Ep 41: Transforming Retail Through AI with Former Giant Eagle EVP & CIO Kirk Ball

‍Evan: Hi there, and welcome to Enterprise Software Innovators, a show where top tech executives share how they innovate at scale. In each episode, enterprise CIOs share how they've applied exciting new technologies, and what they've learned along the way. I'm Evan Reiser, the CEO and founder of Abnormal Security.

‍Saam: I'm Saam Motamedi, a general partner at Greylock Partners.

 Evan: Today on the show, we’re bringing you a conversation with Kirk Ball, former EVP and CIO of Giant Eagle. Giant Eagle is one of the largest regional supermarket chains in the United States, with over 37,000 employees and more than $11 billion in annual revenue. In this conversation, Kirk shares how AI is transforming the retail industry, the impressive scale of Giant Eagle’s operations, and AI’s potential to shape the future of the enterprise.

Do you mind kind of giving our audience a little bit of background about kind of how you got to where you are today? 

Kirk: Yeah, sure. So love the technology space. In college, I was a finance and accounting major, which I thought, you know, I wasn't all that excited about when I started to get to the end of that journey that I was going to have to go into auditing and travel all over the place.

So I took, uh, took some development classes kind of as, as, uh, electives, and fell in love with it. And then I turned right around and went and got my two year in technology and started slinging code before I got out of school and, uh, had a lot of different roles, systems analyst, enterprise architect, program project manager, and just really loved the technology space and the ever changing dynamic of technology. So, you know, I started to make my way a little bit out of, uh, out of the individual contributor space and stepped into some leadership roles and software development and then into, uh, infrastructure and technology and then somehow, uh, got into the digital space.

And then, uh, boy, it just, it just kept going. And, uh, you know, I worked with some really good teams. So my success is really a reflection of the great teams that I've worked with. Certainly I've worked hard and I kind of have a saying that I pulled out of a movie. Chance favors the prepared mind. And boy, I'll tell you what. That's so true. And so I worked hard to try to keep my skills current and even forward looking, but it's really a reflection of the great people I've worked with. And I always worked hard to surround myself with people that were smarter and better than I was and learn from them.

And it's, it's, uh, it's been awesome. And then stepped into a CTO role at the Kroger company and then, uh, CIO at a clinically integrated health network and then, uh, CIO at a, another retailer in grocery pharmacy and convenience called Giant Eagle. And, uh, then I recently retired and, uh, now I'm doing some consulting and advising for some startups and just having a great time.

Evan: Do you mind sharing kind of some of the ways that, you know, kind of modern retail or kind of groceries using technology in ways that the average person might not expect?

Kirk: Yeah, it is, uh, you know, every once in a while I would go talk to, uh, university students or, uh, MBA students and talk to them about the grocery industry and the fact that it's amazingly high tech and, uh, you know, so many of them are really just surprised. You know, from image recognition, computer vision and image recognition, which is an application a lot of retailers are chasing now to figure out how to determine when something's out of stock, on a shelf. 

The number one thing that frustrates the customers when they come into a store or they do a digital order online and that product is not available that they put in their basket that they want to put in their basket while they're in store. So, you know, making sure that you get a quick signal from the time at that last item of that Particular product is picked off the shelf and let somebody know that and doing that with computer vision and sending doing some compute on the edge to do some signaling, and help the team member understand, Hey, we got we got product.

We need to get back out on the shelf pretty quickly. And obviously the Team members are incredibly important in that loop, but it's technology that helps, helps signal, uh, you know, all of the setting of prices is done in a lot of instances. Now with machine learning, you want to optimize the assortment that suits the customer that comes and shops in that store in that particular region, that particular area. So personalization is massively important. Machine learning is used, uh, in setting the assortment, setting the optimized price to balance between margin and volume of sales and driving traffic from your customers and learning which, which products are price sensitive, which products aren't as price sensitive. Uh, and so there's a ton of machine learning that goes on in that space of, uh, setting your assortment and setting your prices and that changes all the time.

When a season comes or a season goes or a particular weather day occurs, that changes, you know what people want to buy and you have to, you have to be prepared for that change and your supply chain has to adjust to that, right? So, uh, you got to make sure that you got the product in store. 

You know, I mentioned, uh, computer vision. There's a lot of thinking going on now about compute at the edge. There are a lot of decisions that get made in a store. You know, you think of the store manager or the team members in a store, there's a ton of things going on. And so how do they optimize their time? What's the most important thing for them at a given point in time, uh, what activity is the most important thing for them to do.

And so that compute at the edge and being able to make decisions in real time is pretty important. And then you've got, you know, uh, I'll go back to things that are pretty straightforward, but they're still massively impressive. 

You know, at one point in time, at one of the places that I've worked in the past in retail during Thanksgiving or the day before Thanksgiving or the day before Christmas, we would do almost as many, if not more, transactions per second than what Amazon would do. So you think about that in the, in the grocery space and you're like, no, that can't be. We were, we were doing a lot. I mean, we were doing hundreds and hundreds, if not low thousands transactions per second, every second, somebody checking out a basket.

So, you know, that, that payment processing, that fintech infrastructure that you have to have. And again, just really all the technology and the thinking that goes into really trying to make sure that we're giving the specific customers the specific things that they really want to buy at a price point that matters to them.

Evan: Like, can we talk a little bit about the kind of the scale of operations? Because I think this is something that I think, At least for me as a shopper, might not fully appreciate where you go into the store, can't get what you need. You check out and you go home. But behind the scenes, right. If I remember right, like a Kroger is on the order of like a half million associates, right. They're not sure there's like huge logistics networks and kind of, you know, you know, vendor management, there's a lot of it goes on behind the scenes at a scale that would probably be unbelievable to most people.

Do you want to share a little bit about that because I think it might be surprising to listeners. 

Kirk: Yeah, I'm not really sure what the count is today, but when I worked there, we would do, I think it was nine, nine, nine million transactions a day. And so you think about that, that's 9, 000 checkouts. And so basket sizes, you know, vary, but you've got to make sure that products on shelf, you've got to make sure that you're offering promotions.

You've got to make sure that product is getting to the stores to keep the shelves stocked, but you also don't want to have too much inventory. So you don't want to spend too much capital sitting in the back room, not, you know, churning and driving revenue. It's just a massive scale. 

And at one of the places I worked, you know, we had 26, 2700 locations. I'm sure there's more now. You know, and each, each store would have, I don't know, probably eight to 10 self checkouts. They would have probably 10 to 15 to 20 manned lanes. So all of that technology, and then you've got to run applications in store. You have to be able to order product. You have to be able to count inventory.

You have to be able to receive product in the back room and track the inventory while in store, know what's coming from a store, just the scale of, and then you've got lots of distribution centers behind that, right? And you've got lots of division offices. So all the people that are doing the buying, doing the merchandising, setting the prices to be able to work at companies that have that kind of scale. At one time, you're, you're also a manufacturer. Right, you're manufacturing, uh, or sourcing to a third party, manufacturing your own private label products. You're a huge, massive supply chain with, uh, with millions of miles traveled every year. And then you've got all those store locations and you've got the administrative areas that are executing all the functions that it takes to make customers happy every day.

So it's, it's incredible scale. And it's, it was, it was a blast. I really had a great time and, uh, learned a lot and was really blessed to work with those companies.

Saam: In January 2024, it's hard to not be thinking about AI as like the theme in software and in technology in a way that perhaps hasn't been in the past, despite the fact that data science and machine learning has been prevalent in a lot of businesses, including some of the examples you cited. Maybe to start, like from your vantage point, where do you think we are in this current AI hype cycle?

And what's some of the impact that you're seeing in, let's say, the grocery industry with this new advent of generative AI? 

Kirk: Yeah, you know, I think it's a really good question. And the thing I'll go back to when I was, you know, early in my career in about 1903, it feels like, but, uh, when I first started out my career, you know, the, the pace of change, change always occurred, but the pace and the cycle time from one point to another point was not as fast as it is now.

So I think the thing that companies are trying to figure out, you know, there's these really incredible, brilliant technologies that have the capability to revolutionize dramatically how people go to market, take their product to market, the cycle times that they can generate a marketing plan, for example.

Maybe I can take a marketing plan that usually takes me 8 to 10 weeks to get generated and put out into the market. Maybe I can take that now with the generative AI platform down to 8 to 10 days doesn't mean the humans, not in the loop, the humans in the loop, but all the all the slow work that the human would have to do to put that marketing plan together. Now they've got an assistant that really helps them. Uh, you know, I've got, I've got examples of folks that, uh, I talked to, uh, I won't mention their names, but big, big bank where they're doing some work where they've got generative AI assisting with complex support calls and complex customer interactions to give that agent or that, uh, person that's dealing, uh, in that situation, they're giving them additional guidance and suggestions.

Right. In real time to help them make sure that that customer leaves satisfied. You know, I think the ability to look through legal documents when I, you know, when you do a software hardware contract, you probably look for 90 percent of the same thing in every contract. Generative AI can do that for us. Right. And we can reduce the cost and the cycle time. I think down dramatically. 

Um, the ability to, uh, drive greater, deeper personalization. Uh, the ability to change decisions and the pace at which decision, decisions get made. So, you know, it used to be in a grocery retail space that, um, when product was out of, off, out of stock on a shelf, um, you would pay team members in some instances to go around and kind of identify there were holes or a customer might, you know, talk to somebody at the checkout and say, Hey, you're out of this product.

Um, but, Now, if you have a computer vision and you've got decisioning at the edge to get that signal, that optical signal, that visual signal translated into something that you can get to a teammate almost immediately, think of the cycle time. And now you've reduce the frustration that your customers feel you've helped the associates be more productive, and they're doing more value add kind of things, right?

So they're focusing their time and getting product out to the shelf where it needs to be, as opposed to trying to figure out where they need to get product on the shelf. So in my opinion, there are so many use cases for artificial intelligence. 

Uh, you know, just that use case that I talked about, how do you get real time personalized pricing delivered to a person while they're in store. Think about how you have to have, you have to know where the person is, you have to know who the person is, what level of loyalty they're at, where are they in the store, and what products are they standing and dwelling and looking at, and how do you then quickly calculate what's the right price for that person. To get them to put that item on a shelf, uh, that makes them happy and it's on their list and they get a good value and maybe you moved one more item into a basket. 

So, you know, I think part of the challenge is, is how do all of these companies figure out the right applications to go after with the technologies that are presenting themselves. And so this is a situation where you can't just rely on your own thinking inside. You have to go see what others are doing.

We periodically go out to Silicon Valley and spend time with Greylock, once or twice a year. You know, I've spent time now with iconic capital and helping people understand, Hey, look, you know, there's an opportunity here. They're invested in a company that's doing pretty cool things that you should think about. So you have to get outside of your comfort zone and you've got to get out and see what's going on. You have to talk to people. You have to talk to vendors. You have to talk to folks in the PE and VC world, and you have to go spend time at universities and you have to learn, and then you get to figure out, okay, these are all the potential tools in the toolbox. Where's the optimal places that we want? Cause you don't have unlimited time and money and resource. So where are the places that we can apply these technologies at to have the maximum value in the quickest amount of time? 

And in some instances, you could get third party help, but your cycle time, you have to make decisions quicker. You don't have the luxury of waiting three to five years to really figure out your strategy, where you want to do your first or second generative AI application, uh, because it's, it's changing the landscape rapidly and, uh, you're going to be. You don't want to put yourself in a situation because you take too long to make a decision on the application of that technology and you find that you're in a competitive disadvantaged situation because you took too long to make your call.

And I think that's the, that's the challenge and that's the pressure, I think, that a lot of people feel now. 

Saam: One of the things that I think is interesting with these really large technology waves is they like fundamentally can change the way business gets done in a way that's hard to imagine, like a priori, right? I mean, if you think about like the computers or cloud computing. 

Like, the example you just gave, even something like the marketing plan construction, right, where you said, Hey, you can use generative AI to build marketing plans and marketing assets, and maybe 10 X or a hundred X the speed at which you're building those things.

That could really change what it means to be a marketer as an example. And so I'm curious, like if you were to put your, you're someone who's been leading technology organizations for, for many decades now, like what's the world going to look like in a decade? And maybe to make the question more concrete, like, are there one or two ways that you think AI might impact generative AI might impact the way, let's just take grocery. Grocery operates. That, like, today feels like science fiction. 

Kirk: Well, part of the key is how do you take these brilliant technologies, and I use that term, I'm reading a book right now called The Second Machine Age, Work Progress and Prosperity at a Time of Brilliant Technologies, and it's a really fascinating book.

And, you know, how do you This is part of the challenge, right? How do you think outside the box? So we talked, we just talked about people trying to figure out how to apply these technologies. How do you think outside of the, uh, the, the, the wall, the box that you're in because you've worked in a certain industry or you've, uh, things have moved at a pace where you, and you've gotten comfortable and you have to constantly challenge yourself every day to reimagine.

Uh, and that's why it's so important. Uh, to listen to lots of different people that are doing things in a lot different way. You know, you've got, um, I think, I think paying with your, with a biometric checkout. I think that the checkout line should be the last place that I put the last item in my basket and then I just walk out.

But you think about, you know, you have to manage loss prevention. You have to make sure that people are getting the service that they need. You know, there's a lot of great interaction that goes on at the front end of the store. But boy, if you could just be able to eliminate lines, just the elimination of lines, whether it's at the deli, whether it's at the front end, regardless of wherever a line forms. That would be awesome. 

So I think, uh, it has a lot to do with, you know, I think certainly delivery product, the ability to get product delivered to your store, to your tastes and preferences, the way that you would pick the, your, your goods and services, the methods of payment. And better yet, if I could just pay where I put my last item in the basket, that would be even better. 

And then don't forget about the associates, you know, really helping supplement some of the mundane tasks, whether it's looking at temperatures, uh, in cold cases, X number of times a day to make sure that those cold cases are up to spec and temperature and the fit.

Hey, just automate all that. We did, we automated all that, right? Temperature temperature sensors. They connect up to the wifi network. They push signals every so often, and you use, uh, machine learning on the back end to determine when a machine, or when a cold case is going out of cycle, and it's time to repair it before it actually quits, right?

And you save a lot of loss prevention. So, uh, you know, I think, uh, being able to communicate and connect with a customer whenever, wherever, and however they want continues to, uh, evolve, and I think it will continue to evolve. 

And look, I think people or customers, regardless of what type of retail you're in, I think they're like water or electricity. They will always flow to the path of least resistance, always. And so how can you use technology to eliminate friction in every single interaction that a customer has while in store or while out of store interacting digitally? 

How do you get them the information that they need? How do you give them the opportunity to buy something when and where and however they want? How do you have the opportunity to deliver what they want? When they want it, where they want it and how they want it. So I think, I think you're going to see a continued elimination of friction. I think that's the overriding theme. 

Saam: We've been talking about a lot of the ways AI can transform businesses. One important precondition for that transformation is having the right culture inside an organization. A culture of continuous learning so that your team becomes, just like we talk about products that are AI native, you can imagine teams also becoming AI native. And so just given the speed at which all this innovation is happening, How do you build that culture of like innovation, risk taking learning so that, you know, and I'm asking this question for all the technology leaders who listen to the show, you know, what are a couple of points of advice you'd give them on how to build that culture so that they, their organizations and people can take advantage of the opportunities for AI in their business?

Kirk: Yeah, it's a really good question, Saam, but what I'll tell you is hopefully they've created that culture long before the application or the advent of AI, right? In my opinion, my humble opinion, you should always have a culture where you're encouraging diversity of thought, you're encouraging continuous learning, you're encouraging finding lots of areas inside of your company and outside of your company. What are other people doing? What are third parties? What are vendors doing? What are universities doing? Going to some conferences here and there, doing a lot of reading. You should always have in a technology space, you should always have that culture.

It shouldn't be something that you're trying to start now. But to your point, Obviously, as new technologies and new capabilities come along, you have to make sure I think it's a combination of continuing to educate the team that you work with, maybe bringing in an additional resource or two that's already got that kind of capability, leveraging your third parties that you work with.

Look, they're all trying to figure out how to, you know, all the consulting firms are, they're training their consultants and how to go out and sell, you know, an AI practice. So. Leverage them, right? They're, they're, they're learning as well. And they're, they're, they're trying to lead the way and being able to help, uh, you know, the customers that they have so you're spot on. 

You have to continually prepare. Chance favors the prepared mind. It always does. And it always will. You should constantly be preparing your mind and your team. And your organization, it's also, you have to prepare the organization. It's not just the technology team, right? I think, how do you help your business partners understand the potential applications, whether it's in marketing, whether it's in more tech, whether it's in merchandising, whether it's in supply chain. And there are all applications there for generative AI and for machine learning. And we've talked about several of them today. 

So, you know, I think those ways that we mentioned on how you continue, uh, continue to, uh, raise the acumen of your, of the team that you work with and the organization you work with. Uh, I think we mentioned a couple of those. And so that's, that's what I would encourage people to do. 

Evan: So at the end of our episodes, we like to do a, um, a bit of a lightning round where we're trying to go for more shorter, punchier answers, kind of like the one tweet version. Saam, do you want to kick us off with the first lightning round question?

Saam: Yes, absolutely. Kirk, as someone who's worn this hat multiple times, how do you think companies should measure the success of a CIO? 

Kirk: I think it's based upon the culture of the organization that the CIO leads and the culture that they help influence across the organization, and then deliver, deliver, deliver.

Do what you say you and your teams are going to do, and also Help drive innovation where appropriate. 

Evan: What is one piece of advice you wish someone told you when you first became a CIO? 

Kirk: Look, I'm a very competitive person. I played a lot of sports. Um, so I like to win. Winning comes in different forms though. And I wish somebody would have told me a little bit earlier in my career, compete with yourself, and compete as a team. It's a team sport. You know, I was always wanting to be the best developer, the best at this. And I finally, you know, I learned, fortunately it didn't take me too long to learn, but you know, if you're like, and I'm going to show my age here, but if you're like a Magic Johnson or Larry Bird, Look at those guys. The first year in their rookie years, they made everybody around them better. 

Be the kind of player that raises everybody's game. Help everybody be successful. Have a, have an abundance mentality and you will be wildly successful beyond all your dreams. 

Saam: How do you think CIOs should position themselves to best collaborate with the rest of the C suite?

Kirk: I think you have to, first of all, give confidence to the C suite that you and your teammates, uh, that you work with know what they're doing and they're staying current, but as equally important, there's two other things. As equally important, you have to spend time going out and living in their world. In our case, in a retail case, go out and spend time in stores, go out and spend time in DCs, go see how the people actually use the systems that you create and that you implement what works, what doesn't work and listen to them and make changes.

And then the third thing is, I think the CIO. Uh, more than almost more than anybody in the organization has to be a master storyteller, right? You have to tell a story to get your organization headed in the right direction to get them encouraged and enthused and engaged. You have to tell your business partners a story about how the application of a given technology can potentially create disruptive innovation in their space.

You have to be able to talk to the board and tell a story. But the magic to the storyteller is being able to tell a story, getting the point that you want to get across, but speak to it, but tell the story in the context of your audience. Don't tell it in your context. 

If I go in and I talk about a bunch of ones and zeros, and I talk about the eight different, uh, seven to eight different aspects of AI. If I talk to them about how these capabilities can transform their business. Now I'm talking their language. So that's what I would say. 

Evan: Maybe switching gears to the more personal side, um, what's a book you've read that's had a big impact on you? 

Kirk: Well, I, I mentioned one earlier, The Second Machine Age, Work Progress and Prosperity at a Time of Brilliant Technologies. And I got one I'm in the middle of, it's called The Changing World Order, Why Nations Succeed and Fail. And there's lots of lessons there and, uh, you know. How do we, how do we pay forward? How do we help, you know, our country and other, other nations be successful? And so that's a, it's a fascinating book. Uh, you know, why do nations fail?

Why do they succeed? And what happens over time that causes them to, they were once successful and now they're not so successful. So it's a, it's a fascinating book. 

Saam: And maybe sticking on the personal side, what's an upcoming new technology and it doesn't AI related that you're personally most excited about.

Kirk: The one I'm most excited about is I've got a down payment on a 2024 Lotus, uh, Emira. And that's a, that's a brand new, uh, Lotus that's coming out and it's, uh, it's an awesome car. I can't wait to get my hands on it. So that's my personal piece of technology. I'm getting pretty excited about. 

Evan: And can you explain what about, uh, what about the technology is, uh, exciting?

Kirk: They've done a wonderful job as far as the design. It's a mid engine car. What they've done with, uh, the tweaking, the supercharge, the turbo supercharging of the, of the engine, the way that the aerodynamics work that the faster you go, the more downforce goes in the car, which gives you much more stability on the road.

Uh, and just the way that they've added a bunch of technology, but you still feel the road when you're driving. So it's, it's going to be, I can't wait. Pretty excited. 

Evan: Okay. Well, next time in your town, Kirk, uh, I might have to ask for a ride someplace. Cause that was pretty cool. 

Kirk: Yeah, that'd be awesome. 

Evan: Okay. Maybe, um, one last question. Um, I know we're almost out of time, but what do you think will be true about. technology's future impact the world that most people would consider science fiction today? 

Kirk: Oh, I think it's, I think it's going to continue to accelerate and change the world. I think, you know, the thing that we have to make sure is that the way in which it changes the world is positive and not negative.

Uh, you know, I think, uh, you know, you read a lot of people coming out and talking about AI and the fact that if it's used in the wrong way, it can create, you know, significant challenges for mankind. I hope that we use AI and I'm sure we will, I hope that we use AI in a very positive way. You know, I think quantum compute I think if we can get quantum compute at scale and get it and get it produced in mass Uh, I I think that has the opportunity to just change the way that everybody lives. 

Evan: Um, I feel like we're going to find out sooner rather than later.

Kirk: That's for sure. 

Evan: Uh, well Kirk, really appreciate you taking the time to chat with us today Uh great chat with you and looking forward to uh some future podcasts or rides with you. 

Kirk: Yeah. Awesome. Thank you

Evan: That was Kirk Ball, former EVP and CIO of Giant Eagle.

‍Saam: Thanks for listening to the Enterprise Software Innovators podcast. I’m Saam Motamedi, a general partner at Greylock Partners.

‍Evan: And I’m Evan Reiser, the CEO and founder of Abnormal Security. Please be sure to subscribe, so you never miss an episode. You can find more great lessons from technology leaders and other enterprise software experts at enterprisesoftware.blog.

‍Saam: This show is produced by Luke Reiser and Josh Meer. See you next time!