What 40 Million Daily Transactions Taught One Restaurant Chain About AI

[00:00:00] - [Speaker 0]
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[00:00:39] - [Speaker 0]
What does it actually look like when AI and analytics move beyond theory and start driving real business decisions at scale? Well, at SAS Innovate, I've been speaking with leaders across so many different industries here in Texas and beyond. But some of the most interesting conversations come from the organizations where data is not just a strategy. It's actually a difference between profit and loss every single hour of the day. And my guest today is David Gardner, and he is the senior director of analytics.

[00:01:13] - [Speaker 0]
And he's got a great story to share. A story about a family run business with over sixty years of history. And he's got a great story about a family run business with over sixty years of history that is now operating more than 300 restaurants and processing tens of millions of transactions every single day. And he will share how they've moved from gut instinct and backward looking reports to real time data driven decision making across the entire business. They've extended breakfast hours based on data rather than intuition, and they've also optimized staffing, forecasting demand with remarkable accuracy, and even improving drive through speed by seconds, seconds that directly impact revenue.

[00:01:57] - [Speaker 0]
So this is not a story about pilots and demos. This is a story about analytics delivering measurable outcomes right here, right now. And, yep, we will talk about how AI is also being used in a practical way, not a way of replacing people, but as a tool that is helping managers make decisions faster, especially in an industry where speed, consistency, and customer experience are everything. So if you've ever wondered what real ROI from artificial intelligence and analytics looks like in the real world right now, this conversation will bring it all to life. Regular listeners will know I always say that I only partner with companies that align with my values and what I'm trying to build here at Tech Talks Network.

[00:02:42] - [Speaker 0]
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[00:03:44] - [Speaker 0]
But enough from me. Let me introduce you to my guest now. So thank you for joining me here at SAS Innovate. For everyone listening, can you tell them a little about who you are and what you do?

[00:03:55] - [Speaker 1]
So my name is David Gardner. My title would be senior director of analytics. Sounds all fancy and formal. Right? But what I do is so so our company is called Body Knoll.

[00:04:06] - [Speaker 1]
So we are the largest franchisee of a restaurant called Hardee's. It's a fast food restaurant. You've if you're on the West Coast, you've it's called Carl's Jr. Okay? So, but on the East Coast, it's Hardee's.

[00:04:17] - [Speaker 1]
And little fun fact, our founder created, the second ever first second ever Hardee's that would be created. So him and mister Hardee went together and built a Hardee's in near our hometown, and and we've been in business now for sixty plus years. Family run business, and I've been with him for the last ten. And part of my job is is analytics, and part of my job is to figure out where and when we can make money.

[00:04:43] - [Speaker 0]
I absolutely love this story. A sixty year old family business, you know, and being transformed by technology, continuously adapting. And just to bring to life what you do here as well, 40,000,000 transactional records every single day across 326 restaurants. So when you're working at that kind of scale, what what is the biggest challenge? Is it speed, accuracy, forecasting, or or or making sense of that volume?

[00:05:06] - [Speaker 1]
Well, in a in a a shameless plug here, SAS has made that, super, super easy. So let's go back. Right? Let's go before that. Before that, you're talking about summarized data coming in.

[00:05:20] - [Speaker 1]
So we're not talking 40,000,000 records now. We're talking very little because it's being summarized through, back in the day, Cobalt and all kinds of coding. Right? And, so now we fast forward to now, and and you take SAS, and and you now you start saying, hey. What if?

[00:05:36] - [Speaker 1]
And the what if becomes, why don't we do it? Yeah. Right? Instead of what if, it's like, let's just do it. So speed and all that has been kinda pushed out the window, thanks to SaaS and thanks to other measures we take.

[00:05:49] - [Speaker 1]
That 40,000,000 continues to grow, by the way. So now we're pulling in stuff from outside of registers. We're pulling in Workday information. We're pulling in lots of stuff and marrying all that together. So when it comes to what we're doing, we're using it in so many different places, and and that's probably what I get so excited to talk about.

[00:06:07] - [Speaker 1]
So if you have any questions about that coming up, I'm sure you do. So we'll I won't spill all of that right now. How about that? Yeah. How about that?

[00:06:13] - [Speaker 0]
So before adopting SaaS then, much of the business traditionally, obviously, relied on spreadsheets, manual reporting, etcetera. So what was the real operational cost of always looking back instead of having that real time visibility that you have now?

[00:06:27] - [Speaker 1]
I don't know if that's I mean, I don't wanna say it's not calculable, but I I think that's tough to say because we were so worried about the present. And, also, let's let's just level it out. We didn't have to deal with COVID.

[00:06:39] - [Speaker 0]
Yeah.

[00:06:40] - [Speaker 1]
Right? So COVID really changed the world. And and I know that's a cliche thing, and we hear that a lot. But for us, being a family run company, which now is getting ready to enter a third generation family running the business, gut feel was I mean, that's a normal thing, and and and we can't hide from that. And I always say even even in our everyday life, gut feel creeps up on us and gets us in trouble.

[00:07:03] - [Speaker 1]
But gut feel and and to be fair, it worked. I mean, he was successful. And and he has no reason not he has no reason not to say gut feel didn't work. But we didn't know what we didn't know then. And and the cost of that, I believe, was probably astronomical.

[00:07:22] - [Speaker 1]
What could we have been would be the question. Right? Not not what we've become. It's hard to measure, to be honest with you. So yeah.

[00:07:31] - [Speaker 1]
And one of things I

[00:07:32] - [Speaker 0]
love doing on this podcast as well is although it's technology, focus, I love focusing on problems that technologies help solve. And one of the strongest examples I was reading about is when you were trying to extend breakfast hours where your instinct said one thing, but data said the other. So walk me through that moment and and what you taught the business about trusting analytics over that gut feeling you just mentioned. I

[00:07:53] - [Speaker 1]
call it my first real win. It was my first real getting my foot in the door with trusting analytics. So so even at the time, I was just considered a financial analyst. I wasn't even anywhere near it, but but but the the story is, you know, the franchisor we're a franchisee. Franchisor said, hey.

[00:08:10] - [Speaker 1]
We wanna extend breakfast, and and we don't know how long yet, but we wanna push that time frame. We typically end at 10:30. We may wanna go to one. That was the first conversation. Our people said no chance because, operationally, it's gonna be a nightmare.

[00:08:25] - [Speaker 1]
We gotta cook burgers on one side. We've gotta cook eggs and stuff on the other side, and we're now we're talking lots of problems. So we gotta figure all that out. So it was back and forth, back and forth. Ultimately, franchisors said, hey.

[00:08:38] - [Speaker 1]
Just test it, please. Okay. So we tested it. And if we if we'd have been back pre SaaS, we'd have never done it, and here's why. So all of that data that's coming in at a at a summarized level are by extending breakfast a little further, that's now considered lunch.

[00:08:58] - [Speaker 1]
Okay? So so from a summary data, lunch, it was all buried in lunch. So lunch was four hours, but the first hour was now breakfast foods, possibly. Really? Right.

[00:09:09] - [Speaker 1]
And for us, historically, breakfast foods have very low has very high margins, low food cost margin for us, so we we make money off of it very well. So when it first started, all we heard was, even when they did it, it's too complicated. I step in the picture and say, let me show you what's happening during that hour. And we were growing at 30 to 40 to 50% every day at every location in that hour, just in one hour. Wow.

[00:09:36] - [Speaker 1]
So the question the the conversation very quickly became, we're gonna keep doing this. Yeah. So then the question became, do we go to one? And data quickly said no. That consumers started cutting off around 12:30, and they didn't go to one.

[00:09:51] - [Speaker 1]
Wow. So we planned and said, okay. We'll cut it at twelve and have enough product carry over to 12:30. But without data, we'd have killed it. We'd have killed it.

[00:10:00] - [Speaker 1]
Gut would have killed it instantly.

[00:10:02] - [Speaker 0]
It's such a great story, and I think we should highlight as well. In the fast food industry, a few seconds at the drive through can make a major difference to customer satisfaction and revenue. So how has analytics helped improve speed, throughput, and overall customer experience? What kind of transformation have you experienced?

[00:10:18] - [Speaker 1]
So from from a drive through standpoint, we measure lots of things. Right? So now we can talk about things like time motion studies, like how long does it take to make us a biscuit versus how long does it take to make a hamburger versus how long does it take to make a chicken sandwich? And Yeah. And those time motion studies help us now calculate labor better, know when to get labor efficiency better, which always helps us improve drive through service.

[00:10:42] - [Speaker 1]
So so even backing up, knowing how much food to prep and have on hand and and all of that stuff is just built off data. All of that stuff ultimately turns into seconds Yeah. And helps that customer get through that drive through quicker. We have other outside companies who measure customer experience for us, and we get all that data and pull that in too. But, ultimately, it all starts there at that restaurant.

[00:11:03] - [Speaker 1]
You know? And how can data and analytics serve them so we can serve the guests better?

[00:11:09] - [Speaker 0]
I was also reading that you've used data to optimize staffing and payroll by the hour, even down to understanding late night labor inefficiencies. So how do you balance operational efficiency with maintaining strong employee experience as well.

[00:11:23] - [Speaker 1]
So what you're talking about is the thing I'm most proud of. Okay? And I hate I hate saying that out loud, but I am. Because prior to my prior to me coming into Body and Know, was a ten years, I was a tax accountant. Super exciting.

[00:11:38] - [Speaker 1]
And, but I will tell you from an analytics standpoint, it is the backbone of of that that p and l statement, understanding profit and loss, understanding what goes in and goes out of it, I think, is core to understanding how businesses run, where money comes in, where money goes out, where you may be losing money. Right? So from a data standpoint, it's helped me a lot understand that. But my ultimate goal was always I would I've always wanted a p and l by hour for every single store for every single day, and we've accomplished that. Thanks to help with SaaS, and and and, we have a consultant called First Analytics.

[00:12:14] - [Speaker 1]
I always like to give them a plug because they do an amazing job with us. But so every store at every at every location, I can tell you in any hour where you've you either, a, made money or lose money. So it's helped us become more agile. From an employee standpoint, you just have to be able to maximize staffing the best you can. So, unfortunately, sometimes that may not I mean, sometimes there is gonna be some winners and losers in that, and that's just, unfortunately, I think, the nature of the beast.

[00:12:41] - [Speaker 1]
Right? Yeah. Right. So, so the goal there is to how do you get them more hours maybe in the morning, where we can use better labor in the morning to cover our our better margins. We can we can afford it better there.

[00:12:54] - [Speaker 1]
So you just have to be creative when it comes to that. So

[00:12:58] - [Speaker 0]
And another big change the company's seen over the last sixty years is the arrival of delivery platforms like DoorDash. Uber Eats changed customer behavior completely. Yes. It is. What did the data reveal about how delivery customers behave differently from those in store customers, and how did that reshape

[00:13:15] - [Speaker 1]
the strategy? For us, with delivery, we were not that we were not going in delivery, COVID forced us into delivery. Right? It forced a lot of people in delivery because people weren't going going nowhere, so we had to hurry up and rush. Looking back, you know, we didn't have a choice, but we, you know, we made some mistakes, obviously, but we've learned from those.

[00:13:33] - [Speaker 1]
But from a delivery standpoint, it's still mind blowing to me that they're willing to pay

[00:13:38] - [Speaker 0]
Yeah.

[00:13:38] - [Speaker 1]
For that service. Yeah. You know? And and we've probably all been in that situation where we are willing to pay for that service, and I get it. But that delivery customer and the traditional customer are not the same customer.

[00:13:50] - [Speaker 1]
They're that they can't be because the the average check is so much higher in a restaurant for a like, a traditional customer, let's just say, spends $9. A delivery customer spending anywhere from 15 to $18, and it's not even close. Like, they they don't seem to mind. So I think we're dealing with two different we are we know we're dealing with two different customers, and and and it's probably two different age groups and demographics as well. So

[00:14:16] - [Speaker 0]
Wow. Wow. Incredible. And you've also mentioned forecasting accuracy improving to within just naught point 1% in your first quarter using SAS Visual Forecasting. So but without questioning, mean, for business leaders that are listening, what does that level of forecasting precision actually unlock for an organization?

[00:14:34] - [Speaker 0]
And, also, what would you say to those people listening that are thinking, hang on a minute. That number can't be right.

[00:14:38] - [Speaker 1]
Okay. So I hear this a lot. That's okay. I'm good with this. For us, that it was our so, again, we partnered with First Analytics, big partner, big helper there to get us get us off the ground and get us running.

[00:14:49] - [Speaker 1]
And that first year, you you just referenced first quarter. Yeah. We finished the year at point eight for the whole year. Right? We missed our forecast by point eight.

[00:14:59] - [Speaker 1]
That is on roughly a half $1,000,000,000 in sales. We missed by point eight. And when I talk about unlocking big wins for me, it unlocked massive wins for me and getting my foot in the door in a lot of other conversations. How that's helped us is now we plan better. Right?

[00:15:13] - [Speaker 1]
Now we know if we can get a forecast I'm not saying it's gonna be that accurate all the time. For context, last year's forecast missed by just a little over a percent. I'm super happy with that too. Right? And a lot of people would be.

[00:15:26] - [Speaker 1]
Of course. So, kudos to SaaS. Kudos to First Analytics for a big help. But it unlocks a lot of potential for us to know what kind of year we're expecting and how to proceed with our operations team. Because in today's economy and in today's environment, as we're all aware, it's tough.

[00:15:44] - [Speaker 1]
Mhmm. It's very tough. And and we're dealing with a lot of factors. Our our the second generation who runs the company now said it best, we've never seen times like this, where everything is hitting us from every angle. Right?

[00:15:57] - [Speaker 1]
We're we're talking weight loss drugs. Yeah. We're talking now gasoline prices. We're talking the the inflation. We're talk we're just talking everything, wars, and and and we're having to fight so many battles that we've never had to fight.

[00:16:09] - [Speaker 1]
Yeah. So if we can get a forecast accurately that accurate, we know how to plan. And if we know how to plan, then we know how to be adapted. We we can react. We we can prepare instead of having to be reactive.

[00:16:20] - [Speaker 1]
We we can prepare and try to move forward with our plan. So

[00:16:24] - [Speaker 0]
And from the outside looking in, another thing that stands out on your story is data democratization, giving nontechnical teams access to dashboards and insights. How important was that to making analytics, accessible beyond just the data team and into everyday decision making?

[00:16:40] - [Speaker 1]
Yes. So so, again, we were a very paper driven company. I think a lot of places were, and they still are, and that's probably a big hurdle. I was not. I'm a big fan of of it's gotta be in your hand.

[00:16:51] - [Speaker 1]
It's got we all walk around holding a phone. Technology is key. Right? So why not? So my goal was always to put it in their hand, put it in their face, make them see it, make it visible, make it easy to understand.

[00:17:02] - [Speaker 1]
So we we're very big into stoplighting, red, green, yellow. So green, you're great. Yellow, caution. Red, we got problems. So instead of focusing on a number, I need you to focus on color, and let's start identifying problems quickly.

[00:17:15] - [Speaker 1]
Yeah.

[00:17:15] - [Speaker 0]
How did AI or how has AI transformed things for you?

[00:17:18] - [Speaker 1]
So for us, it's two things. Okay? One, we haven't seen yet, and I'm super excited about it. We started the conference here, and I'm super excited. I'll save that one for last.

[00:17:27] - [Speaker 1]
What we've seen at the beginning, what we're doing is we we've again, with first our first analytics, we've helped create, basically a mentor, call it. It's kind of our AI mentor for our restaurant managers. So thanks to COVID, turnover has been through the roof. Yeah. A lot of people are seeing that.

[00:17:44] - [Speaker 1]
So we lost a lot of seasoned managers who just either retired, health reasons got out. What we learned was we've gotta get these new managers up to speed quick because we just lost thirty years of knowledge. Right? So we've partnered with with, like, First Analytics, and we're taking AI. We our goal was to always make it an extension of your hand, not to be not to be cumbersome and and and more work, but every day, it tells them how their day is, what they need to plan for, where their opportunities are, what they need to focus on for the day, and it's built location by location specific.

[00:18:21] - [Speaker 1]
And it helps highlight opportunities, helps highlight where they're doing well, give them a shout out where they're doing well, also where they need improvement. So that's a big game changer for us, because we can now take a brand new manager and kinda throw them in that role. And hopefully, with the help of AI, they can start getting up to speed a lot quicker. Right? Instead of having that wheels and everything's crazy because these things don't you know, it's chaos.

[00:18:45] - [Speaker 1]
Now, hopefully, in their hand, they can focus on what they need to focus on. Now with what we've seen at Innovate and what we're excited about is now I can take the hope is and the the plan is in the future, these dashboards and all these things I've created, layer in Copilot. And now these nontechnical, nonanalyst people can now ask Copilot, hey. Can you help explain? Yeah.

[00:19:07] - [Speaker 1]
Right? Because while I understand it, you understand it. I've got people I just need you to run restaurants, but I also need you to understand the business side. So if you can have Copilot help explain what does this mean, and how does it affect me, let's say, and it can go through that and give them a nice example, I think that'll change the game for them and help them unlock things quicker without having them having to be an analyst. Right?

[00:19:29] - [Speaker 1]
So you just kinda get them ready. That's all.

[00:19:31] - [Speaker 0]
Yeah. I was gonna say the word game changer is often overused, but this really does feel like that moment.

[00:19:35] - [Speaker 1]
It does.

[00:19:36] - [Speaker 0]
When you got people running restaurants, the last thing that they care about is technology, AI, and code fires.

[00:19:41] - [Speaker 1]
Because they got so many fires to put out. Right? Yeah. Yeah. Giving them that

[00:19:45] - [Speaker 0]
interface where they can just ask you questions, and it's something that we all use in our Correct. Store

[00:19:49] - [Speaker 1]
line. It's it's an extension of your hand as well. That's why I say I like to say that. Yeah.

[00:19:52] - [Speaker 0]
But have you had any resistance or push back or people

[00:19:56] - [Speaker 1]
Surprisingly, no. Yeah. I think they're desperate for it because they use it every day. Yeah. So why would you not want it?

[00:20:04] - [Speaker 1]
And now granted, at the very beginning, it was the, are you taking my job? Yeah. No. We're just trying to enhance your job. So I always reference AI as simply it's like that seasoned, consultant that you've got at your hand, that you can just talk to whenever you need to talk to, and that's how I try to view it.

[00:20:21] - [Speaker 1]
It's not a job replacer. You you know, Brian made a good point this morning yesterday morning, which is we still need people. And he's right. We we do. And and and that's where if we can use people in a, it's a game changer, to your point.

[00:20:35] - [Speaker 1]
Yeah.

[00:20:36] - [Speaker 0]
And I I hope this is correct, but I was reading this. You got 38 district managers, hundreds of restaurants, and with that alone, consistency must be a constant challenge. So how does analytics help those local managers make better decisions while still protecting the brand standards across the business.

[00:20:52] - [Speaker 1]
Right. So it's actually 48.

[00:20:53] - [Speaker 0]
Is it

[00:20:54] - [Speaker 1]
48? It's 48. That's right.

[00:20:55] - [Speaker 0]
It's suck my research.

[00:20:56] - [Speaker 1]
It's okay. It's alright. You can blame me. It's in that article, I think, actually. Yes.

[00:21:00] - [Speaker 1]
We kinda missed it. But no. Analytics is a it's been a struggle. Just again, we've been trying to get off paper.

[00:21:07] - [Speaker 0]
Yeah.

[00:21:08] - [Speaker 1]
So once I've got them to understand things, consistency has been everybody's seeing the same dashboard, everybody's seeing the same dataset. The other thing we did too was instead of you just getting your stuff, now you have access to everybody's. Because I want you to understand how other people in in our company's doing who are running similar restaurants to you. So the, hey, by the way, reach out to them and get help. Yeah.

[00:21:32] - [Speaker 1]
And say, what are you doing? How are you doing? Or can I help you? Right? So the consistency side, while struggle, has slowly become better because we're getting them more and more used to understanding what these dashboards are saying, which is why Copilot, I think, will be that game changer that we just talked about.

[00:21:49] - [Speaker 1]
So

[00:21:50] - [Speaker 0]
And I suspect many customers or most customers, they don't care about the dashboards. They just want their hot food quickly and correctly. So how do you translate all that data and AI into something that the customers actually feel without them even knowing that there's any technology behind it? I would imagine that's quite a tricky balance too.

[00:22:06] - [Speaker 1]
It is. I I think the key is, you said it, they don't need to know it's there Yeah. Which which gets back to and I and I and I will I will call out another brand, and I apologize, but they're doing a great job right now, which is Burger King. So if if you know very anything about them right now, they're going through a massive transformation. And and what they're doing is they've leveraged every bit of technology they can, but what they went back to is the basic set the basics of quality, service, and clean.

[00:22:33] - [Speaker 1]
Mhmm. And and I think that's where you win. Now data can help tell you the quality of the service and the clean, so that's where the background data says, where the customer just sees, was the food good, was my service great, and was the place clean? And I think that's the basics of what you have to get back to, and and I think that's what the customer will see if data can help get you there. So

[00:22:53] - [Speaker 0]
And for yourself, obviously, here at SAS Innovate, what have you been up to? Have you been speaking, meeting people? What have been up to?

[00:22:59] - [Speaker 1]
Yes. I get, I get used a lot, and I enjoy it a lot. This is this is a lot of fun. It's I kinda call it my Super Bowl. Yeah.

[00:23:07] - [Speaker 1]
How about that? So I get to talk to wonderful people like you. So this is a a wonderful highlight. But, no, I I I've had a lot of fun. This is my fifth or sixth Innovate, and I've had a lot of fun and seen a lot of great sessions, seen a lot of fun stuff, done a lot of presentations, got to play Family Feud earlier this morning.

[00:23:24] - [Speaker 1]
So I've had a lot of fun. Yeah. Of course. I I highly recommend to anybody who wants to come. So.

[00:23:28] - [Speaker 0]
And a moment ago well, before we started recording, you were just, checking in on your flight.

[00:23:32] - [Speaker 1]
Yeah. Gary, that's right. Thanks. When

[00:23:34] - [Speaker 0]
you get on that flight Yeah. What you're gonna be reflecting on when you put in all the announcements, all the conversations, everything that you've done here, what are gonna be thinking about on that plane home?

[00:23:43] - [Speaker 1]
Can't wait to get Copilot in our hands Yeah. Because my team has been itching for that, and and I have an exceptional dashboard creator, especially one out his name's Alex. He does an exceptional job for me. But to give him that, man, he he will grow leaps and bounds, and I'm excited for him for that, because I think that's that's the goal as a leader, is to grow those people underneath you. Right?

[00:24:04] - [Speaker 1]
And and just to keep building into them, and our our company's our company's motto and values are we believe in people. And I think I think with Copilot, with him, I'm I believe he will be exceptional and grow and and do wonderful things for us. So, yeah, we're excited. I'm excited about that. I can't speak enough on that.

[00:24:22] - [Speaker 1]
So

[00:24:22] - [Speaker 0]
Sounds like we need to pencil in another chat for exactly twelve months.

[00:24:25] - [Speaker 1]
Let's do that. Yeah. Let's definitely do that. We can do it whenever you want, but sounds like you're busy all the time.

[00:24:30] - [Speaker 0]
No. We'll definitely make something like that happen, and I'll I'll put details to your LinkedIn post to your link. Anyway else you'd like me to point everyone listening that are interested in carrying on that conversation and finding out more about you?

[00:24:41] - [Speaker 1]
LinkedIn's fine. You can reach out there, and we can have a conversation. That'd be great.

[00:24:45] - [Speaker 0]
Yep. Well, awesome. Well, I'll have links to everything. I appreciate how busy you are, so thank you so much for taking the time and sit down. Thank you.

[00:24:51] - [Speaker 1]
Thank you so much.

[00:24:52] - [Speaker 0]
Wow. What I loved about this conversation, not only was my guest an incredibly cool guy, it's also just how grounded it was in reality. There was no hype here today. Just a very clear view of how data and analytics can transform a business when applied to the right problems. Whether that is identifying profitable hours down to the minute, improving forecasting accuracy across a half billion dollar operation, or helping new managers get up to speed faster with AI as a support system.

[00:25:24] - [Speaker 0]
Everything tied back to tangible business impacts. And I think this highlighted something that often gets overlooked too. Customers, they don't care about dashboards or AI models. They care about getting their food quickly, accurately, and consistently. And the role of technology is to make that experience better without even being seen.

[00:25:47] - [Speaker 0]
It needs to be invisible and feel seamless. And this is where the real value lies, using data to quietly improve operations behind the scenes while delivering a seamless experience out front. And as always, I'll include links in the show notes so you can connect with David and learn more about the work that they're doing. But I'm curious. What are the biggest real world impact stories from AI and analytics in your business today?

[00:26:14] - [Speaker 0]
And are you measuring it in a way that actually matters? Techtalksnetwork.com. Please drop by. Let me know. Love to hear from you.

[00:26:23] - [Speaker 0]
But that's it for today. Time for me to return to the show floor now and get more stories like this. Well, thank you for listening as always, and I'll speak with you again tomorrow. Bye for now.