. And we just thought the time was right for a technology provider to come up with some fresh thinking and be innovative and adapt with all the changes that retail has been facing over the last 20 years as well. People say, oh, wait a minute. We're talking in for us, this is a roll-up of like, whatever, 70 legacy software companies. How are they taking this mantle of innovation? Well, I think I set the record for the most interviews over the last five years with Duncan and Charles and Stefan because I didn't buy into it. Until about 18 months ago, it clicked, it's real. We have a real digital practice, hook and loop digital around, and hook and loop traditional core of going in and going after that user experience, doing end user research with all of our retailers. That's what the retail industry needs and wants. And it's not a collection of old legacy products. Maybe six years ago, we've moved on from that. In fact, I've never felt more vigorated and the market has been reacting with their wallets. So everybody in that space has kind of an Amazon War Room mentality. Trying to figure out how to use their physical presence as an advantage. It's been difficult. Why has it been so difficult and what is the answer there? Well, it's been difficult because if you think of Amazon, it's the ultimate endless aisle. You can never run out of product. Anything you need, they have it. Now why retail or customers go into a retail store is because there's a brand and there's an experience that they like, they like the personalized shopping. And there's technologies that we're creating around the concept of converged commerce that allow the concept of endless aisle. So you can have that same brand experience and take advantage of that endless aisle capability where if you're a retailer, you walk in the store, they don't have your product rather than leave or showroom and buy something from Amazon. You can simply buy it off of an application within that store and it can be shipped directly to your house. Can you, when you go into a retailer and explain that converged commerce concept, do you have to quantify it or is it so visceral and it's such a hot topic that they sign a contract with you right away? Well, it's a mixture of both. I mean, anything that touches the customer, there's an overemphasis on wanting to impact and attract and retain the customers coming into the store. So anything impacting the in-store experience is getting a bigger portion of the budget or pie as opposed to speeds and feeds and hardware and infrastructure and things of that nature. And do you see, well, the hook and loop sort of matured from working with one sector to going across the product line and then helping customers. Do you see some of your retailing technology moving beyond retail? That's a great question and we'll get to that one. So when you look at the intent to acquire, we're not done, but with the announcement yesterday with Starmont, they're a converged commerce in-store experience platform. That in-store experience clearly applies for retail. There's no reason why it couldn't apply to other industries like oil and gas or to healthcare or to service providers because at the end of the day, we all serve as customers and they might be called patients. They might be called building contractors. But at the end of the day, that's what these in-store experience applications provide. So Corey, unpack a little bit this converged commerce concept by maybe describing the future retail software experience from a consumer standpoint. What does that look like? Well, I think it's the analogy of, well, this technology exists today and we want to provide this to our retailers where you do a lot of the research before you go into a store to buy something. You'll browse online. You'll figure out what size you want. You'll figure out what material and what attributes are appropriate for you. And sometimes you might not go through the cart. You might abandon the cart. Well, we have the technology where you can walk into a store and it'll identify you as, hey, Mr. Valente, you, I noticed you were online. You didn't hit the click button. You didn't buy it. Can we offer you a 10% promo to buy that while you're in the store? It's little technologies like that that can personalize the retail experience so we can start getting that unified experience, whether it's online, catalog or in the stores. So real time and data really start to play a big factor here. That's right. So what gives Infor an advantage, particularly from a data perspective? Well, I think Infor has an advantage. You know, we made an acquisition. It just closed. I think you're familiar with it. It's called Predictix. So Predictix is an analytics platform. And really when you think of Predictix, think of it as the algorithms that a retailer needs to make sure the right product is in the store at the right price point at the right time. And the difference between Predictix and say some of the other legacy solutions out there is it was built cloud native to begin with on AWS. It's a very configurable platform for specific, you know, Charles talks about micro verticals. So when you look at retail, don't just think of retail in general. There's soft line apparel, there's grocery, there's department stores. And they all have their little nuances where they're different and you can make those configurations on Predictix as a platform and we can ensure that the right products are there at the right time. So predict this talk M&A for a second, Predictix. And then you made an announcement that you intend to acquire Starmont yesterday, I guess, right? Where does, where does Starmont fit and how does it fit with Predictix? Well, so I think the best way to look at Starmont is it's a good brand, but what's even more important than the brand is they're really good people, very talented people. Not very often can you find an organization that has great customers, but also has a lot of engineers that live and breathe the store space every single day. So from our perspective, we're going to fold them into our mix with our rhythm platform team. And we've been working really hard at getting the e-commerce side down with our rhythm platform development team. Now we have the in-store experience and the in-store developers and we can marry those two together. And again, I want to be selfish and say that this is strictly a retail play, but the reality is at any point in time, there's other customers. Like I said before, somebody accessing a government website or a public healthcare site, they're technically a customer. And the more we can infuse that science with a combined experience from Starmont, the more offerings we can take to market. You know, when I'm listening to you, it's pretty clear there's like a lot of data feedback loops that are coming back, some from the operational systems, some from the customer experience, along different touch points. But in reality, they're not really that different. They show up as machine data. How do you take all that data and improve either the experience for the customer or prospect the next time or the operational delivery of the experience? Well, let me give you a use case. So when you look at predictive modeling and predictive solutions for retail, the alternative to what we offer around machine learning and native cloud is this concept of time series. So if you're a retailer, they look at it and say, hey, here's a bad example, but here's a brand new glass of water. They compare it against what used to sell and trend as other brands of water. But with machine learning, we load up all items and we tease out factors like weather and we tease out factors around holiday to get the optimal forecast that this is going to sell X amount of units and X amount of stores. So from a big data perspective, that's really how we feel like we're differentiated around the science. Would it be fair to say that those data sources can be just as easily external as internal and that a key part of the job is constantly enriching the 360 view or the context to make that high fidelity prediction? Yeah, absolutely. I mean, again, this platform is something that we're going to take into other industries too. I mean, when you're in retail and you're forecasting what SKU is going to be in the store, the worst case scenario is somebody doesn't buy it or somebody goes in the store to buy it. Think about healthcare. If you make predictions around the patient experience, if you don't have the right product in the right room, somebody dies or has an issue, right? So we're going to keep taking that feedbook loop all the way across the supply chain back into this platform. So what do customers need to be successful at that description of the time series and that machine learning? You've got the infrastructure from presumably from AWS in terms of a data pipeline, right? That is people struggle with the data and Hadoop but it's so complicated. Okay, the cloud guys kind of got that right. We talk about this all the time. Here it is. Here's a service. Okay, great, check. But then you need domain expertise. You need some data science. What else do you need to succeed? So this is what really gets me excited and one of the reasons why I'm here back to your first question is we start with end user research in mind. So before we start an engagement, we bring in our hook and loop designers up front to wireframe and make sure that end state experience is what the business users will adopt. So the age old adage of, hey, it's not the product that didn't work per se. It's the change management or business process change. Technically there's no need for, well very little need for process change management if you get that end state completed up front. So we feel as though the differentiation around designing the end state up front versus working through the traditional waterfall methodology of here's a lot of requirements, we'll go away, we'll develop some stuff, we'll throw it back to you and tell us if your user's like it. We feel like that model's dead. And so that's how we think we're much different in these applications. And in terms of you talking about micro verticals before, philosophically, you've worked in a number of software companies, what's the difference? Is there philosophy of, well it's just that last mile is too much of a pain in the neck. We don't want to do it. Or we want to let our ecosystem do that versus the in for philosophy, can you juxtapose it? It's a little bit of both. I mean, the secret sauce per se is some of the applications that are more configurable like the predictix applications or the end state in in store experience with Converge Commerce. It's the traditional, what some pundits call retail ERP which is really around automating certain data processes. No one's going to differentiate around effectively managing a purchase order or an invoice much better. So for us, it's a combination. We can get the unique secret sauce and configure that end state that they're looking for of the predictix applications in Starmont and some of the traditional core applications. We can automatically bring and embed best practices around those traditional aspects. And again, a lot of people would say, software comes in, the TAM is not big enough for us to go after. Or it's too expensive for us to go after. How do you rationalize a square-nose circle? Have you talked to Duncan? Has he been on here before? This is something we've been talking about for a long time and he jokingly said, I realize why no one's done this is it costs a lot of money. I mean, you've seen who we've acquired over the last 12 months and a lot of them are based upon servicing retailers much better. So this is one of those things where we have an innovative team that believes in disruption and doing something and retell the way it should be. But we also have the backing and scale of a company like Infor where we can make these strategic bets, you know? One thing that we heard from the guy who founded predictix actually, his name escapes me right now. It's Mulham. Mulham, yeah. That actually goes back to your era at Retek and maybe even a little before that, you know, I too as the analytics engine could go in before SAP. And it looks like predictix and maybe StarMount can go in before or instead of a wholesale renovation of the transaction application, which is the really hard, you know, heavy lifting, very expensive thing. So in other words, high value, low cost, very high value ROI is what it sounds like it's possible now. I would love to say you need to go in for retail for everything end to end. The reality is that there's some investments that retailers have made. And the reality is we can provide that value around the core. So we can make, we can dummy down the execution and embed our science and analytics on top of it, both for in-store experience, online, as well as with our predictive applications to your point. All right, we have to leave it there Corey, but I'll give you the last word, you know, lay out the vision, you know, of the future where you want to take this business. Well, I'm excited. And like I said, it's been 18 months and it's been unfathomable about how much growth we've had. And I'm just chomping at the bit to tell you some of the numbers, but I know I've been told not to since we're privately held, but we've grown significantly and we're having a lot of fun. We're being disruptive. And frankly, the market's been craving an alternative to the duopoly for a long time. And we feel like we're providing a good experience for them so far. Well, the excitement's palpable. We love to bring it to our CUBE audience Corey. Thanks very much for coming with us. I appreciate it guys. Yep, thank you. All right, keep it right there, everybody. We'll be back with our next guest is theCUBE, we're live from New York City, right back.