More Than You Know
Page 16
But what really determines a price-earnings ratio? A company’s value is a function of the market’s expectations for its growth rate and its economic returns. This fundamental concept explains why looking at growth in isolation can be so misleading. Growth can be good (when a company earns returns in excess of the cost of capital), bad (when returns are below the cost of capital), or neutral (when returns equal the cost of capital).
You must first have a clear sense of whether a company is earning appropriate returns before you can judge the effect of growth. Companies can, and do, grow their way to bankruptcy.3 Likewise, some low-growth, high-return businesses consistently carry premium valuations. Studying growth in isolation of economic returns is an invitation to failure.
Gaining a firm grasp of a company’s prospects for economic returns requires a thorough understanding of competitive strategy.4 The goal of strategic analysis is to address three fundamental questions:1. Is the company generating returns on investment above the cost of capital, or is there good reason to believe it will earn attractive returns in the future?
2. If returns do exceed the cost of capital, for how long can the company sustain its excess returns?5
3. Once a company’s returns dip below the cost of capital, what’s the probability it can stage a sustained recovery to above-required returns?
In this piece I take a closer look at the latter two questions, drawing on empirical data from the technology and retail industries to bring the points to life.
Death, Taxes, and Reversion to the Mean
One microeconomic theory that is well documented empirically is the notion that a company’s return on investment reverts to the cost of capital over time.6 The theory, and intuition, is straightforward. Companies that generate high returns attract competition and capital, which drive returns toward opportunity-cost levels. Similarly, capital flees poor-return industries—through bankruptcy, disinvestment, or consolidation—lifting returns back to the cost of capital.
Exhibit 25.1 shows this process for a sample of over 450 technology companies from 1979 to 1996. (The analysis stops at 1996 to avoid issues related to the Internet bubble.)7 Credit Suisse ranked companies by quartiles based on their cash flow return on investment (CFROI), and followed the return patterns. Because CFROI is a real, after-tax measure, the time series is unaffected by the potentially distorting shifts in interest rates and inflation.
EXHIBIT 25.1 U.S. Technology CFROI Fade
Source: HOLT.
The top group earned an average CFROI of 15 percent during the initial period and declined to 6 percent after only five years. The worst group went from 15 percent negative returns to almost zero (still well below the cost of capital) within five years. The middle two quartiles showed relative stability around cost-of-capital levels. The return gap between the highest and lowest quartiles went from 3,000 basis points at the first measurement period to just 300 basis points after ten years. While ten years is insufficient to complete the reversion-to-the-mean process, much of the progression is evident within that time frame.
Consistent with theory, attrition plays a central role in the improvement of lowest-quartile returns. Just 60 percent of the lowest-quartile companies were active after five years, as many of the poor performers went bankrupt or were acquired. This attrition creates a survivorship bias, allowing returns to rise during the decade. In contrast, 85 percent of the firms in the highest-return quartile were active after five years. Attrition rates across all quartiles tend to average out after five years.
One consistent feature across the many mean-reversion studies is that some companies (albeit not many) can and do earn persistently high returns. In the study of nearly 700 retailers from 1950 to 2001, 14 percent of the companies never earned below their cost of capital.8 Of the 1,700 technology companies in the sample from 1960 to 1996, 11 percent sustained an unblemished record of positive excess returns.
Sustaining high returns is a huge potential source of wealth. Given two companies with the same initial returns and future growth rates, the business that can sustain above-cost-of-capital returns longer will be significantly more valuable and hence will trade at a much higher valuation multiple.9
A strategic assessment of a business earning high returns should reveal the source of the excess spread—typically either a consumer or production advantage—and provide some framework to consider the longevity of that advantage. Further, some businesses (especially those in network and knowledge businesses) enjoy increasing returns as they grow.10 A company’s strategic strengths, and the economics that result, are essentially overlooked by a singular focus on growth.
I’ve Fallen and I Can’t Get Up
Stock prices reflect expectations, and the key to generating superior long-term returns is to successfully anticipate expectation revisions. An important corollary is that neither a good (i.e., high-return) business nor a bad (low-return) business is inherently attractive or unattractive. Investors need to assess the stocks of all companies versus expectations.11
In this spirit, it’s worth looking at a particular class of companies—those that have realized a downturn. Here, a downturn is defined as two consecutive years of CFROI below the cost of capital following two years of returns above the cost of capital.
This analysis is particularly important for value investors, who often buy companies that are statistically inexpensive in the hope that economic returns improve. The classic value trap is buying a cheap company that deserves to be cheap based on poor economic returns. But buying a company that is cheap because of a temporary downturn is potentially very attractive if the market does not anticipate the turnaround.
Exhibit 25.2 shows what happens to companies that realize a downturn. The sample includes almost 1,200 companies from the technology and retail sectors. The data for the two industries are strikingly similar, and not particularly encouraging: Only about 30 percent of the sample companies were able to engineer a sustained recovery. (Credit Suisse defined a sustained recovery as three years of above-average returns following two years of below-cost-of-capital results.) Roughly one-quarter of the companies produced a nonsustained recovery. The balance—just under half the population—either saw no turnaround or disappeared. Companies can disappear gracefully (get acquired) or disgracefully (go bankrupt).
EXHIBIT 25.2 I’ve Fallen and I Can’t Get Up
Technologya (%)Retailb(%)
No turnaround 45 48
Nonsustained turnaround 26 23
Sustained turnaround 29 29
a Sample of 712 companies from 1960 to 1996.
b Sample of 445 companies from 1950 to 2001.
Source: HOLT.
This analysis also shows how long companies experienced downturns. For both retailers and technology companies, roughly 27 percent of downturns lasted only two years, and for both sectors over 60 percent of downturns lasted for less than five years. In other words, the destiny of most firms that live through a downturn is determined rather quickly.
These mean-reversion and turnaround data underscore how strong and consistent competitive forces are. Most stocks that are cheap are cheap for a reason, and the likelihood that a business earning poor returns resumes a long-term, above-cost-of-capital profile is slim.
Yet the evidence that high-return persistence does occur (and the likelihood that markets misprice this persistence) suggests that investors with a strong grasp of competitive dynamics and a sufficient investment horizon have an opportunity to realize superior returns.
26
Trench Cooperation
Considering Cooperation and Competition Through Game Theory
What the Prisoner’s Dilemma captures so well is the tension between the advantages of selfishness in the short run versus the need to elicit cooperation from the other player to be successful over the longer run. The very simplicity of the Prisoner’s Dilemma is highly valuable in helping us to discover and appreciate the deep consequences of the fundamental processes involved in dea
ling with this tension.
—Robert Axelrod, The Complexity of Cooperation1
The live-and-let-live system was endemic in trench warfare. It flourished despite the best efforts of senior officers to stop it, despite the passions aroused by combat, despite the military logic of kill or be killed, and despite the ease with which the high command was able to repress any local efforts to arrange a direct truce.
—Robert Axelrod, The Evolution of Cooperation2
The War Metaphor—Death or Life?
Executives and investors often use war metaphors to describe business.3 You hear discussions of “winning the market share battle,” “make a killing,” “locking up customers,” and “outflanking the competition” all the time. In fact, the word strategy comes from the Greek strategia, which means “command of a general.”
We generally think of business, like war, as zero-sum: One side’s victory is the other side’s loss. And many games of strategy—like chess and checkers—are zero-sum. Not surprisingly, early researchers focused their efforts on the best way to play these games. That thinking also spilled over to competitive strategy, which often assumes clear-cut winners and losers. In such settings, the war metaphor certainly appears appropriate.
But is war always zero-sum? No, as one extraordinary example illustrates. The Western Front, a five-hundred-mile line in France and Belgium, was the scene of some of World War I’s most horrific fighting. Enemy units were hunkered down in trenches one to four hundred yards apart, and the payoff from a bloody encounter was often just a few yards of territory. From these dismal circumstances, cooperation—a live-and-let-live strategy—emerged. Both sides learned that there would be proportionate retaliation for any aggression, so when one side showed restraint, the other side learned to reciprocate.4
In retrospect, it looks like the cooperation got started at mealtimes. When the quartermasters brought food to the front, each side stopped shooting. From there, the soldiers arranged additional truces by shouts or signals. When battalions rotated to the front lines every eight days, the outgoing group would provide fresh troops with the details of the tacit understanding with the enemy. As one soldier leaving the front said to his replacement: “Mr. Bosche ain’t a bad fellow. You leave’im alone; ’e’ll leave you alone.”5
This story is relevant for executives and investors because it provides clues about what circumstances are necessary for cooperation to prevail over brutal competition. There are two areas where competitive cooperation is especially valuable: pricing and capacity additions. I will use some basic ideas from game theory to show how cooperation can emerge and why it’s so hard to achieve. This tool is especially useful for industries where two competitors largely dictate industry actions.
Why a Date and a Marriage Are So Different
Game theory is the study of interactions among players trying to maximize their payoff. What makes the analysis tricky is that the actions (and reactions) of the players determine the payoff. So game theory forces executives to think not only about their own choices but also how those choices will affect the choices of their competitors. Not all executives naturally put themselves in their competitors’s shoes. Consider the following quotation from the former chief financial officer of a leading multinational paper company:If you’re thinking about building a new paper facility, you’re going to base your decision on some assumptions about economic growth . . . What we never seem to factor in, however, is the response of our competitors. Who else is going to build a plant or machine at the same time?6
One simple yet powerful model in game theory is the prisoner’s dilemma.7 Consider a case where two competing commodity producers must decide whether or not to add capacity at a cyclical peak. Exhibit 26.1 shows the payoffs. If competitor B adds capacity and A does not (upper right corner), B gets a disproportionate payoff. Alternatively, if A adds and B doesn’t (lower left corner), A gets most of the spoils. If both add capacity (lower right corner), the aggregate payoff drops and neither A nor B do as well as if only they had added capacity. Finally, the industry payoffs are the highest if neither company adds capacity (upper left corner), but each company’s payoff is not as high as it would have been if only one had added capacity.
EXHIBIT 26.1 Capacity and the Prisoner’s Dilemma
Source: Author analysis.
So what should a company do if it plays the game once? Suppose you’re company A and you believe company B won’t add capacity. Your best strategy is to add capacity. But let’s say you believe company B will add capacity. Your best choice, again, is to add capacity yourself. So no matter what competitor B does, if you play the game once it pays for you to add capacity. 8 The scenario that optimizes total value, though, is for neither company to add capacity. Among other things, game theory shows that the rational solution for a company is not always the solution that is optimal for the industry in total.
In business, as in our trench warfare example, the interaction is not one time but continual. So instead of playing the prisoner’s dilemma once, companies effectively play it over and over. Cooperation is much more likely to evolve in an iterated prisoner’s dilemma because companies “learn” to work together.
In the 1980s, political scientist Robert Axelrod held a tournament to determine which strategy was most effective in an iterated prisoner’s dilemma (each game comprised two hundred moves). The strategy that won was tit-for-tat, which starts by cooperating and then uses its competitor’s prior move as its next move. Tit-for-tat assumes the best to start, provides clear negative feedback for defection, and is quick to forgive.9
Cooperative behavior in the business world breaks down, or doesn’t get started, for a host of reasons. One important factor is the quality of the signals. Sometimes companies try to signal their intentions to their competitors, but those signals are simply too ambiguous or are misread. Another factor is corporate memory. Even though two cyclical companies may compete day to day, when a top-of-the-cycle capacity addition decision presents itself, executives may treat the situation as a one-time prisoner’s dilemma because they often don’t think over long enough time scales (both past and prospective).
Price and Quantity
For three decades prior to 1974, the two afternoon newspapers serving Sydney, Australia, the Sun and Daily Mirror, raised prices consistently and in effective lockstep. The Sun led these price increases. In 1975, things changed. The Sun raised its price from 10 to 12 cents, but the Rupert Murdoch-owned Daily Mirror stood pat. The lower price allowed the Mirror to gain circulation share and hence increase its advertising rates, driving higher profits. Sun profits, in contrast, fell. Finally, in 1979, the Sun dropped its price back to 10 cents.10
This is but one example of where game theoretic analysis might have been useful. A tit-for-tat strategy would have encouraged the Sun to immediately drop its price back to 10 cents, eliminating the Daily Mirror’s payoff from choosing the negative strategy.
Executives and investors can use tit-for-tat to analyze dynamic pricing rivalry.11 Cases where these tools have been useful include the U.S. film business, the U.S. ready-to-eat cereal business, and the Costa Rican cigarette market. And while the framework is likely most relevant in cases where there are two clear competitors, it is also relevant provided there is sufficient industry concentration.
Game theory is also useful for evaluating capacity additions. In many cyclical businesses—including autos, chemicals, papers, airlines, and energy—companies tend to evaluate capacity additions at cyclical peaks. This analysis comes at the peak because demand is robust and companies typically have the financial wherewithal to add the capacity.
As noted in the earlier example, though, capacity additions by all companies dampen the payoff at the peak and lead to greater excess capacity during the ensuing trough. In their book focused on game theory, Co-opetition, Brandenburger and Nalebuff argue that the benefits of limiting supply outstrip the costs.12
The main message is that competitive markets need not be zer
o-sum. Under the right conditions, executives can see their situation as an iterated prisoner’s dilemma and make pricing and capacity decisions that maximize long-term value. Because tit-for-tat can deal with negative competitive action (e.g., price cut or capacity addition) quickly and unequivocally, it incorporates a policing component. Investors can use this framework to judge management’s thought process and degree of corporate memory.
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Great (Growth) Expectations
On the Limits of Corporate Growth
Castles in the air—they are so easy to take refuge in. And so easy to build too.
—Henrik Ibsen, Master Builder
I see more predictions of future earnings growth at high rates, not less. A few people have taken the abstinence pledge, but it’s very few.
—Charlie Munger, Outstanding Investor Digest1
Compounding and Confounding
Managers and investors generally consider growth to be an absolute good. Managers routinely discuss stretch objectives and sometimes even embrace “big, hairy audacious” goals to motivate their employees and to impress their shareholders. Growth investors routinely seek companies that promise rapid, sustainable increases in sales and earnings.
But most investors do not intuitively understand the power, and onus, of compounding. To see how you stack up, take this little quiz: