Motley Fool Money - Emergency Pizza, Stat!
Episode Date: October 12, 2023It’s hard to bet against the enduring appeal of everyone’s favorite dinner. (00:21) Bill Barker and Deidre Woollard discuss: - How Domino’s continues to compete for its share of stomach. - The i...mportance of loyalty programs and the worry of loyalty fatigue. - If Walgreens’s new CEO will keep steering the company toward healthcare. (17:21) Deidre Woollard interviews Professor Michael Robbins on his new book Quantitative Asset Management and the future of AI in investing. Claim your five dividend recommendations here: www.fool.com/dividends. Companies discussed: DPZ, WBA, WMT, AMZN, UBER Host: Deidre Woollard Guests: Bill Barker, Michael Robbins Producer: Ricky Mulvey Engineers: Dan Boyd, Annie Pope Learn more about your ad choices. Visit megaphone.fm/adchoices
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Pizza is ready. Motley Full Money starts now. Welcome to Motley Full Money. I'm Deidro Willard
here with Motley Fool analyst, Bill. How are you doing today? Good. Thanks for asking.
Well, Bill, earning season is starting to kick in. I'm sort of stealing myself for the onslaught
of three, four, five, ten companies a day. How do you deal with that tight of information?
You know, I tend to focus on what's in the headlines to a very limited extent.
and the specific companies that I'm most responsible for following as an analyst here at greater
detail, it's the best time.
That's the most real information.
So I don't mind it.
I love it.
It's the best time.
Yes.
Well, we've got some earnings today to talk about.
Let's talk first about Domino's pizza.
Same store sales down a little bit, but Domino's is interesting to me, because I think people think
of it as, you know, it's selling pizza, and of course, it's selling pizza. But that's
really part of the puzzle when you think about the business, because it's a franchise business.
It's definitely a selling supplies business. What metrics are important with Domino's beyond
just like they're selling more pizza?
Well, boy, that is a big one.
It's a big one.
It's a very big one. Beyond that, sort of what the store count is, the new store
account, year to year, what the cash on cash return.
are per store and per new store, are they cannibalizing any of the existing stores?
I think that it's a relatively easy business to follow because it's got a simpler business
plan than many others. Despite the franchise fees and all that, it's about how many pizzas
they can sell more than anything else. They've expanded the menu beyond pizza.
That helps at the margins, but the core business hasn't changed too terribly much.
No, it is still all about the pizza.
One of the things that's interesting, though, is they are investing heavily in technology.
They're partnering with Microsoft, and they are passing some of that cost on to the franchisees for things like the app.
How much are the sort of collaborations that they're doing?
Like, they're each thing, how much are you factoring that into looking at the business as a whole?
Well, Uber Eats collaboration is interesting.
Domino's is still doing the deliveries, and so they're just visible on the Uber Eats app.
They've already got a very well-developed online presence and have for years, and that's been one of the big contributors to their success.
So they're just expanding into Uber Eats in the sense that people see them there rather than their own ads.
There are people who will only order from Uber Eats right now.
That's how they just choose to get their food delivered.
They probably don't realize it's Domino's that's delivering rather than Uber.
So over time, and this is going to be, I think, a market rollout initially, and then
it's going to expand from there, potentially quite a bit of additional business for Domino's
with relatively little.
investment, but it'll cut into the margins.
But no, the investment is definitely happening on their app and driving their customer loyalty
and improving things on that end as far as the technology goes.
Yeah, they want people to order from them rather than through Uber Eats.
They don't want to split the profits with Uber Eats if they don't have to.
So making additions to the loyalty program, getting people to come back directly to them,
just as a hotel would rather have you book directly at their site rather than through Expedia
or Hotels.com or any of the other ways that you can get the same thing.
But, you know, Expedia or all the intermediaries have their loyalty programs,
and the hotels have their loyalty programs.
It's the same dynamic here, where Domino's wants to develop the app experience and the online experience
as well as it can, so that it is not, so that it's getting all of the, you know, money that it can
from the sale. It's the same endpoint work that they've got to do. Yeah. Let's talk a little bit
about the loyalty program. They announced something earlier this week, a PR-driven story, but
really made me think about their loyalty program. So they launched this thing where they call it, like,
a free emergency pizza. Well, it's really just buy one, get one later, but they kind of, you know,
they call it an emergency pizza. That sounds kind of funny. It got a lot of headlines.
But the other part of that story, too, is they've also lowered the barrier to entry for the program.
You can, you know, so they're really trying to get that loyalty program going.
They're trying to make sure that people become part of that. You know, you just made a good point about Uber,
because, of course, Uber has, you know, they have their memberships and their loyalty programs.
So I'm wondering when do you think that the loyalty program is going to grow with Domino's, does this have to become part of the,
the system and overall, like, how much do factor loyalty programs into thinking about the value of the
business?
Well, it shows up in the numbers. It shows up in the margins.
So I think that giving, you know, buy one, get one later, pizza getting a little bit of advertising
coverage for that is all to its benefit.
And I think that everybody out there, grocery stores, you know, the little discount,
you get by joining their loyalty programs. Certainly the airlines are people who become
quasi addicted to the miles, the points, the free stuff they can get at the margins. And so the
more that you make people think, and part of the equation, making people think they're getting
a value, extra rewards from being in the loyalty program, is to create real rewards.
and Domino's. It's easy. You get a free pizza rather than you get access to the airport lounge
or something like that. But the emergency pizza, I guess, offers some interesting advertising
possibilities that I can think of.
Yeah. I do wonder if there's going to be loyalty program fatigue, though.
I mean, for some things, like airlines, of course, you're a member of those. It just makes
sense. I think everybody I know is a Starbucks reward, you know, go and you get your coffee
eventually. Sometimes you get free one. That's a good thing. But eventually, do people get sick
of managing all of these different rewards? And does that lead us more toward that idea of
a super app where things sort of get consolidated? I always feel like we go through these cycles
of consolidation and then unbundling and then consolidating again.
A super app for all rewards?
For all rewards? Hey, maybe for all food.
Has somebody tried that yet?
I mean, it's not yet. Maybe they should.
To a certain degree, it's meant to be your phone so that you don't have to remember all the things.
You don't carry a card with you that you pull out at checkout at every establishment,
that it can just live on your phone.
So that, I suppose, is the solution to the too many loyalty rewards.
programs and numbers that you would have to remember and cards that you would have to carry.
Yeah. That makes sense. They should just put it in the iPhone wallet. One more thing about
Domino's. When people talk about the company, they worry about the debt a little bit. I mean,
you have $5 billion in debt here. That's a lot of pizza. How should investors be thinking
about that debt?
Well, I think that it is a lot of debt. I think that's a fair thing to look at. It has worked
out to the benefit of shareholders because debt has been relatively cheap. So the debt, you know,
before the last 18 months, was an extremely good way to fund growth compared to issuing more
equity. So I don't blame them for that. Then they have a target, I think it's, you know,
four to six times Ivetah or something like that on the debt.
So as long as they're maintaining and they are what their target range for the debt is,
I think that you can look at how that translates into additional profits for the company through the growth.
But if debt becomes more and more expensive,
and they don't have that much debt to pay off in the next three years,
so no one should worry about whether they would run into any,
serious financial trouble. And, of course, the business is very predictable. The cash flow appears
every day. People eat every day. So it's a business that can maintain more debt because of the
predictability of the cash flows. But it's a lot of debt for a company this size.
Yeah, yeah. But the fact that it's not coming to anytime soon is at least a little bit of a
comfort, I guess. Yeah. Hopefully, from everybody's perspective, it will be cheaper to borrow in the future
than it is today. Homeowners and businesses and everybody, except people who have savings and bank
accounts, they don't mind higher interest rates, but everybody else is pretty much hoping in the
future is cheaper. And if it is, the domino's debt will be less of a problem than if it gets to be
more expensive.
Oh, God, I hope.
Math. That is, in fact, math. Let's talk about another company that reported today. You and I were on
the Motleyful Morning Show for our membership yesterday. We talked a little bit about Walgreens Boots Alliance,
because they announced a new CEO, Tim Wentworth, who has a strong healthcare background.
And Walgreens is interesting. It is really moving into that healthcare business. They're growing
that mostly through acquisition, but debt is a factor here. It's costing them a lot of money.
Looking at this company, when you see a company in general in the midst of this real change in focus,
how do you assess the value of the long-term strategy, especially when it's an older company like this?
Well, I assess it in the numbers and what management says about the strategy,
and they may have heard the conference call today.
This was the first chance from the new CEO to talk about whether there are any changes.
in the pace of the rollout or the use of funds to acquire rather than to do something a smaller
scale within the stores. So, you know, so far it has not worked out terribly well for shareholders.
And I think that the transition to a CEO with more healthcare background, particularly in the
PBM space, is good because that's a big part of,
Walgreens money is negotiating and managing the PBM relationships and surviving them.
And so somebody who knows where the bodies are buried is going to be useful.
Yeah, yeah.
You know, the results came in below estimates.
I mean, part of that is just, you know, less COVID vaccines, less COVID testing.
But even though the results came in below estimates, the stock was up,
I think some of that is sort of that new CEO bounce, maybe a little bit of hope that they're going to have a new strategy,
or just the idea that after six weeks of an interim CEO, at least, you know, there seems to be a plan forward.
You think that might be what's causing a little bit of that?
I'd have to guess, having not heard the conference call that something in there was useful.
I think that the stock is down so much this year that simply not delivering bad news,
or news as bad as it might have been, especially after the CEO abruptly left.
There might be questions about whether another shoe is going to drop.
So with a stock down 30-some percent this year, today's report had an easy act to follow.
Now, a lot of the time, somebody new to the equation will come in, and I don't think
that there's been time to do this, just dump a whole.
lot of things, the big bath theory of getting all the bad news out right away.
And as I get, that's none of that's my fault.
So we'll just take a bunch of write downs and we'll just, you know, put all of the losses
in a big bucket and therefore they don't count.
So I don't think there was time to do that for this report.
So the miss on top line, small as it was,
I think market just is taking a sigh of relief, I think, that there isn't any particularly
bad news this time.
Yeah, and they did talk a little bit in the release about cutting costs, and I think the
market wants to see that.
They've seen a lot of acquisitions, and now they want to see this cost cutting.
They want to see sort of finding where they can make some savings.
But you're right.
It hasn't performed well over the past few years.
a tough business for pharmacy overall, because now you've got Walmart, you know, Amazon, Costco,
everybody's getting into the pharmacy game. And I'm wondering if Walgreens kind of has to make
this payoff in order to survive, because really these businesses are moving from being, you know,
retail essentially to now being retail and increasingly healthcare and services.
Maybe so. It is a problem that you're traditional.
business, which has worked very well and has allowed you to grow a lot, is being now
attacked by Walmart, Amazon, and Costco. That's a lot. That's a lot to deal with. And so they've got to
have some strategy for what that world is going to continue to look like. And the one that they
have gone with has not translated into profits yet. But they're
in a good space, their trusted healthcare name more so than those others.
And there's an opportunity there, but large drugstore chains don't survive just because
they get large.
Yeah, very true.
I mean, we're betting on the demographics of the aging of America with this one.
All right, Bill.
I'm going to wrap up with a silly question.
What's your pizza order?
My pizza order usually involves a lot of meat for pizza.
What are you?
Like a sausage and a pepperoni guy?
Something like that.
Yeah.
Whatever's available.
Yeah.
And yours?
I'm a pineapple person.
I don't know about that.
Thanks for your time today, Bill.
Thank you.
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Let's start at the beginning. Quantitative asset management. People have probably heard it said a lot, but not necessarily understand.
exactly what it is and how it differs from other investing approaches?
Yeah, it's in the news a lot lately. And in fact, I think most investors now are quantitative
in one way or another. But people, I think, misunderstand the purpose of it and think it's about
coming up with a number, a scale, a metric to judge a trade, when really it's about the
process of thinking through the trade in a discipline, structured way, which I think works
for everyone, even people who aren't great at math.
That would be me. Your book focuses on a lot of different types of modeling. So how can a
qualitative investor, like me, get a better understanding of some of the models used in
quantitative analysis and get a little more comfortable with some of those numbers?
Well, there's lots of great information out there. And a lot of these models are accessible
to people without a lot of knowledge, although it's a little dangerous to use a powerful tool
without a good understanding.
But some of these tutorials are really intuitive and interesting.
So you can think of, for instance, a linear regression as a way to put a line on a chart
full of dots, so the line is as close to as many dots as possible.
And the way they do that is they measure the distance between the dots and the line
and try to make the sum of those distances small.
In fact, the real way they do is they take the square of those distances.
A lot of the other more powerful machine learning methods are based on that sort of thing.
They might use a different way to measure things or a different kind of line.
Or maybe they use that line to divide two different types of dots instead of trying to find
a line that's closest to fit them all.
And that's a second type of problem called classification.
So even in this short discussion, this simple analysis, we saw the two major types of quantitative
analysis, regressions, and classification. So it can be intuitive. And a lot of videos show this
graphically with all sorts of colors and moving graphics. And I think it's pretty accessible for a lot of
people. But then these much more complicated models, the ones that people are so excited about
lately, like the large language models, they're harder to grasp. It's harder to get a true
understanding of those things. It's a little like quantum physics. Once you move out of the
realm of what you're used to and the intuition about the world around you and things become
abstract, it's hard to get a really good understanding to be able to use those tools properly.
Yeah, that's an interesting point you made about the difference between intuition, because so
much of qualitative investing is thinking about what you feel about a company, what you know,
listening to the earnings calls. You look at the numbers too, but you also are going on a lot
of intuition, whereas quantitative is really different from that. So thinking about modeling in general,
what are the limitations of it? And when maybe should we put the modeling to the side and go a
little more on the intuition? Yeah, that's a really great question. And there's a lot packed into
that. But all models are limited, almost by definition. It's just prohibitively difficult to build a
a model complex enough to take everything into account. So an important feature of quantitative
investing is if you do your testing, you run a bunch of experiments and you know what you've
tested and what you haven't. You have that envelope, that parameter that you're comfortable in.
You know you've tested these things and you're pretty reasonably sure that you understand
what's going on. In quantitative investing, it's pretty clear what you don't know. You may be right,
you may be wrong, but if you haven't tested it before, you really don't know. And that's a great feature
in a way of thinking. If you're qualitative, if you're intuitive, it could be very powerful,
but you're also always a little unsure and sometimes more unsure than others. And a lot of times
your mind plays tricks on you, and your comfort level informs you of how much you believe in something.
So if you're comfortable with a situation, you have the intuition that you know what's going on,
and that's not at all necessarily true. With quantitative investing, you know exactly the
limits of your knowledge. And importantly, when you're trading, you should have an investment
thesis. You should have a reason for investing. And that's the difference between investing and gambling.
And when that thesis is violated, when you're out of your depth, you should exit your trade, even if you're making a lot of money.
Because if you're making a lot of money, you don't know why. Maybe you'll start losing a lot of money and not know why.
The important thing is you should know why. And for me and people like me, quantitative investing gives you that comfort level, that you actually know where that barrier is.
You know what you've tested and what you haven't. And also, very importantly, and this is something maybe some amateur traders don't think.
so much about. When things don't go well, people want to force you to stop what you're doing. They get
uncomfortable. They get afraid. And it's important to be able to defend yourself and your trade.
So if you have tests, you can say, hey, look, we've experimented with this. We've seen this
in our experiments. You're uncomfortable. I get that. I understand what you're feeling. But
your feeling is not as valid as our experiments. Until you have a good reason for us to exit our
trades, we have a good reason to stay in them. Whereas if you're intuitive, your reasons might be
great, but they're a little harder to convince people of. And that may turn into someone
forcing you to exit a trade before you have to. I want to talk a little bit about AI and how it
might change the world of investing even more than it has. You mentioned earlier the large language
models. What should we be looking for? How does it impact your world? Yeah, it's already had a
tremendous impact, and it will continue to do it. But I think the story is really changing.
So machine learning and artificial intelligence are really just an evolution of statistics.
If you're in the field, you recognize that there are just maybe a more powerful way to do statistics.
Some of them are a little more removed than others.
Large language models are very different from simple linear regressions, but it is an evolution.
And it will certainly affect everything.
It's already pervasive, even if you haven't noticed it yet.
Netflix uses it to help you pick your movies.
certainly most ads you have are generated by some form of AI.
Spam filters have been using AI for decades.
So I think the fact that it's there, and you might not even notice, is a testament to its power.
But what I think is changing is that up until a little while ago, it was very hard to do those things for an amateur.
And you're pretty much limited to simple statistics.
Recently, I think many amateurs can do it.
You can download software, Psykit Learn, or Matlab has all sorts of packages.
There's lots of different ways to use AI as an amateur, either for free or very close to free.
And until a few months ago, I think they were pretty sophisticated relative to most of the other things that we've heard about in the news.
There might be some secret things going on in government laboratories and hedge funds and things.
But in terms of what was known in the public media, the free software was pretty powerful.
But that's changing.
So OpenAI is becoming not open.
There's all sorts of private models by Microsoft and all the other big companies.
I'm sure the hedge funds have all their own secrets.
At the university, I work with research partners who use these enormous computers, just the size of large buildings.
quantum computers, and all this technology that's absolutely not accessible to individuals.
So I think we're moving through a golden age of AI where amateurs can really do some very
sophisticated stuff. And this is kind of going the way of high frequency trading, where
average people just can't compete. And there'll only be a few entities with even the possibility
of competing with each other. Every once in a while, there'll be a tremendous breakthrough,
which can happen outside of those organizations.
An amateur could create a mathematical proof that just turns everything on its head.
But that's really rare and hard to do.
So I think, you know, this idea of producing alpha, this idea of outperforming the market
is going to get further and further away from the average person.
And even these little niches, these little opportunities that a lot of people don't look at
are going to be hoovered up by these machines that are so capable of doing so many
things at once. And it's a little bit dystopic, but it's kind of the way it seems to me right now.
Is there still value for people to try to learn and try to understand investing with this idea
that you've got this sort of AI threat kind of looming over us?
Well, yeah, I think there's still a lot of time before that happens from a personal standpoint.
It's not going to happen overnight, but maybe in a generation.
maybe the people in high school now won't have the opportunities we have to create investment
returns. But right now, there's a lot being left on the table. A lot of these machines are making
some very obvious mistakes. I read an article about that game Go, you know, with a little
rocks, a little board game, and someone used AI not to create a strategy that beats the game,
but to identify the weaknesses in the other AI strategy.
So it wasn't trying to find a way to win.
It was trying to find a way to expose the obvious errors the competitor was making.
So it's kind of a cat and mouse game.
And as we know from high-frequency trading, it really hasn't worked out like a lot of people
would have thought it was.
These high-frequency trading machines are not so brilliant because they're focusing
on speed.
So they do some very simple trades, but they do them very quickly.
So if you can think of something a little smarter, maybe that's another dimension where you can beat them, even though they're faster than you.
The same may be true with AI, at least for the next five or ten years.
Don't quote me on the time.
I don't know.
I'm not a futurist, but they're making plenty of mistakes now.
I mean, anybody who uses voice recognition on their phone knows how many mistakes their text messages have in them.
So there will be errors to capitalize on.
And in a lot of ways, that's easier than finding investment opportunities.
I'd rather find mistakes in an algorithm than, you know, try to find a good trade.
There's less noise and randomness in it if you can identify a pattern.
So, yeah, there are things that we can do.
It's not going to turn overnight.
Well, fantastic. Thank you.
This was great.
Really appreciate your time.
the book is quantitative asset management. As always, people on the program may have
interests in the stocks they talk about. And the Motley Fool may have formal recommendations for or
against, so don't buy ourselves stocks based solely on what you hear. I'm DeJewa Willard. Thanks for
listening. We'll see you tomorrow.
