Jun 17, 2021
Chase Cabanillas, CIO of Flex Technology Group, has directed data & digital transformations from retail giants like Harris Teeter and Kroger to IoT companies and brings his unique leadership insights on how to harvest this disruptive power.
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We were building out a digital team and watching people grow into what we were building, from a very small team into a, you know, an enterprise structure. That was the most rewarding part for me.
This is Tresata Talks & I’m your host Shreya Nandi!
Our intention is to bring you perspectives – some our own, some from our group of even smarter friends & confidants – to help inform your opinions on how data, as the nuclei of digital & tech, will reshape the world we live, breathe & play in. In this episode, we have Chase Cabanillas,]a close friend of the firm’s and a recognized leader in data and digital power transformations in industries ranging from retail to IoT.
You can find the transcript for this episode on tresata.ai: that’s T-R-E-S-A-T-A dot C-O-M. And let’s keep listening.
Welcome to Tresata Talks, Chase. How are you?
I’m doing well. Thank you. I’m happy to be here.
Chase, when we were meeting to prepare for this episode, I was intrigued by how you wouldn’t call yourself a traditional technologist or a data enthusiast. Yet, you’ve had a career that’s as deep in tech and data as can be. So, how would you explain this dichotomy?
I have been, since a small child, I have looked up to business people and entrepreneurs, kind of like I imagine other people looked up to sports heroes. We just didn’t watch sports much when I was a kid. So for me, people who were doing, you know, interesting things in business, creating companies, those were interesting. So I guess if anything, I would call myself maybe a business person, if I could do that, or maybe a wannabe entrepreneur, since I’m not an actual person who has started companies. But that’s kind of who I aspire to be like, it’s a, you know, great business people.
Given your career trajectory, of all the things you have done, what would you call your greatest learning moment, when your brain went, “Aha! I need to pay attention to this.”
There were probably a lot of smaller ones earlier in my career that had more to do with technology. But, the biggest one for me, probably eight years ago now – we’re building out a digital team, and the building of the team was, you know, literally hiring the first people. We were building the tools, the mobile app, all the things were being built from scratch.
The “Aha!” for me was what I actually love is building the team primarily, that was the best part – picking the right people, developing people, and watching people grow into what we were building from a very small team into a, you know, an enterprise structure. That was the most rewarding part for me. And then on the technology side, I realized at that point in my career, I was never going to want to take another job where I wasn’t building something from scratch or close to scratch, and definitely changed how I approach the rest of my career.
My strategy was always that we would figure out the means as long as we were passionate enough about the end. And that sounds like maybe a little, a little too “pie in the sky” that, you know, we could just figure it out. But even with the most technical people we hired, our emphasis was on people who had a lot of passion for the end. I think part of what gave us that freedom or gave me that freedom also, in terms of building our internal team, is that we were partnered with technology companies, including Tresata at the time, that had their own passion.
And their passion was about the data or about the the technology. And so our focus was the customer, and then we had partners that, you know, helped bring the focus on some of those things that I call the means.
Where did your journey in data begin?
My background is in retail, as I mentioned, grocery specifically, and I have always said that grocery has been in “Big Data” since forever. Or at least way before the term was even coined, “Big Data.” Because if you think about it, a grocery store has a crazy amount of just transactional data. That’s not even including the fact that a standard grocery store has, you know, far more than 30-40,000 different items on their shelves.
So just the data on transactions on a daily basis and the data on what items you carry in your store, that already would qualify as big data if that’s all you tracked. But, you know, starting way back, I think probably in the 90s, the grocery stores started using like loyalty cards and things like that. Then, the amount of data that was generated became, you know, probably exponential, the growth of data, because now you’re tying it to individuals.
And then you’re able to build metadata around that data, that transactional data or those items, who buys them or kind of people buy them. To answer your question, though, about what it was like then, it was, in my opinion, as much of a centerpiece to how we did business or approached our business back then as it is now. It’s just the tools now are obviously much, much better.
If the tools are what matter and in data lies the secret to make those tools intelligent. How does that get delivered?
Mhm, it would be ridiculous for me to say anything but that we are going through massive amount of change. But as you as you pointing out, it’s about the tools, in my opinion. So the same desires are there, right – more convenience, more accessibility, more equality in terms of access to things products, and services, all these things that humans have always strived for, in my opinion.
And certainly in the US, we have always strived for more and more and more. The example we all use in conversations like this is something like Amazon, where you almost you just think about a product you want and you can get it, you know, right away. That’s a reflection, I don’t think it’s not a new need, I guess the idea that I want to be able to think about, you know, a product and get it as soon as possible. That is not a new desire, in my opinion. It’s just now we have better tools for that.
In the case of retailers, we also have better tools to even remind you of things you didn’t know you wanted, which is, again, not a new behavior, though, right? Even going back to like window displays for department stores, they were trying to, you know, make you remember something that you wanted that you never even knew you wanted. The same is true now, but it’s, you know, recommendations in your Instagram feed or something like that.
I’m glad you brought that up. Can you share with us an example, Chase?
The easiest example for me because it’s relevant to my career is the one that I already mentioned, which is the loyalty card at the grocery store. So I think, by now, most people realize what that is doing – that it is a way for the retailer to pair their transactions with their identity. We weren’t interested in the person’s actual identity, we were using a number. So, I’m not one who gets worried about the privacy concerns.
But I do think it’s fair to say that people probably realized less, certainly 10 years ago, I think more so now, they realize that the data is being collected about them all the time. And what maybe they don’t realize as much is that’s always been happening. So you’ll see obviously plenty of Netflix documentaries now, that will, you know, try to scare the – out of you, as it relates to the data being collected by Facebook, or Amazon or Google or whatever, or collected by your phone.
But in my opinion, again, it’s another example of just the tools are better. That’s always been the case, and trying to capture what, you know, consumers want and do so using whatever data you can gather about those consumers – I think that that’s an old story. It’s been happening for a long time.
So slightly off topic, when you look at the pioneers that are changing the ways that we humans think, what truly separates them from the norm?
I don’t know that they are necessarily more courageous or anything like that. And my opinion is, in my observation of people, like the example I will have to use, because anyone who knows me knows I’m like a huge Elon Musk fanboy. But I will use him as an example. My perception of him in interviews and things like that is that it doesn’t occur to him not to disrespect the norm. I don’t even think he realizes that people would choose to, you know, live within the norms.
Obviously, I have a biased sample set in my head of people that I think have, you know, done great things, and disrupted certainly in technology. I think those people also, though, are less interested in the standard measures of success, you know, money being the most obvious one. A lot of times those people do make a ton of money because they successfully disrupt. But usually you will find that they are obsessed with other things.
If the tools are getting better at knowing what consumers need, how can companies keep up when those needs change across generations?
Yeah, I mean, I think for one, there is a different expectation of, or I guess, maybe not expectation, a different definition of quality for different generations, in my opinion. So the idea of like a beta test, or even like an alpha user of a product – that is somewhat foreign to people who did not grow up on the internet.
And so the idea of releasing an MVP, a Minimum Viable Product that, you know, has bugs in it, or you know, doesn’t have key features, that is anathema to many leaders in organizations. That’s less so true now, I think but certainly 10 years ago, that was like insane, that would have been sacrilege to say, “Hey, let’s release this mobile app that’s missing some key features.” And the reason is, they were catering to people like them, who their definition of quality has to do with, you know, completeness.
The, you know, younger generations are used to, you know, releasing an app or using an app that is missing a bunch of features. You know, if you use, you can use whatever example you want – Snapchat, Tiktok, you know, a lot of YouTube for even, you know, for older folks. These are apps, though, that did not have full functionality. Gmail is another obvious one that was in beta for years, because it didn’t do a bunch of stuff. But that’s totally acceptable.
And people considered all those apps that I just mentioned, they considered them high quality apps, because for what they did do, they did a really good job. Or they did it in a unique way, a way that was unique enough or interesting enough that you were willing to look past some of the, you know, short sightedness might be the way that previous generations would see that.
Chase, it’s time to make a prediction, and we’re calling this the “One Mic Stand.” What is the one thing that you would take a stand on as something that we need to pay attention to, but haven’t yet?
I think that bridging the gap in leadership styles, between the generations, to me is the thing that we don’t pay enough attention to, in my opinion.
Ultimately, leadership has a lot to do with motivation, and not-as-great leaders either, like I said, they oversimplify, try to apply some stereotype, or, even worse is they maybe just ignore the difference and say, “No, we should all be the same.” You know, examples being emotion at work. It’s a very common phrase, I think, which is hard for me to imagine, but in leadership of previous generations, it’s like, “Hey, when you come to work, you know, check your emotions at the door” or something like that.
To me, that would be insane. Like, I would never, ever say that to someone on my team, because their emotions is what makes them super passionate and really good on my team. And I would never want them to check them at the door.
That sounded like a pretty good mic drop to me. So, thank you so much, Chase, for joining us here today.
Yeah, absolutely. Thank you.
And there’s plenty more from where that came from. Give our last episode, “Take It To 11 Tresata Turns 10,” a listen to find out how one of the tech companies Chase mentioned came into fruition. If you’re left wondering about anything else, email us at email@example.com. That’s firstname.lastname@example.org. Give us a follow on LinkedIn, Twitter, Facebook, and Instagram. And feel free to subscribe anywhere you’re listening to us. And, we’ll talk data to you soon!