Stock Portfolios, Football Teams, and the Stories We Tell Ourselves about Each

By Simon Hallett, Vice Chairman | July 09, 2021

The world is complex and unpredictable, but humans prefer order, and cause and effect, so therefore tell stories that purport to explain what is simply random. Narratives pre-date writing. They help make events coherent and memorable, while arousing emotions in the listener. Behavioral biases, which all humans share, are in many cases essentially products of the stories we tell ourselves. The more detailed the story, the more entertaining it is and the more powerfully it can affect our emotions. We love stories. That can often be wonderful, but in decision making it can be dangerous.

In investing, there has been at least a little progress towards improving decision making by resisting the power of stories. Quantitative investors describe how they adhere to purely objective rules (rules and lines of code that, of course, they themselves have written) to govern their behavior and reduce bias. “Quantamentalists,” another breed of investor, allow some judgement to enter their decision making once they have established the framework. They do this in part in recognition that, as a rule, most humans don’t like rules. We suffer from what psychologists call “algorithm aversion,” i.e. preferring to go with our gut. That preference results from our need to remain in control, or at least to believe we are. Permitting human override of an algorithm may degrade the quality of its output, but in granting themselves the comfort of exercising some degree of control, decision makers likely improve their rate of adherence, for an overall improvement in outcomes. I fully expect self-driving cars to come with a steering wheel that will have no impact on direction of travel, but will allow the human passenger to feel more secure than if she were simply sitting back and giving herself over fully to the computer under the hood.

In his book The Success Equation, Michael Mauboussin writes extensively about the importance of a strong process and rules in activities where the immediate outcome is driven by luck and skill. He describes how it is possible to improve skill through what has become known as deliberate practice: repetitive, purposeful, and systematic repetition with immediate and specific feedback. Luck, however, can only be managed by having a strong process, with rules or standards constraining decision making and the urge to impute too much importance to our role in any one result. In activities such as investing or team sports—arenas where skill and luck both come into play—narrative is particularly seductive, making adherence to this recipe for success a constant battle.

The pandemic meant the stands were still empty at “Theater of Greens,” the home stadium for Plymouth Argyle this year, but the ideas were plentiful as to how to harness the theories of behavioral economics to put a more competitive squad on the field.

Richard Thaler, who won the Nobel Prize in Economics for his work in behavioral finance, has noted that 1980s basketball superstars like Larry Bird converted their three-point shot attempts at the same near-40% rate as 21st-century sharpshooters such as Steph Curry or James Harden. Yet, Bird took half as many three-point attempts as are normal today, favoring shots closer to the basket, which great players can hit roughly 50% of the time. It took 30 years for the three-point shot to become as popular as it is today or, in other words, for basketball to realize that 0.4 x 3 is greater than 0.5 x 2.

The Bill James Baseball Abstract, an annual compendium of baseball statistics that ultimately legitimized the science of baseball sabermetrics, was neglected for many years before a James disciple, Oakland Athletics General Manager Billy Beane, used the approach to identify underpriced skills for his small-market team, as popularized in Michael Lewis’s 2002 Moneyball. It was only then that James himself landed a job in the front office of the Boston Red Sox, helping the team finally overcome the “Curse of the Bambino,”¹ and win its first World Series in 86 years.

Many baseball fans complain that the influence of Moneyball has been too great—players are chosen purely for their ability to walk or jack balls over the fence; defenders are all stacked on one side of the infield because that’s where the statistics say the vast majority of a given batter’s ground balls will be hit. “It’s no fun anymore!” Clearly, those fans prefer intuition and stories to success and efficiency. They also subscribe to the great man theory, that results are driven by individual managerial genius, the wizened skipper playing a hunch.² And yet, organizations typically strive to create and adhere to processes that can improve their probability of success—to control luck.

I have been involved in two firms with many similarities, one being an investment manager and the other a football (soccer) club. An investment portfolio can, through careful construction, be more than the sum of its individual parts thanks to diversification. It may seem odd, but a football team is a portfolio. It, too, needs careful construction. You can’t simply rank order the most attractively priced available players and take the top 20 to form your squad. You would end up with a team made up only of defenders, and no goal scorers.

More than a decade after John Henry, the Red Sox owner who had hired Bill James, purchased Liverpool FC and brought Moneyball to the UK’s Premier League, systematic use of data analytics has finally worked its way throughout the ranks of English football. At my football club, Plymouth Argyle, which plays in the third tier of the leagues, we have set rules and standards to guide the decision-making of those who select the squad. Beginning with our philosophy, i.e., answering the question “What is the style of football we wish to play?,” we have defined the desired characteristics of each position. Our philosophy includes playing the ball forward from the back with quick passes along the ground to the opposition’s part of the field. Our goalkeeper must, therefore, be able to kick with both feet and play short passes while under pressure from the opposing forwards. We also prefer to play in a tactical lineup, known as a 3-5-2, with a pair of strikers at the front and a couple of fit defenders, one on each side, who dash up and down the wings depending on whether we or the opposition have the ball.

Defining the philosophy this way and defining how we will implement it enables us to search databases for players that match our criteria in each position, such as the defender we recently signed based on some impressive data around his defensive blocks, aerial duels won, and tackles per game. Then, in quantamental fashion, we can conduct research into aspects of players that can’t be quantified (yet!), such as their character, personality, or work ethic.

There are differences between assembling an optimal squad of football players and an investment portfolio. One is that securities prices are freely available, updated continuously, and can be compared with their hypothetical value generated by a model. That is not the case with football players. Transactions can only be made in two “transfer windows,” one midway through the season in January, the other during the summer before the next season starts. And no one has yet come up with a model that can assess players’ value in the way that we forecast cash flows and discount them to a present value to give an idea of what a share of stock is worth. I live in hope, though!

The market for football players is relatively efficient, but not completely so, and becomes less efficient the lower down the leagues you go. In this way, the relative inefficiencies of the market are parallel to those for, say, US large caps compared with those for emerging market small caps.

But surprisingly, perhaps, there are more similarities than differences. The market for football players is relatively efficient, but not completely so, and becomes less efficient the lower down the leagues you go. In the Premier League, the most watched football league in the world, there is a strong correlation between what you pay and the results you achieve. That is not the case lower down, so my club has a strong incentive to improve decision making, to exploit the behavioral biases and subsequent mispricing that is prevalent. In this way, the relative inefficiencies of the market are parallel to those for, say, US large caps compared with those for emerging market small caps. Similarly, though, as the potential gains to improved decision making increase, so does the resistance to replacing intuition with algorithms and process that reduces the degrees of freedom under which individuals operate. Those clubs which can overcome that resistance will generate a competitive advantage—an edge. I believe my football club has such an advantage, but I am on the alert for signs of backsliding—going along with “But that’s the way we’ve always done it!”

We have gone down this path at Plymouth Argyle because we want to spend the Club’s money wisely and compete by being smarter, not by spending more. At Harding Loevner we started down this path 25 years ago as decision making spread beyond the handful of founders to an expanded investment team. Each portfolio remained the product of two single decision makers but was now made with input from over 30 analysts. We had to learn how to structure a process that benefits from group wisdom but is not damaged by “groupthink.” The foundation of that was, and still is today, individual accountability and aggregation of individual decisions. Analysts drive the process and decide what stocks they will cover. They are free from direction by their colleagues, and free from direction by portfolio managers. They are not completely free, though. Just as Argyle’s team must recruit players who meet the objective standards we have established as being consistent with our playing philosophy, Harding Loevner analysts must confine their activities to securities of companies that they judge to conform with our investment philosophy, which focuses on growth, quality—which we have historically equated, in part, with a demonstrated track record of profitability—and price. When we look back at the last 25 years, we can see clearly that the arc of evolution of our investment process has been to define more clearly and rigorously the rules that restrict our analysts’ liberty to follow any company they chose. This has been highly effective at controlling biases and risk, and, overall has been good for returns.

Today, there are any number of voices, both internal and external, calling us away from the framework and structure that have served us well. The rise of the digital economy, and its steady proliferation of fast-growing but still-unprofitable businesses with compelling narratives, continually tests our reliance on an established track record as a guide to the future and the best indicator that a company has the culture and institutional strength to withstand cyclical downturns and shifting competitive landscape. Has the nature of growth changed? Have the kinds of characteristics that define quality shifted? Or are those merely the stories we tell ourselves to justify paying higher prices for the hot new fashion?

I don’t know the answers to those questions yet. I do know that, while it is necessary for portfolio managers to evolve along with markets, such evolution should take place deliberately and only after careful consideration. At Argyle we are at the early stages of translating our playing philosophy into a structured process for how we find players, and how they play on the field. Already, though, there have been occasions when we’ve had to adapt on the fly and adjust our typical tactical lineup. Football, like investing, is a game where the opposition can see what we do, and we must adapt to how they counter our plans. Players get injured, and replacement players may be less capable at implementing the approach. So, how we implement our philosophy must evolve, but we must be clear with ourselves that such adjustments are a change in process, not a change in philosophy. If we were to start changing our philosophy, we would surely be lost, tossed on a swirling sea of narrative.

Endnotes

¹Purportedly begun in 1920 when, after he had led the club to three World Series titles in six years, the Sox traded George Herman “Babe” Ruth to the rival Yankees for $125,000 (about $1.7 million in today’s dollars, or roughly the salary of Boston’s current backup catcher, Kevin Plawecki).

²It could be said the great man theory is also a feature of investment marketing—how often do brand name investment managers attract large amounts of client assets and then collapse in ignominy?

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Too Much Information

By Simon Hallett, Vice Chairman | March 03, 2021

In the late 1950s, in his book Common Stocks and Uncommon Profits, Phil Fisher recommended making investment decisions based on “scuttlebutt,” the kind of information an investor could get by asking around. This entailed tracking down and interrogating customers and competitors, employees, and former employees. Doing research, in the sense of gathering evidence and analyzing it to reach a conclusion, was hard work, but enabled analysts committed to such intellectual labor to obtain an edge over their competitors simply by having better, and more complete, information.

Indeed, when I started my career in investing in the late 1970s, obtaining even basic financial info about a German car company still required going to Germany and knocking on the company’s door.

Now gathering information no longer takes much effort. We are deluged by floods of data—not only the details of prices, volumes, margins, and capital investments of individual companies, but also highly granular data about credit card receipts, numbers of cars in parking lots, or words used in media reports. These new, “alternative” sources of information have briefly given some stock pickers a slight edge in predicting short-term stock price movements. The informational advantage provided by such data is but fleeting, however; once this data is commercially accessible to everyone, the advantage disappears. Thus, even for the short-term investor, information gathering itself no longer provides a lasting edge.

For long-term investors, the relationship to information has changed even more fundamentally. You no longer need to seek information; it finds you. Your job, rather, is to act as what Lou Gerstner, the former CEO of IBM, called an “intelligent filter”—determining the information that is important and ignoring data that (in the case of the investor) doesn’t help you forecast cash flows and estimate the value of a security.

The fact that filtering information is the long-term investor’s task, of course, doesn’t prevent most from feverishly pursuing every bit of information they can about the companies they follow. Egged on by the 24/7 news cycle, internet chat rooms, and by data providers to know their companies in as much depth as possible, investors often seek to become experts in every aspect of each company’s business. It’s dubious whether this helps them make better estimates of what a company’s shares are worth. Instead, the evidence suggests that, beyond a certain amount, each extra piece of information has zero marginal impact on forecast accuracy. The impact remains positive, however, on the investor’s confidence in their forecast.

The evidence suggests that, beyond a certain amount, each extra piece of information has zero marginal impact on forecast accuracy. The impact remains positive, however, on the investor’s confidence in their forecast.

In one unpublished study, described in Winning Decisions by J. Edward Russo and Paul J. H. Schoemaker, people who handicap horse races were asked to predict, based on increasing amounts of information, which horse would win a race. They found that, beyond a very limited amount of data, forecast accuracy did not improve with more data, but the handicappers’ confidence in their forecasts continued to grow with each extra bit of information.

Knowing more makes you feel better, in other words, but doesn’t help your decision-making. In investing, feelings and actual results arguably are even more disconnected. After all, feeling good about a decision is rarely a help in successful investing—to have a good outcome, an investment view must be different from that of most other investors, and standing apart from the herd almost always leads to discomfort.

Sitting on Our Asses

The job of an investment analyst, then, when forecasting a company’s business prospects and the price that should be paid for its stock is to distinguish between what is important—the signal—and what is useless noise. That’s what we do at Harding Loevner. Our “common language” is designed to guide investment collaboration by helping us focus on low-frequency signals that are important to a long-term investment thesis and avoid being distracted by torrents of high-frequency information that obscure the relevant underlying issues.

We recognize that our industry has an extensive tradition of emphasizing high-frequency signals to induce transacting. In the past, much of the revenue associated with financial services was transaction-based. Brokers were paid only when customers transacted (indeed, when I started my career, so were investment managers!). Unsurprisingly, brokers devoted great effort to stimulating customers to act. Customers responded as you’d expect them to—humans like action, not sitting still. Although the investment management industry has shifted in recent years to replace commissions with asset-based fees, there remains a popular expectation that a good investor will be active, including taking advantage of the most readily available and highest-frequency bits of information: stock price movements (both up and down).

Few investors, though, are able to capture any benefit from high-frequency signals. Our analysts don’t even look at stock prices until a company has been thoroughly researched and qualified as meeting our quality and growth criteria, its long-term cash flows have been forecast, and the fair value of its shares estimated.

Stock prices are much more volatile than the underlying qualities of the business they are supposed to reflect. Investors should remember the words of Charlie Munger, who said successful investing is a matter of “finding a few great companies, then you can sit on your ass.”¹ Of course, while we spend a lot of time following Mr. Munger’s advice, that doesn’t mean we are sitting still. We are constantly questioning our assumptions, testing our hypotheses, updating our information and, occasionally, as a result, changing our minds. Usually, though, ignoring the calls of those whose business model, if not entire worldview, revolves around urging you to move is the key to success.

Compounding the Effect

An investment process structured around the long term, and asking questions about long-term strategy not short-term results, will focus on a few fundamental signals that show a company’s progress in creating value for its shareholders. It will focus on competitive structure of an industry, and durable competitive advantages, rather than on the outcomes of the recent past. It will take what you’ve learned and use that to forecast a company’s investments in its business and the cash flows those investments should generate over long periods of time. Only then can you make an informed guess as to what a company is worth and compare it to what the market is inviting you to pay.

A process focused on the long term also recognizes the importance of compounding—that over a long holding period, even if you did overpay, the rate at which a company continually reinvests its cash flows will be a much more important contributor to your return. In an era when information is so democratized, our one true edge is an ability to latch onto a few incremental competitive advantages that we’ve identified in a company, and allow the company to do its job over the long term and provide the power of compounding to our clients’ portfolios.

In an era when information is so democratized, our one true edge is an ability to latch onto a few incremental competitive advantages that we’ve identified in a company, and allow the company to do its job over the long term and provide the power of compounding to our clients’ portfolios.

Humans invariably underestimate this phenomenon. Compound interest is one of the wonders of the world, yet few people understand how powerful it is. It appears our brains are designed to deal with linear, not exponential progressions.

If there was any doubt about our difficulty in intuiting the power of exponential growth rates, look at how unperturbed most people were a year or so ago when COVID-19 began spreading, first in tiny increments. People could not grasp what the impact of a very standard exponential growth curve could be until it was sloping nearly vertically upwards.

A long investment time-horizon also benefits from the long term being more predictable, despite being the sum of a series of short-terms. When some luck is involved, individual outcomes are unpredictable, but the rules of probability dominate as the number of independent trials and outcomes increase. The outcome of a single spin of a roulette wheel, a roll of dice, or draw of a card is unpredictable, but in the long run the house’s victory is as near a certainty as we can get in this world.

Our job is to turn the coins we toss into unevenly weighted ones, by being disciplined about the information we use, diligent in our research, and allowing the companies in which we invest our clients’ capital to do the heavy lifting for us.

Endnotes

¹Charlie Munger, Berkshire Hathaway Annual Meeting, 2000.

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Meme Stocks and Market Structure

By Edmund Bellord, Asset Allocation Strategist | June 08, 2021

Unless your investment horizon is measured in milliseconds, it’s usually best to ignore what everyone else is doing. But, occasionally, the market throws up something so peculiar that you have no choice but to sit up and pay attention.

The GameStop debacle, and the meme stock phenomenon more broadly, certainly fit that category. The story bears all the hallmarks of a Hollywood script: how a ragtag group of mostly retail investors, armed with commission-free trading apps and loosely coordinated across online message boards, executed a colossal short squeeze on the hedge funds betting against a down-at-its-heels brick-and-mortar video game retailer while inflicting bloody noses on some of Wall Street’s supposedly most-sophisticated operators. Predictably, several films are already in the works. But beyond the thrill of extravagant market pyrotechnics served up with a generous side of schadenfreude at seeing the odd master of the universe brought low by the great unwashed, why should we care?

Market manipulation is hardly new, and short sellers have always been a vulnerable target. The algebra of short selling, where the size of a losing position balloons ever higher as losses accumulate, is such that short sellers are forever in danger of being squeezed. Wait too long to cover or, worse yet, fail to rebalance at all, and you risk being wiped out. No surprise then that short selling for profit (as opposed to for hedging) is the province of dedicated specialists.

Despite their somewhat louche reputation, attested to by the prevalence of short-selling bans that reflexively blossom every time the market wilts, short sellers are nonetheless a key part of a healthy market ecosystem. A healthy market, one that allocates capital to its most productive use at the lowest possible cost, is predicated on many financial species with different time horizons, preferences, and liquidity needs co-existing in symbiosis. Despite what the textbooks might say, liquidity and price discovery are not created in a vacuum; they spring from the unceasing dance between three types of market inhabitants: long-term investors, arbitrageurs, and liquidity providers. Long-term investors attempt to steer capital towards its most productive use, arbitrageurs improve price discovery by correcting the occasional mis-pricings that emerge between assets with similar payoffs, and liquidity providers lubricate transactions, which helps to shrink transaction costs. If any one of these groups grows too dominant, the dance can quickly turn into a scrum.

It may be too early to add dedicated short selling to the long list of business models disrupted by the internet just yet, but it’s safe to assume that the shorts’ cost of capital has gone up.

Dedicated short sellers are a rare breed of arbitrageur whose relatively small number and modest asset base belie their importance. Much like value investors, whose tendency to buy when others are selling has a stabilizing effect on falling markets, short selling has a similar calming effect in the opposite direction. By leaning against unwarranted price increases, short sellers are a counterweight to market excess, one that makes for a more hospitable environment for beta grazers and alpha hunters alike. In helping to expose flimsy business models, ferret out accounting malfeasance, and unearth cases of outright fraud, short sellers are natural predators that benefit the market’s ecology. Enron, Lehman Brothers, Valeant, and, more recently, Wirecard and Luckin Coffee all owe their comeuppance in large part due to the sleuthing of dedicated short sellers.

Although short sellers are at the center of the GameStop saga, most of the ink spilled has focused on the more conspicuous elements of the story: the evident power of massed retail investors, their copious use of derivatives to magnify leverage, and the populist tendencies that seemingly motivated many of the squeeze’s participants. What has received less coverage is the potential impact of meme stock manias on market structure.

On the face of it, the debacle mirrors many previous episodes of market manipulation, no different, say, than the Hunt brothers ill-fated attempt to corner the silver market in 1980. But there is a crucial difference. A conspiracy to manipulate markets pre-supposes a central origin, a mastermind to hatch the plot before putting it into action. But on this occasion the conspiracy, such as it was, emerged spontaneously. It began with local, seemingly random interactions online that began to feed on themselves in an accelerating feedback loop.

There was no syndicate head, no directives whispered into disposable cell phones, no encrypted texts, none of the subterfuges typically associated with a conspiracy. Quite the contrary, discussions were held in the open, within freely accessible (albeit anonymous) web forums, where anyone was able to proffer their views about the fundamental value of the business, comment on the high short interest, or add an opinion about the implications of the tight float of underlying shares outstanding.

Decentralized and self-organizing short squeezes that materialize spontaneously represent a new type of concern for regulators because it’s unclear which rules, if any, are being violated. Moreover, it’s far from clear what mechanisms can be put in place to prevent it from happening again. But while this may be a headache for regulators, it represents an existential threat to short sellers. It may be too early to add dedicated short selling to the long list of business models disrupted by the internet just yet, but it’s safe to assume that the shorts’ cost of capital has gone up.

The impact of this new regimen on short sellers is impossible to gauge with any precision. They are a secretive bunch, after all. But we can guess at their travails by looking at the performance of the most shorted stocks as represented by the Citibank US Short Interest Equity Index. The index is akin to a long/short portfolio constructed according to the level of short activity for each stock in the Russell 3000, measured as the ratio of the amount of stock on loan relative to its overall trading volume. After ranking stocks according to this ratio and removing stocks with the most extreme metrics such as high borrow cost, the index simply shorts the 10 percent of stocks with the highest short ratio and goes long the 10 percent of stocks with the lowest short ratio. Historically, simulating short sellers in this way has been a profitable strategy: from its inception in June 2015 through the end of 2019 the index generated a cumulative return of 35%, with a highly respectable return to risk (Sharpe ratio) of close to one. At the onset of the pandemic in early 2020, which coincided with a jump in retail trading reminiscent of the tech bubble, the index collapsed. Over the following months it gave up almost its entire accumulated historical performance before reaching its nadir in January of this year, just as the GameStop episode reached its crescendo. Given the index’s long exposure to the least-shorted stocks, it likely understates the actual damage inflicted on many actual short sellers.

Source: Bloomberg

It’s a truism that no one enjoys losing money, ever. And if the performance of the index is indicative of the damage inflicted on short sellers, we can expect an imminent thinning of their ranks and with it a weakening of their stabilizing influence.

There is a small town in Thailand whose large population of macaque monkeys draws a steady stream of tourists. The locals sell bananas to the tourists who feed them to the monkeys. When the flow of tourists dried up during the pandemic, this balance was thrown into turmoil. Within weeks, the town was overrun by gangs of starving monkeys. Whole neighborhoods were declared no-go areas by authorities after videos of rampaging monkeys went viral.

It’s probably a stretch to claim that having fewer short sellers would have quite such a dramatic impact on market structure as the loss of tourists had on this Thai town, or that the monkeys are now calling the shots, but markets are notoriously susceptible to unforeseen events. A seemingly inconsequential disturbance in one area can ripple out, propagating and growing until it ultimately leads to systemwide effects. While our attention is often drawn to conspicuous price movements, it’s easy to overlook the veiled institutional or structural changes that sometimes precede and may even precipitate them. Bananas, anyone?

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Culture Club

By Simon Hallett, Vice Chairman | October 06, 2021

In sports, dynasties like the American football Packers of the 1960s, the New Zealand All Blacks national rugby squad, and basketball’s San Antonio Spurs have demonstrated the power of culture to bind individuals together and enable a team to produce results above what could be expected by simply adding up the expected contributions of each member. The business world has tried to produce similar results; although exactly what culture is remains poorly defined, the hundreds of jobs available on LinkedIn seeking an individual to oversee a company’s culture certainly attest to its importance. I’ve been fortunate to have a front row seat at an investment firm (Harding Loevner) known for its strong culture and, more recently, at a UK football club (Plymouth Argyle) that is trying to develop a culture that will strengthen the organization behind the team on the pitch. As is frequently the case because of my dual roles, the parallels between the two industries and the two organizations are very much on my mind.

There are many similarities between cultures at football clubs and investment organizations, despite the underlying processes required by their core activities—making decisions on the pitch about how to try and score and defend or making decisions about buying and selling securities—being very different.

In both industries, the goal is for the team to be greater than the sum of its parts. On the pitch, an individual must rely on teammates, but certainly not debate or challenge them. Rather, coaches teach decision making so that, like muscle memory, it is instantaneous and requires little active thought.

At Harding Loevner, rules and processes constrain decision making to prevent it from being dominated by cognitive biases. Colleagues think for themselves but must expose their ideas to challenge. This is the core of our investment culture—what we call “collaboration without consensus.” We believe that one of the most difficult biases to overcome in conducting research is the tendency to give precedence to evidence that confirms our beliefs and to ignore evidence that challenges them. So, it is important that our ideas be continuously exposed to challenge. However, this leads to other problems. Humans, as social beings, generally don’t like disagreement; they are literally fearful of it. That’s why an important part of a culture of collaboration without consensus is that it be enabled by both transparency and the value of tolerance. We strive to sustain an environment in which colleagues do not feel threatened by disagreement and recognize that challenges—while discomfiting—are essential for good decision making.

It would be nice to be able to say that our culture at Harding Loevner emerged from a successfully executed plan, but that wasn’t really the case. Thirty-plus years ago, the few of us at the firm just wanted to be good investors and to serve clients who shared our views about what made a successful investment program. The firm’s values simply reflected the personal values of the founding generation. We all believed strongly in acting with integrity and always putting clients’ interests first. Beyond that, I don’t think you could say we particularly held the values associated today with Harding Loevner. We didn’t set out consciously to make a culture based on transparency, personal accountability, tolerance, and the importance of process. Those values only developed as we learned more about decision making, often from our mistakes.

For example, we discovered early on that sharing information with our colleagues was valuable in sharpening our views. But we soon learned that without individual accountability and very clear rules of engagement, disagreements could very easily descend into finger-pointing and personal attacks. We also came to realize that no amount of experience is a substitute for exercising judgement within the constraints of process and structure. The alternative, too often, is a culture of blame and chaos.

Left to Themselves, Even Great Cultures Die

Part of a winning culture is the ability to adapt to changing circumstances, to have processes that change, and to take risks with new ways of behaving. Above all, perhaps, is the willingness to keep learning. Arie de Geus, former head of Royal Dutch Shell’s Strategic Planning group once said, “In the future, the ability to learn faster than competitors may be the only sustainable competitive advantage.” That ability must be embedded in culture no matter what other values the culture incorporates. A good example comes from the success and subsequent decline of Arsenal Football Club, which in the late 1990s broke with English football tradition by hiring a Frenchman to manage the team. Arsène Wenger’s on-the-pitch tactics and approach to nutrition and training overturned decades of English football culture and brought a level of domination rarely seen in professional sports. The Arsenal team of 2003-4 was unbeaten during an entire season, a feat that had not been accomplished since the late nineteenth century. Although the club went on to further success, other clubs gradually learned from, adopted, and refined its methods. Arsenal failed to innovate further and gradually slipped down the league table to a point where Wenger was eventually replaced.

Arsenal's (L to R) Kolo Toure, Robert Pi

The 2003-2004 Arsenal team earned the nickname the “Unvanquished” for becoming the first elite-level UK football club in more than 100 years to go an entire season undefeated—in large part thanks to its disruptive culture. Above, Kolo Toure, Robert Pires, and Ashley Cole celebrate the 2-2 tie with Tottenham that sealed the feat.

Source: ODD ANDERSEN / Staff via Getty Images

As we endeavor to strengthen Plymouth Argyle’s culture, my experience at Harding Loevner has been critical in giving me a clearer sense of what will work. At Harding Loevner, we were taking cautious steps in the dark, with nothing to give us confidence that we were on the right path. But we did learn, and that has been helpful as we try to make an Argyle culture that will enable us to achieve our vision. As such, we are approaching our task with an intentionality that would have felt presumptuous to my younger self. It starts with a more specific goal. English football is a multi-level pyramid in which especially good or poor performance brings promotion or relegation to the next level up or down in the hierarchy. At the end of 2019, a year after we had lost our spot in League One (the third level from the top), we said that in five years our goal was to be financially sustainable and playing two levels above where we were then.

To realize that vision, one of the key values we have espoused at Argyle, just as at Harding Loevner, is transparency. One difference is that our transparency extends to writing down our Vision & Values and posting them to our website. In this way, everyone at the club—as well as our supporters and sponsors—knows what the vision is and what the values are that we expect will underlie every decision. Another of our core organizational values is to be efficient and process oriented. Here, again, we are not exactly inventing the wheel. Increasingly the lessons those of us in finance and organizational science took to heart about the role of process in managing our cognitive biases have also found their way into successful sports cultures. The most famous example comes from baseball where the Oakland A’s, under general manager Billy Beane, incorporated objective data into their decision-making processes to come up with new ways to gain competitive advantage on a limited budget. Once it was widely revealed in Michael Lewis’s Moneyball, Beane’s approach influenced most of the rest of baseball, spread to basketball, and is now beginning to have an impact on English football. At Argyle, our most immediate source of inspiration has been the outrageous success of Brentford F.C., for years a lower-league club of modest means, which, under the ownership and guidance of Matthew Benham (who made his fortune successfully managing his own cognitive biases gambling on football matches) has risen to the English Premier League, the pinnacle of the football pyramid.

I could elaborate on how these and our other values trickle down via our areas of strategic focus to Argyle’s CEO’s goals and to the goals he sets for every individual. But for my purposes here, the point is just that these values and goals are written down, enabling the board to communicate to our fans how we will behave and to our staff what we ask of them. The result has been powerful. Two years into our five-year plan, we have regained our position in League One, halfway toward our goal of climbing to within a level of the overachievers at Brentford. More importantly, everyone at Argyle now knows what we are trying to achieve, what is expected of them, and the values that should underly their everyday decisions.

We are now at that critical juncture faced by any strong culture looking to endure and thrive through generational succession.

I’ve learned from Harding Loevner the kind of culture that leads to sustained success. I’ve learned from Plymouth Argyle how impactful transparency and communication can be in cultivating that culture. Harding Loevner has reached the age where it can no longer rely on the people who made up the founding generation as its cultural torchbearers. Over a decade ago, we began laying groundwork for the transition of ownership and management of the firm from that generation to the next. We are now at that critical juncture faced by any strong culture looking to endure and thrive through generational succession. As the people in whom the culture is most embodied prepare inevitably to move on, they have no choice but to write more of it down. We early settlers will need to be more transparent (at the risk of being annoying) about what our culture has meant to us personally and to the firm’s success under our leadership—not so that it may be set in stone to be accepted immutably, but that it may be evaluated critically. Our younger colleagues may have slightly different beliefs and values. We expect them to receive the vision, turn it over in their minds and revise it so that they may carry it on as their own. It will be their responsibility to make sure that the firm’s culture enables it to serve its clients as well in future as it has since 1989.

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Out of Our Minds

The pandemic meant the stands were still empty at “Theater of Greens,” the home stadium for Plymouth Argyle this year, but the ideas were plentiful as to how to harness the theories of behavioral economics to put a more competitive squad on the field.

Endnotes

Too Much Information

Sitting on Our Asses

Compounding the Effect

Endnotes

Meme Stocks and Market Structure

Source: Bloomberg

Culture Club

Left to Themselves, Even Great Cultures Die

Source: ODD ANDERSEN / Staff via Getty Images

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Disclosures