Disclaimer:

00:22

This podcast is for informational purposes only. Information relating to investment approaches or individual investments should not be construed as advice or endorsement. Any views expressed in this podcast are based upon the information available at the time and are subject to change.

Rob Campbell:

00:38

All right. Hi, everybody! Joining me today on the podcast is Paul Moroz. Paul, welcome back.

Paul Moroz:

00:43

Great to be here, Rob. Thanks.

Rob Campbell:

00:45

So Paul, we're here to talk about the post-mortem, a process that the Research team goes through on an annual basis, usually around this time of year. And so maybe just to kick it off, what is the post-mortem process, and why do we do it?

Paul Moroz:

00:59

At the beginning of each year, we look back over the last year, often even further back—many years, depending on how long analysts have been at the firm. And we basically look at the mistakes we've made. Where did we screw up? What went wrong? What did we learn about those?

It's an opportunity to get humble and share with other colleagues. So, it's partly about teaching and learning, but culturally it's so important because we recognize that one of the greatest mistakes that investors can make is when they're overconfident, or they think they know it all, or they're not willing to admit that there were mistakes made. And so this process is specifically designed as a cultural element to really show that we need to be humble and we need to learn and we do make mistakes. And what can we ultimately learn from it? It takes about four of our research meetings to go through this process with the entire team.

Rob Campbell:

02:12

And just to explain a little bit more, what does that mean to “go through the process?” Is it a round-the-table type discussion? What actually goes into this post-mortem?

Paul Moroz:

02:20

Each member of the Research team will look back on the stock recommendations they made, [and the] longer term performance of the portfolio. We have data that is analyzed by our Lab team that picks out attribution on a stock-by-stock basis and on a cohort basis, going back many, many years now. And so they'll take that in and they will write their mistakes and their learnings. In some cases, [in] a longer piece of research on an investment that didn't pan out. And then from that process, then they'll share some of their top two or three learnings. They'll post their entire piece of work to the team. And we'll open it up to the team to ask questions, provide feedback or comments, and have a discussion.

Rob Campbell:

03:09

So, I can imagine this would be a rather uncomfortable exercise—basically making yourself vulnerable in front of your entire team. Particularly if you were a newer member of our Research team within the past year. At the same time, I would think that it's so important for people to be forthcoming and vulnerable to make the exercises as effective as possible. So, what do you do in your role to facilitate that? What are some of the things that you do to help tease out these most valuable learnings?

Paul Moroz:

03:37

Well, it's important when you're in a position of leadership to walk the walk. So, I'm the first one that sticks my hand up and says, "Hey, I got this wrong. I made a mistake. Here's what I've learned." And when you show that you can be vulnerable and there's a safe environment, it helps create trust and candour. Now, the other thing, Rob, that we have going for us—it's a great question, but it's even odd thinking about it within our culture, because we have a culture that has a flatter hierarchy and we have a culture of candour, so it's a lot easier to have these conversations. And we've been working on this for so many years now it would just be very different than being in a culture where there's a lot of hierarchy or people fear the risk of being reprimanded for something that they say.

Rob Campbell:

04:30

Got it. And Paul, can I just ask, before we dig into some of the learnings, just about the concept of learning itself. I was reading one of Christian's learnings from the last year, or at least the way he framed it. He said, "Gosh, this is a good exercise, but we need to be humble about our learnings, because if I closed my eyes and crossed a six lane highway during rush hour, and if I got through by chance, what should I draw from that learning? Does it mean that I'm invincible? That I can do this? That there was no risk?" So, can you just talk to that? Are there any pitfalls in this exercise of learning?

Paul Moroz:

05:02

Yeah, absolutely. There's three big…I'll call them “learning problems” that come to mind. The first is simply time. So, with enough time, the stock market is always right, in the sense it'll give you an answer, but over how long do you wait before you actually measure a decision? And so it's actually a terrible feedback system.

Paul Moroz:

05:26

Let's pick on what's going on in today's world with GameStop. And there's a stock where the feedback is giving a lot of positive energy to the investors that have put forth their money. But do you want to wait a little bit longer to evaluate the investment decision? Probably. So, so many of these…it's a question of often years to play out and even longer. Market cycles.

05:52

So that's the first problem. The second is, there's actually a problem with how...we'll call it the “thinking participant impacts experiment.” This is straight from George Soros, a very famous investor, and he was a student or a fan of Karl Popper, who was a famous philosopher. And he came up with this theory—he disagreed with Karl Popper on one point where he said that the social sciences were different than the natural sciences. You couldn't set up proper experiments because in a social science, the person conducting the experiment or the thinking participant actually influenced the course of events. Now, there's a lot of situations in business and the stock market where that applies, and then it's difficult to learn from them.

06:45

So, one of the ways I think that happens is when you get an individual as a leader that's just super special—they influence the course of events. So I'm thinking about the concept of...I think it was Walter Isaacson that coined the phrase “reality distortion field” with Steve Jobs. Elon Musk has a lot of that. And you got to think, "Well, how much of the success of Tesla is just this one individual character?" And he has bent the perception of that business, the perception of the industry, been a cheerleader for raising money, and really influenced the fundamentals of the company. So, do you learn that you should take those risks? Or that maybe it won't work out if you don't have that special person?

07:29

Another one is on the mass crowd level. If a crowd believes in something enough, they can impact the fundamentals too. So, a classic example would be a run on a bank. If everyone believes that a bank might fail and starts lining up—and then you can imagine you can see people lining up at a bank to take their money out—the bank can actually fail. So, as you encounter these, it's difficult to learn because they might play out in different ways as the thinking participants think differently.

08:03

And then the last one, Rob, why learning is so difficult is alternative scenarios—where the world might've just turned out differently. Currently we're in a low interest rate environment, low inflation environment, and the central banks have been very accommodative. There's been times in history where that hasn't been the case. So, you can imagine that what you would have learned by implementing certain strategies in, say, the early 80s, might be completely different than implementing a particular strategy in our times today.

Rob Campbell:

08:36

Got it. So that's great. There's clear benefits in going through the process of learning. We've got to hold our learnings lightly, perhaps, or at least make sure we're drawing the right conclusions. So with that stage set, why don't we get into it and some of the big learnings that you gleaned from the team and from yourself over the past year?

We'll start with one of yours. You've got a “Ben Stiller Theory” about humans and people and the way they're wired. Can you share a little bit about that learning and what that concept is with our listeners?

Paul Moroz:

09:06

This is Ben Stiller, the actor. I apologize to Ben if you're listening to the podcast. I'm sure you won't be. But he was in such comedies like Zoolander and so on. And a lot of the movies that he's been in, he plays that comedy role. He sticks to that same sort of part. And I lovingly refer to this as the “Ben Stiller Learning” in that I think each of us in our own way are actors. We have our tendencies to be wired a certain way in terms of how we make decisions and our own biases, and that results in a particular part being played.

09:44

And so reflecting on myself, what are my Ben Stiller personalities? One of the things that I go to when I make investment decisions is, I'm always thinking, “defense first.” And I'm concerned that perhaps things won't turn out so well. That's just my natural disposition. Over the past while, risk management really hasn't paid off. So that's a mistake in one sense on my part, but the greater realization is that, well, I have to work with other actors, other teammates that fill in those different perspectives.

10:18

My colleague Peter Lampert had built on this idea in a different sense, in that he observed that we've made a lot of strides and maybe errors in the past in how we've perceived the rise of China and the investment opportunity set in China. And his observation, coupled with the Ben Stiller idea, is that for those people that have spent more time in Asia—I've lived in Singapore, Peter Lampert lived in Singapore, we have other people that have lived in Asia—our disposition towards their system and different ways to go about business...we just have a different lens. Versus say…someone that has spent more time in the West, or someone that has grown up and experienced more of a communist system in…call it Eastern Europe. So, just understanding that we have these different lenses, being aware of them, and then trying to work hard to see others' perspectives, that's what I mean when I talk about, “we're all actors just like Ben Stiller.”

Rob Campbell:

11:26

We may have referred to this in a past podcast, but we've put significant effort into that very thing—at least increasing the awareness of the way we are individually wired through Research meetings over the past year. Can you just share a little bit on that process? And I think it was designed with that learning in mind.

Paul Moroz:

11:45

Rob—you're referring to, I think, some of the work we've done on the cultural front with the [Insights Discovery^®] profiles?

Rob Campbell:

11:51

Exactly. And just understanding people's personal histories and what's shaped the way that they are today.

Paul Moroz:

11:58

The background is that, within our HR process, we're really looking for what we call “cognitive diversity” on the team. We embrace different perspectives and experiences, but it's not enough just to bring in a team that has that cognitive diversity, you have to work hard to understand their perspectives.

12:17

And so we went through a period of time...it took us close to six months to go through these profiles that delved into how people are wired, essentially. And in that process, every research meeting we had, we'd start off by going through someone's profile and they would share their experiences—what has shaped their perspectives and points of views. And it was a chance for the rest of the team to ask questions, provide feedback, and really get to know people. And in that process of recognizing that these different perspectives are okay, you build trust and you're better able to utilize your teammates when you're collecting information to make investment decisions.

Rob Campbell:

13:07

So, building trust and effectively reducing friction, I would think too.

Paul Moroz:

13:10

That's exactly right.

Rob Campbell:

13:11

Got it. Let's move on to another learning. This is one that I presume is not new for the year 2020, but this idea of the “folly of forecasting,” and how one should filter as opposed to trying to forecast. Can you expand upon that a little bit for our listeners?

Paul Moroz:

13:28

Absolutely. I mean, 2020 was such an unbelievable year because it demonstrated how we were in a period of ultimate uncertainty. We didn't know whether there was going to be a multi-year bear market with some sort of depression; or a bull market where stocks go up, where there could be inflation, where central bank stimulus makes it a very good period for investors.

13:57

So, our mantra going through this was really to “be in two spots at one time.” And this concept of trying not to predict the future because you get it wrong so often is something that many of our teammates recognized, relearned over the course of the year. The expression, "filter, don't forecast..." it’s a concept about trying not spend our time guessing on things that we can't possibly predict, but focus on our investment philosophy and assemble portfolios that have the most attractive features that they can, and that are diversified and have natural contradictions in them—so whatever environment that we end up in, they're going to be resilient to do relatively okay.

Rob Campbell:

14:41

It's funny you mentioned [Karan’s learning] because I like something that he put into the post-mortem: the three most important words in investing are, "I don't know." So, put yourself in the path of favourable chance and build resilience, as you said, to whatever outcome.

14:54

So, recognizing the folly of forecasting, of having to try to predict how the year would end up—we did have two, maybe three distinct phases throughout the year. But if I boil down to two, I'm wondering, Paul, if you can just tell us some of the learnings that you had on the way down with respect to the stock market, and some of the learnings that came from the team on the way up?

Paul Moroz:

15:16

That's a great way to phrase it because we joke that you have bear market learnings and bull market learnings. And these are different.

So, the bear market learnings that came up... for example, John Wilson realized that not all debt is equal. And as we went through the crisis, we went through every company on an individual basis to understand their covenants and understand their liquidity profile stretching out.

Paul Moroz:

15:44

And so for us, it wasn't just a matter of leverage—his learning really pointed to in this case the liquidity profiles were vastly different between different companies. Another one on the downside came from Jeff Wilson, one of our traders, who just learned just how difficult that severe volatility is mentally. Having to manage the day-to-day ebbs and flows and bad news of the market...it's mentally draining. So it was a very different environment than when the stock market just moved steadily in one direction. There isn't the same level of volatility.

Rob Campbell:

16:24

Let’s get back to…we did learnings on the way down. Learnings on the way up? I don't know if this injects some positive energy into the conversation, Paul.

Paul Moroz:

16:30

Vijay, our Director of Research, has made the comment on the way up that...just simply, “don't interrupt the process of compounding.” That's really the long-term, “Be Boring. Make Money.^TM” game that we're involved in. On the way up you realize, "yes, this too shall pass. These companies will compound." And with, he adds the caveat, "and valuation will matter at some point." So that's the “up” learning—with a caveat.

17:02

There's another one that came across many individuals in the team, recognizing that during this period of time, risk management doesn't seem to pay.

Rob Campbell:

17:12

Meaning what?

Paul Moroz:

17:14

Well, meaning that there seems to be so much focus on the upside, any time that you made a decision to try to manage risk, it just went against you. It looked foolish in retrospect. So again, that could come back to a timing problem, but that's just the market regime that we seem to be in. And I think looking at some of the...I'll call it “pockets of froth” that are going on in the market when you read the press, you can see how there's certain elements of an investment process regarding risk management that are just not being rewarded right now.

Rob Campbell:

17:53

Speaking of process then, can we shift into this category of process learnings over the past year? One of the things that I picked up on was this tension between gathering enough information versus the paralysis of needing all the information before making a decision or acting. And that is with respect to trading, with respect to whether to do more work on a company. Can you speak to that? And just the overall framework around process and decision-making.

Paul Moroz:

18:25

That's a great question. Imagine coming into a research organization as a new analyst and being faced with all this information and having the flexibility to spend time reading really, an infinite number of annual reports, talking on the phone with people, spending time out looking at assets…all the typical due diligence things we do. When is enough, enough? When have you hit Pareto's Law of 80/20, where you have most of the information to make an investment decision?

19:00

That came up a number of times. For most analysts, it marks a point in their learning curve. Probably anywhere from the three year to seven year mark, as you're transitioning and you're sorting through how to manage this problem. It's a real art. There's a couple of ways that we've expressed this—people have realized, "Don't boil the ocean. Don't go the full distance." Or I call it “counting bathrooms.” If you've gotten to the point where you're researching McDonald's and your due diligence process involves counting the bathrooms and making sure they're there, you've probably got too far.

Rob Campbell:

19:36

As Jim would say, "Focus on the tides, not the waves."

Paul Moroz:

19:39

That's right.

Rob Campbell:

19:40

Just on that subject of process, a couple of other learnings that I picked up on were this idea of betting on people, as they tend to create skew. Another one that's maybe adjacent is just that companies that tend to have an internal compass focused on the customer, tend to do better over time. Can you speak to those learnings? Particularly in this environment where lots of these virtual business models are developing and we've seen them perform exceedingly well in the stock market over the past year.

Paul Moroz:

20:08

Well, on the people front, I think people are the heart of capitalism. They make decisions on who to fire, who to hire, what products to develop, what problems to solve. And what's so fascinating to me about people is when you find good people, there's a whole bunch of things that they can create that is going to come out into the future. It's not in the present. And that means that there's an opportunity to create value that isn't necessarily recognized. So, we obviously spend a lot of time interviewing management teams and as best we can, sorting out how we allocate capital to people just as much to the companies themselves.

Paul Moroz:

20:53

Now, you had asked about this learning or idea on companies that are customer centric. And I think you've hit on a real important point. The way that I would phrase this, Rob, is that there is a difference between the value proposition that companies provide, and the way they make money and monetize that. And sometimes those are detached. And a lot of times what happens in the course of the evolution of a business is, there's a real successful product or service that's created, and then the company figures out how to monetize that. They put processes in, and then innovation goes stale or they're not keeping up with investment. And so when you find companies that are mindful of the value proposition—and remember that if they keep providing extra value to the customer, the business is going to carry on—often not only does the business live longer, but they create more value and customers are happier, and the whole thing's a wonderful story.

Rob Campbell:

22:04

Sounds like another time horizon related learning.

Paul Moroz:

22:07

Absolutely. My colleague had just recirculated some of the management principles of Amazon…and make no mistake, they're playing the long game and focusing on the customer. Solving problems is certainly one of the directions that they continue to move towards.

Rob Campbell:

22:24

Paul, as you listen to the learnings bubbled up from the team, do you recognize a lot of them? Meaning do you say to yourself, "Gosh, I remember back in the mid-2000s when I learned that?" And what do you do with that, if you do recognize those learnings?

Paul Moroz:

22:39

Some of it is an experience thing. As you go through a career as an investment professional, you have to have that learning. You have to go through market cycles. You have to go through a bear market and a bull market. And it's one of those things where it can be difficult to teach until you've actually just been through that. And in terms of coaching, sometimes you just don't know. You might have a different opinion on things. So, I think what you can provide is historical context or the counterpoint, but remember the fragility of learning—it's very difficult. I turn this back to…what's so important is just this principle of getting vulnerable and opening up and trusting your colleagues to share learning in the first place and say, "I think I made a mistake on this." That's half of the battle.

Rob Campbell:

23:28

Great. And then one last question with respect to just broad learnings from the team—and this might be bigger picture, just big shifts in the macro backdrop that we've witnessed over the past year—you and Peter Lampert have talked about the crossing of the Rubicon. Can you expand upon that, just with respect to government policy?

Paul Moroz:

23:48

It seemed COVID was a catalyst for more government intervention into the economies. And the political pendulum has been swinging towards the left for many years now, but why we felt that the Rubicon has been crossed—there is so much direct fiscal stimulus that the next several years may look a lot different. This is almost like precedence has been set again for trying to solve problems directly on the fiscal side. And that has ramifications for maybe how the economy is run and some of the risks that surface as a result, whether that's inflation or whether that's redistribution of wealth. That's not a prediction on how that plays out, but more of an observation suggesting, yeah, there's been an evolution here and it could be different in the next decade or so.

Rob Campbell:

24:43

Like we said earlier, more about filtering, less about forecasting. It sounds like a great place to end, Paul. Thanks so much for sharing your thoughts on the post-mortem process and why it's important. It sounds like we're going to have you back on this podcast a year from now for the 2021 learnings. Look forward to it.

Paul Moroz:

24:59

Thanks, Rob.