Peloton Needs a Wizard

We also talk about big oil and chat with Tom Chivers, author of “Everything Is Predictable: How Bayesian Statistics Explain Our World.”

In this podcast, we break down Peloton‘s CEO shift and big oil’s big profits.

And Tom Chivers, author of Everything Is Predictable, explains how the Bayesian theorem underlies much of modern life and investing.

To catch full episodes of all The Motley Fool’s free podcasts, check out our podcast center. To get started investing, check out our quick-start guide to investing in stocks. A full transcript follows the video.

This video was recorded on May 02 2024.

Deidre Woollard: Can the turnaround continue when the turnaround CEO leaves? Motley Fool money starts now. Welcome to Motley Fool Money. I’m Deidre Woollard here with Motley Fool contributor Jason Hall. Jason, how’s your Thursday going?

Jason Hall: It’s going great. It is earnings seasons, so much happening. We’ve got a bit of a bombshell this morning.

Deidre Woollard: We did. Indeed, I want to bring you on to talk big oil, but before we do that, we got to talk about that bombshell. Peloton’s CEO, Barry McCarthy, he’s out. He’s leaving company after just a little over two years. It’s so interesting he was supposed to be the guy who’s going to turn it around. He’s got the Netflix credibility. I don’t know. I’m wondering what’s next. Earnings call was full around about the turnaround talk. We’re still turning around, but this turnaround is taking a lot longer than anyone thought it would.

Jason Hall: There’s no doubt about it and it certainly has gotten more complicated. Because on the surface you look at it, it feels like, hey, mission accomplished, at least a big part of the mission of turning the company around getting its financial house in order trying to right-size operations. They touted being free cash-flow positive this quarter. But man, the more I’ve been thinking about this and reading a few follow-up stories with what’s going on. Maybe the story is more complicated than we think. Here’s how I’m thinking about Deidre. Let’s start with the McCarthy story because we have two things. We have the leadership changes, that turmoil that’s happening, how that’s going to affect the business. Then we have, where are we with the turnaround story? Starting with McCarthy first, it definitely feels really sudden. Maybe it is. We don’t know all the conversations that have been happening in the boardroom in recent weeks and months. We did hear, however, that one activist investor, going back to last fall, was sending private letters to the board, agitating for McCarthy’s Ouster. I’m sure that played some role in this. McCarthy’s also 70. He’s not a young whipper-snapper. He’s been doing this for 30 years at this point. As an executive with a lot of big companies dealing with finance. I’m sure it’s been a full-contact Marathon, mixing metaphors here for him, the past couple of years. But then here’s the other part of it too. Look at the entire executive team, Deidre, these are people he brought in, almost all of them if there’s one content Executive that’s been around since before the company went public. But in terms of the people that are running the organization dealing with a finance operations, it’s a completely different groups. The culture has to be very different and their focus has to be very different than it was under the founder that McCarthy replaced. Then looking at the operations, looking at cash flows, again, you can say part of the job is done that generated free cash flow, this quarter they talked about, like that’s the expectation going forward. Then part of the question becomes, well, who’s the replacement going to be? You would think that you’d want McCarthy to hang around for a little bit longer as more than just a consultant to the business, which he’s saying he’s going to advise. You have a couple of relatively young but experienced, how do you describe them? Is it is it co interim or Interim Co CEOs, Deidre?

Deidre Woollard: Still little confused and we don’t usually get Interim Co CEOs.

Jason Hall: Right, and they are both on the board. One is the Chairperson, she’s stepping out of that role and one of their largest investors, who is one of the board members is going to be taking over as Board Chair. But it’s possible one of those may be a good fit. Karen Boone, her background, those in finance, and it seems they’re looking for like a Chief Growth Officer to be CEO. Maybe Chris Bruzzo, maybe that’s more his role he spent a lot of years as the Chief Experience Officer at EA. His entire career is marketing and brand management. I’m sure they’re going to be trying to find that person. That leads us to the next part, the turnaround.

Deidre Woollard: Well, it’s interesting because if either of them were going to be the potential CEO or co-CEO, why not just start now. I’m not sure if Peloton is looking for somebody else, someone with a McCarthy style like credibility and financial charisma, no name. That could be it too. But yeah, let’s dive into the earnings just a little bit because, they’re not bad. They’re not blowing the doors off for anything but users only down about 1%. They’ve still got 6.4 million users. There’s stuff to like here. I just don’t necessarily see that the turnaround part in terms of the growth of the business is happening.

Jason Hall: I think if we were to step back and pull turnaround out of the conversation to think about this. As a patient rushed into the ER, this is stabilization. The business is stable at this point. Year-over-year total users fell a little bit. But if you look it from the prior quarter, which was the holiday quarter, a calendar quarter, it increased a little bit and some of that’s surely seasonal. They gained some people that bought bikes or treads or whatever and became users. But then really the important user number is paid users. That number has been incredibly stable year over year. That number is not down from where it was a year ago. It’s actually up a tiny bit, and it’s up a little bit from the prior quarter too, and that number matters more. Now, subscription revenues are not necessarily growing. Again, that’s what you really want to see. It feels like, again, it’s a stable business generated about nine million dollars in positive cash flow in the quarter. Still generating really big operating losses, Deidre though. I think that’s an important thing. I started peeling back the layers a little bit and looking at that cash flow story, one thing that really stood out to me, they drew down about $75 million of inventory in the quarter. On a GAAP basis, you still recognize the margins the same way in selling those bikes and stuff is low margins. Mid-single digit margins. But you generate a lot of cash for those things because if these have been sitting in inventory for months, you’ve already paid for all the components that made it. Cash out may have happened in a prior period and the cash in, you can keep doing that. They’re going to keep drawing down inventory for a while. But at some point that inventory is going to stabilize. The question is going to be, what are the cash flows look like once that happens? That makes me say stable is one thing. Turnaround and returning to growth. That’s a very different story and that’s where I think the skill set for the next CEO is going to be important because we’re definitely going to need a wizard, right at this point.

Deidre Woollard: I think we want someone who can get away from the hardware and more into the app and things like that. Since it seems to be, to some extent that’s where things are headed.

Jason Hall: There’s no doubt about that.

Deidre Woollard: Let’s move on to big oil. We’ve got some earnings that we’ve also got some news. Exxon is set to close on that $60 billion deal to acquire Pioneer. That was announced last year, but now we have the FTC. Finally, they’ve reached a deal. This is going to happen. One person not coming along to the finish line there is Pioneer’s former CEO Scott Sheffield, but I’m curious, what does this deal going through mean for Exxon? I know it’s all about the Permian Basin.

Jason Hall: It is. It’s about the Permian. This is the massive shale play in West Texas and moves a little bit north there too. But the bottom line is that this is some of the cheapest, easiest to access oil in the world at this point. ExxonMobil already has a substantial position in the Permian. A lot of Pioneer’s plays are adjacent to that. That’s extra valuable. It’s not just getting those assets, which this is what it is. It’s an asset buy, they’re not buying Pioneer’s business, they’re buying Pioneer’s oil and gas reserves. That’s really what it comes down to. They’re going to be able to leverage that because they already have a lot of operations in that area and a lot of their contractors that they use are operating in that same area and operating on those same Pioneer fields. But the little things that they’ll be able to do, like doing longer laterals in assets they have now that now they have the pioneer assets right next door. That means less drilling activity, potentially better margins. I think some of the things they’ll do on the margins that can make this a little more profitable could be really useful. Things like only having the CEO of ExxonMobil and not Sheffield and other CEOs who is really driving out operating costs in terms of like administrative people. That’s another way that these things pay off. I think it’s just business as usual and just getting better, cheaper, more oil. That’s aligned with where a big part of ExxonMobil’s North American businesses already focused.

Deidre Woollard: Big oil is still seeing big profits and maybe not as monstrously big as over the past couple of years. Shell reported today they had 7.7 billion in profits. What’s interesting though is they’re going to put 3.5 billion into share buybacks during the next quarter. They’ve already had 13.2 billion buybacks over the last 12 months, 20% higher dividend per share than first quarter of last year. I’m wondering part of the investing thesis right now with big oil, with these profits, is it just that they’re going to be really good to shareholders as long as the profits are also equally good?

Jason Hall: I think so. Hopefully it remains this way. These are our colleague, Tyler Crowe. He and I’ve covered the oil and gas industry together for over a decade at this point and recently we were discussing, and he told me that he thinks that the US oil industry is curious over to the European majors like Shell as well. It hasn’t been this healthy in maybe 40 years, which is remarkable. It’s a product of what happened in the prior decade, really coming out of 2014. That boom when we saw oil prices skyrocket and say over $100 a barrel for almost three years and then fell to the thirties. What happened is all these oil and gas companies ended up with all of these resources that they developed, that the cost to get the oil and gas out of the ground was so much higher than the market was realizing. It gutted the industry and the companies have spent 7-8 years sweating assets, really innovating, getting better at getting oil out of the ground for a cheaper, and that’s gotten us to this point and it came to a head in the pandemic where demand crashed for a quarter and then skyrocketed, and everybody had to really get back to work to meet demand, but everybody has been more disciplined. The thing that’s tempered it now and has forced them to stay disciplined, Deidre? Is interest rates have skyrocketed. A lot of that early drive up through the early 2010s, money was cheap. Money is not cheap anymore, so they can’t just go chase growth. They actually have to be responsible allocators of capital and it seems like broadly they continue to do that with smart growth, not chasing growth, chasing cash-flow growth, buying back shares, taking whatever’s left after you meet your capital program and the repurchases that you want to do, paying in dividends and grow the dividend a little bit. Interest rates are helping us right now because they’re keeping managements from doing dumb things.

Deidre Woollard: Makes sense. The other thing that’s happening, of course, is the energy transition. Shell is to some extent a part of this. It’s interesting because shareholders see this but they wanted to go faster. There’s a shareholder proposition led by activists, shareholders follow this, which asks for it to align its medium-term carbon emissions reductions with the Paris Climate Agreement. Shell talked about this a little in their earnings, call. Their response was like, trust us, we’ve got this. But what do you make of this and other ongoing calls for big oil to pick up the pace of what they’re doing?

Jason Hall: First thing I want to be abundantly clear, I completely support anything we can do to support reduced emissions. I’ve a kid. You think about the future, and I think it’s really important that we address this massive existential risk to humanity. But I will say that when it comes to these companies, the leverage position has shifted. Back into late 2018, 2017 to 2020. There was a big push and it seemed like there was a lot of momentum on the side of activists and those pushing for these companies to reduce their emissions. It was even so big as the Rockefeller Foundation, the guy that basically created the global oil industry, the Rockefeller Foundation decided to divest itself from the oil and gas industry completely. There was a big push broadly to really coerce these companies to really focus on carbon reduction, they were struggling back then. They didn’t have a leg to stand on and say, we’re just going to keep making a lot of money because they weren’t making a lot of money. They had to count out a little bit and try to really work on these initiatives and really lead with a lot of climate reduction, at least in the conversations that they were having. The game has changed Deidre. These companies are very profitable now. It seems like the ESG movement has taken a big blow in recent years. The company’s managements, I think they realized that they have got some of the leverage back and they can say, look, we’re just going to do our thing. We’re going to be responsible. We’re going to try to make economic decisions that are smart about carbon reduction. But our goal is to produce energy and generate cash flow for our shareholders, and then the shareholders can figure out what to do with the cash once we pay it to them.

Deidre Woollard: I think transitions always take longer than we’d like them to, and that’s always a thing to keep in mind.

Jason Hall: They take longer and then they happen fast.

Deidre Woollard: Very slow and then very fast. Also, ConocoPhillips they reported today as well, not quite as big as Shell. Production a little bit higher than expected. Profits, a little bit lower. You’re looking at both natural gas and crude oil when you’re looking at these companies and just wondering about how as an investor in these types of companies, you’re thinking about the relationship between both natural gas and oil prices.

Jason Hall: This is a good opportunity to start by drawing the distinction between ConocoPhillips and these other super-majors like Shell, ExxonMobil, etc. ConocoPhillips is a pure play on exploration and production. They go find the oil and gas, they produce it, and then they sell it to somebody that’s going to do something with it or they market it directly through refueling stations and that thing. That means that ConocoPhillips is very much a leveraged bet on the price of oil and gas. If you’re Shell, you have a petrochemicals business, you have refining operations that are less susceptible to the ups and downs of oil prices. You have that built-in diversification that a company like ConocoPhillips doesn’t have. With that said, you start looking at oil and looking at natural gas. They share the reality that supply and demand drive their prices. Now, the difference is where that supply is and where the demand is. Oil is very much a global commodity, whether it’s oil or refined products like jet fuel or gasoline or diesel. It may be refined in North America and then used in Europe, or produced in South America and refined in Africa and then used in the United States. These things move a lot. Relatively speaking, they’re relatively cheap to move. There, just liquids and you can move them pretty easy. Natural gas is, [inaudible] and this is starting to change, but historically has been exclusively consumed in the market that it was produced in because it is so expensive to move it. You have to take it, super cool it to condense it enough to get enough energy density to get enough of it on a vessel to then move it overseas. The vessels are very expensive. Then you have to take that liquid and gasify it in, and pump it into the pipeline of wherever it’s gong to be used, so it’s complex and very, expensive. That means that the shipping costs in the markets that don’t have it, Japan for example, most of Europe, their cost of natural gas is far higher than it is say in North America where we have gobs and gobs of natural gas that’s low-cost. The other big difference, Deidre of course is oil mostly transportation fuels, for the most part, some from petrochemical manufacturing. Natural gas, that’s utility, through your power plants, home heating, industrial heating, cooking, that sort of thing. The use cases are a little bit different for them too.

Deidre Woollard: That totally makes sense. Thank you so much for your time today, Jason.

Jason Hall: Deidre, it was great being on with you.

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Deidre Woollard: One theorem underlying AI prediction and forecasting. Tom Chivers author of Everything is Predictable, have Bayesian statistics explain our world. Here’s how the world of an 18th-century mathematician impacts our daily lives. You’ve called the Bayes’s theorem a theory of not quite everything, and I think that’s a good place to start, so tell us a little bit about what this theorem is and why it is the theory of not quite everything.

Tom Chivers: Sure. Well, I’ll say everything to do with intelligence is prediction. When we say we understand something, to a first approximation, what we mean is that we can predict it. We have a good model of it in our brains and we can predict it. We are always predicting the future. Almost everything we do is predicting the future. If you go to the shops, you are predicting. You’re going to go and buy some breakfast cereal, you are predicting that the shop we’ll have breakfast cereal. When you apply for a job, you’re predicting that there’s a reasonable chance you’ll get the job and that you will enjoy it and will be glad that you did when you do so. What Bayes theorem is, is massive prediction, is all the math if you’d like. All these predictions are uncertain. You’re never 100% certain that the shop will have breakfast cereal. You’re never 100% certain that you’ll get the job or the job will be a good one. But you can put an estimate, you wouldn’t redo it in numbers but you’ll have an estimate of how likely it is that that will happen. If you apply or if you walked to the shops then you’re betting that this predictions. All Bayes is the maths. The maths that describes how you make predictions and how you update those predictions in the light of new evidence. It’s this really simple one-line equation, and it’s the heart of it all. It’s the extent to which you are making good predictions, is the extent to which are being Bayesian. The extent to which you’re making bad predictions is the extent to which you’re not being Bayesian. It’s like the iron law of prediction. You see what I mean?

Deidre Woollard: The reason I read the book and I was interested is thinking about this from an investor standpoint and a stock picking standpoint. The way I’m looking at it is there’s two things. You’re trying to predict the macro cycle and you’ve got a lot of priors from that, from previous cycles, and search your leaves seeing everyone trying to predict the recession and failing miserably. Then you also are trying to do it with individual companies based on other companies that had a similar trajectory or things like that. How does Bayesian theory play into both of those?

Tom Chivers: First I should say I’m not a stock picker. Funnily enough if I’m allowed to name-drop, my mom’s great uncle was a really brilliant stock picker. He was this guy called John Maynard Keynes, who you may have heard of.

Deidre Woollard: Yes.

Tom Chivers: He made incredible amounts of money on the stock market and then lost it all and then picked it again and did it again, so I’m trying to be a huge disappointment to him. But no one should take anything I’m about to say as investment advice, that’s really critical. I think the key from a Bayesian framework is you never have certainty in anything, you always have confidence levels in your estimates. You might think its 60% likely that Google will outperform the market or something like that, and then you saw they’ve just bought a bunch of NVIDIA chips or their latest smartphone looks really good and you adjusted up. Or you see that their latest generative AI has just completely flopped and just started doing really weird results, and so you adjust your estimate down. Just keeping in your mind that you never have to say, I think this is good or this is bad. You can say, I’m 70% confident that this thing is good. I’m moving up and down as new evidence comes in and just constantly updating yourself. The other thing I think it’s relevant when you’re thinking about investors and stock pickers themselves, because we know, don’t we? That the average stock picker does not beat the market. If you see someone get lucky over a year and make money over a year, how sure should we be that they are genuinely skilled and how much should we think that they had a couple of big trades and got lucky? With Bayesianism, you never have to make a final judgment. Early on you say, my prior is that for any given stock picker there’s only 30% chance that they’re going to beat the market or whatever the correct number is. Thirty percent maybe lower. But if after a year they’re ahead of the market, you say, well, I will adjust that opinion up. If they’re doing it after two years, you adjust your opinion up. When you’ve got Warren Buffett’s, he’s been doing it 50 years, you can be extremely confident without ever being certain that this guy is genuinely skilled and has something, has an insight into the market that most of us, certainly I, do not. I think that would be how I’d apply Bayesian framework to it.

Deidre Woollard: Yet there’s some of us that are better at this than the rest of us. You have this section in the book about the super forecasters. What’s the difference between the super forecaster and the rest of us? Because there’s a lot of forecasters out there, but I don’t think any of them are super forecasters.

Tom Chivers: No. This is the thing, I don’t know how many of your listeners would have heard the term before, it was Phil Tetlock, he’s still a working scientist but when he was young and in early 30s in 1984, he sat in on various meetings in the White House. I think it was about what people predicting what’s going to happen next with the Soviet Union. Something happened that none of them were predicting, and that was the appointment of Gorbachev, who was a liberal reformer and it’s completely changed the whole thing. But everyone said this unexpected thing confirmed what I already thought. That was Tetlock big takeaway from it. He sets up this thing called the Good Judgment Project, which it was literally getting people to make hundreds and hundreds and hundreds of predictions. Time-limited, explicit falsifiable prediction like will the Yen be higher again be higher than the dollar on 7 December 1986, whatever, and then judging how people did. He found that the median prediction was no better than random guessing. People were completely rubbish basically. It’s on a spectrum, some people are really rubbish, I think actually anti-correlated with truth, and some people were much better and they arbitrarily picked the top 2% and said these ones we’ll call the super forecasters. They did loads better. They outperform CIA analysts and stuff. The way they do better is they do things like breaking questions down into component parts like it’s a Fermi estimate if you’ve heard the term. If you ask someone how many piano tuners there are in Chicago, they won’t just say, I don’t know, about 2,000, they’ll say, well, what percentage of people own a piano? How many people are there in Chicago? Breaking it down, how long does it take to tune a piano. These sort of questions and trying to break the question down in smaller parts. They’ll keep score, so if they make a prediction and it’s wrong, they’ll note that down rather than just allowing that to disappear from their brain, and only remember the times they’ve got it right and so they can learn from it. I think from the Bayesian point of view, the really important thing they do is they use prior information.

They explicitly use what a Bayesian would call prior so late. A friend of mine who’s a super forecaster, his example he always gives a cite it in the book I think, is imagine you’re at a wedding and someone asks you, should be a pretty inappropriate thing to ask at a wedding actually now that I think about it, but imagine someone asked you this at a wedding, how likely do you think this couple is to go the distance? A non-super forecaster might just use the information around them, like, they look so in love, they look so happy, they’re staring into each other’s eyes, 95%. But a super forecast would try and find some appropriate reference class from appropriate base rate from which to adjust. Well, about one in three British marriages end in divorce so I’ll start from there. Then I see how closely they’re looking into each other’s eyes and adjust up or down from there. Depending on whether I think they’re looking in an appropriately loving way. That’s explicitly Bayesian. They call it using that outside view that is finding a reference class or base rate and then adjusting with the inside view, the details in front of you. But that is exactly the same as having a prior probability and adjusting it with new data, and it is crucial to a good forecasting. It’s tricky sometimes because when you’re doing things like predicting whether Russia will invade Ukraine in 2022. What’s your reference class? Is it the percentage probability that a given country will invade a different given country? Is it number of times Russia invades Ukraine per centuries? Do you update by the number of tanks that they put on the board, or I don’t know. It’s complicated and that’s a lot of the skill is finding a good reference class. But that’s what you do. That’s how you start out.

Deidre Woollard: Hey Fools, just a quick programming note as we wrap today’s episode. This is my final show as the host seat for Motley Fool Money. As I leave the Fool, I want to share just how much I’ve appreciated learning from all the analysts during my time here and all the time, you, our listeners have spent tuning into my conversations on podcast. Thanks for listening and Fool-on. As always, people on the program may have interest in the stocks they talk about, and the Motley Fool may have formal recommendations for or against, so don’t buy or sell stocks based solely on what you hear. I’m Deidre Woollard. Thanks for listening. We’ll see you tomorrow.

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