 Hello everyone, and welcome back to theCUBE's live coverage of Teradata Possible here in Orlando, Florida. I'm your host, Rebecca Knight, along with my co-host and analyst, Rob Streche. We are joined by Lenny Colborne. He is the director, enterprise information management from Federated Cooperative, in town from Saskatoon, Saskatchewan. Thanks so much for coming on the show. You're very welcome. It was a long flight and it's nice to meet both of you. Yeah, so why don't you start by telling our viewers a little bit about Federated Cooperatives? It's a very interesting company and it has a very long history. We're a Western-based Canadian company. There's over two million members that own portions of 160 local co-ops, of which Federated Co-op serves them. So members own the co-ops, co-ops own us. We serve the co-ops, the co-ops serve the members. And that is over 1,500 locations, covering over 630 communities. So we are a proud Western Canadian company. And these co-ops tell our viewers a little bit more about these. So we are, as part of the cooperative retail system, we have food stores, sea stores, card locks, gas stations, agri-centers, home and building supplies, pharmacies, liquor stores. And we even have our own petroleum manufacturing facility. So very big, very integrated, very much woven into the communities. The byline is we build, feed and fuel Western Canada. Indeed, indeed you do. So tell our viewers a little bit about how you use Teradata. We have been a very traditional company, very traditional and a little slow to getting into data and analytics. Aggressively, we are investing in technologies to improve all of our processes. That is creating new and new sources of data of which they're not centrally located. So we're really here using the technology to remove silos between processes, make data available and help our business make decisions. So really, we'll go back to the old term in the 90s, decision support systems. That's really what we're using Teradata for today. And are you using it to really, like you said, decision systems so you're using it to really understand what data is coming in from all of the different cooperative and their members and how they're using so you can predict trends or how are you actually using it? Absolutely, and we're looking at it for all aspects of running the business. So how can we best serve our customers by knowing what their trends are, what to recommend and so we're moving in that direction around changing how our membership works to a new loyalty program. How can we help the co-ops be more profitable which skews aren't really delivering what things could we put on promotion to add to baskets and then even within our supply chain how can we reduce the cost and make it easier to order goods which then turns into lower costs at the store which then helps our members. So we are bringing in data from all over the organization. We're trying to do our very best to connect the dots. It's also a big shift from our business. They're used to reports. They look at their reports. They get their reports, they make some decisions. They don't get into the depth of why certain trends are happening. They don't get to slice and dice the data in a way that may be intuitive to them. So it has been the last three years a wonderful shift, right? So that's when I joined the company. We became a Teradata customer at that time and we have made really good progress but we got a lot more good work to do. When you were describing the shift, the shift, it really sounds like a shift in mindset about how you make decisions, what kinds of information you're using to make decisions and maybe going from the old gut instinct to actually looking at what are the numbers saying. How hard has that been in terms of at the culture level of making that change? That's the most challenging, right? You can buy the best technology. You can integrate it. You can organize it. You can prepare it. But it's the people that make the decisions. And so, and that's one of the things I work hard with my team. We're not here to collect data. We're not here to organize data. We're here to use data to drive action. And that has been, certain groups we had really good success. Other groups have been a little slower. So, we're focusing on the groups right now that have really embraced the change and we're hoping to use that as almost an internal advertisement of why some of the other groups should make the change. But again, it's been incredible. The support that our team has gotten, some of the insights we've delivered. And we're excited to move forward from kind of reporting and dashboards and potentially get into some of the AI work or machine learning work. And that's going to be another shift for our company to do. But change is constant. I think we just have to continue communicating why we're making that change and how we can add benefits back to the business. Have you gotten any pressure from the co-op owners to move in that direction from a gen AI perspective? So, what's wonderful about the co-op? It is 160 independent companies. So, it's hard to drive standards, but they do want to drive good business. And so, we're working on ways to demonstrate how they can use their data to make better decisions, but they're also busy running their business. So, we have to be very mindful of how to approach and deliver and over deliver and make sure that we're hitting the areas that they need, not the ones that we're hoping to drive, but we have certain co-ops, they'll sign up for anything that we do. They're very excited about getting to see sometimes some of their data for the first time. When you talked about how some of the co-ops have really embraced this and then they've become internal evangelists for what you can be done, what is possible when you use data to make these decisions. Can you give us some examples of insights that you've gleaned and ways that these co-ops have either found new roads to different streams of profitability or maybe gotten out of certain businesses? Yeah, for us, we've really been driving some insights into their membership and their members and how they're spending and where they're spending and where they're not spending and how often they're spending. And so, they've had an understanding of it but they haven't seen it across all of the lines of business, they haven't been able to compare it maybe to other co-ops and so, I would say in the last year we've made really good progress there. But we're looking to go even further with personalization of offers, really driving down understanding our customer, increasing the amount of data available around products so that people can find the products that they're looking for. So, again, we're making a lot of changes. We every once in a while have to take a pause and go, is that benefiting the company? Is there anything we could do a little differently? Did we hit the point? But what I find is it's opening up their eyes to the possibilities of data and how they could use it to make their decisions because at the end of the day, they're driving their own companies. If we can put the right data in front of them to make better decisions, they're going to see the benefits of that. Do you go beyond that to deliver data products to them such as like a recommendation engine so that the members, the actual members of their co-op can actually get, hey, we see you bought these things. People like that have bought these others. There's a light version of that that we're doing with some of the co-ops but we are doing a major push into personalization over the next year so, I'm excited to see what we have right now on the drawing board and how it turns into reality to help benefit the members and the co-operatives. Yeah, it's part of that you're also looking, again, when we were talking before we came on about the regulations and stuff that potentially could be coming around. Canada is definitely in front of the US from a national perspective with privacy, especially in the personalization space. How do you take that into consideration with what you're doing? It has to be baked in from day one so we have to be very mindful of that. We have Papita and some other, both federal and provincial legislations and we operate in four provinces so we have to be very mindful of that too but we have to bake that in and we have to make sure that personalization is a benefit to the members, right? You know, at the end of the day we ultimately serve the two million plus members and so we have, again, we have to be very mindful of the approach that we take. Have to bake that in and make sure it's tested and vetted. You know, a lot of times you'll find a data source and you've done a good job stripping off things that may impact the law but when you're connecting multiple data sources you may have brought those things back together again and so those especially synthesized data products you have to be very careful of. You mentioned that you've been at Federated Cooperative for a few years about the same time that you've been a Teradata customer. Why Teradata? Well, interestingly, my last company I worked for was a Teradata customer for about 12 years so that was one of my decisions. I've had a lot of trust in the platform and in the company and when I heard that they were also becoming a Teradata customer it made it an appealing change. Yeah. And have you seen the rate of innovation? Because, I mean, you've been a long customer. It seems like I've known Teradata for years and it seems like the rate of innovation within Teradata has really stepped up especially coming into this conference. And we have to continue to take advantage of that, right? So if you've worked with the platform for a long time you have to continually educate yourself on what the new possibility is with the platform, right? ClearScape analytics or running your own machine learning models or any of the new features that are coming you have to start trying them, right? So that's the challenge. You're busy running, you've had success using certain ways of working with the platform and you have to continually innovate within your own development teams to say, try something new, try to solve this problem differently. And we're very pleased that Teradata continues to add new features and ways to solve data problems. So what kinds of conversations are you having at this conference where you are interacting not only with Teradata leaders but you're also talking to customers like yourself, analysts who are trying to figure out what's next on the horizon. Tell us a little bit about what you're hearing and what's most exciting to you. Well for me, a lot of the conversations I want to speak to some of our other Canadian customers and how they're dealing with privacy. We're on premise today with Teradata. So for those that have made the switch to the cloud, how was it? What were some of the challenges to get there? What were the benefits? We also want to look at, maybe not even in retail spaces, people who are creatively solving data problems using the platform. And that's why we come to these conferences is to learn from others, right? And especially from other customers. I mean, it's nice to hear from Teradata. It's nice to see the road maps. It's nice to hear about the technologies. It's where that rubber meets the road with the technologies. Customers who are having success using it, those are the best conversations. And how open are people? I mean, is there a sense of competition or is it the co-op petition or is it because your businesses are so different, it's okay to share best practices? I find most companies are pretty good to talk to or pretty open. I've typically not run into now, we don't want to talk to you because we compete in the same space because oftentimes we're just dealing at the fundamentals with data. And even two companies who are using Teradata, one may be using it for retail, one may be using it for supply chain. So it may be a different conversation but I do enjoy coming to conferences like this to just to have that chat and get energized to go back to the office and try something new. How have you, because all the rage now is data teams and how they're built out, how do you deal with just the influx? You must have tons and tons of data and getting the people with the right skill sets to help you out with that. That is a challenge and when you're building connected data sets, you tend to bump into each other. So we've been delivering products for the last couple of years in a very agile manner, small teams, self-organized, really focusing on what's the problem statement? What are we trying to solve? Do we have the data available to do it? Do we have a product owner from the business that will lead and guide us, not build it, then they will come mentality but really work closely with the business. Very small iterations to get to a most valuable product that we can get out in a short period of time and then let the feedback drive its future creation iterations. And we've had success in that but because we've added so much data as you add new team members, they're like, what data do we have in them? I think we have all of it, you never do, right? So we're looking at other ways to map even our own data sets, whether it's an internal data catalog or ways. So one of the mantras of my team is what we really want to do with data for the bit. Can the business find the data? Can they trust the data and can they use the data? And if we've met all three of those criteria, we've done our job and trust is there, usage we're getting better at, finding again as we add more and someone's not familiar with the data set that we've produced because maybe they don't work in that area of the business, we've got to get better at putting catalogs and stuff together so they can find it. Lenny Colborne, thank you so much for coming on theCUBE. You're very welcome and thank you. Thanks. I'm Rebecca Knight for Rob Stretche. Stay tuned for more of theCUBE's live conference, live coverage of Teradata Possible.