...Notes on exponential revenue growth
While we’re on the subject of extrapolation and speculative valuations, it may be useful to address the primary driver of market strength in recent weeks – the FAANG group comprised of Facebook, Apple, Amazon, Netflix, and Alphabet (renamed from Google). From a near-term perspective, this advance has many of the features of a “short-squeeze” – in particular, the advances tend to be “jump” advances on rather light volume, as sellers back away at the same time that short investors attempt to cover by chasing the stocks higher. Still, it’s the long-term perspective that’s particularly interesting here.
We’ve always emphasized that stocks are a claim on the very long-term stream of cash flows that they will deliver to investors over time. When companies are growing very quickly, investors tend to look backward, and as a result, they often apply very high rates of expected growth to already mature companies. When valuations are already elevated, this practice can be disastrous, as investors discovered in the 2000-2002 collapse that followed the tech bubble.
On this subject, it’s notable that Apple’s revenue growth rate has slowed to an average rate of less than 4% annually over the past three years. As I detailed a few years ago, “Despite great near-term prospects, within a small number of years, Apple will have to maintain an extraordinarily high rate of new adoption if replacement rates wane, simply to avoid becoming a no-growth company. That’s not a criticism of Apple, it’s just a standard feature of growth companies as their market share expands.”
The tendency for growth to slow as company size increases is sometimes called the “law of large numbers.” This is excruciating for anyone who knows statistics, because the law of large numbers actually describes the tendency of the sample average to approach the population average as sample size increases. What people really mean is “logistic growth” – which is the tendency of growth to slow as the size of a system approaches its mature “carrying capacity.” For any logistic process, the growth rate slows as size increases, steadily falling in proportion to the amount of remaining capacity in the system.
Leading companies in emerging industries can experience spectacular growth rates because of the compound effect of rising market share in a growing sector. Let an emerging industry start from a tiny base, and grow at 30% annually for a decade, while a leading company moves from a 10% market share to a 50% market share. The company will enjoy a 10-year growth rate of 52.7% annually. But as companies become dominant players in mature sectors, their growth slows enormously. Let that mature industry double over a decade, while the company’s market share slips from 50% to 40%, and the 10-year growth rate of the company slows to just 4.8% annually.
Investors should, but rarely do, anticipate the enormous growth deceleration that occurs once tiny companies in emerging industries become behemoths in mature industries. You can’t just look backward and extrapolate. In the coming years, investors should expect the revenue growth of the FAANG group to deteriorate toward a nominal growth rate of less than 10%, and gradually toward 4%.
The chart below shows the general process at work, reflecting the relationship between market saturation and subsequent revenue growth. Here, the points are plotted based on revenue at each date as a percentage of 2018 trailing 12-month revenues. The vertical axis shows annual revenue growth over the subsequent 2-year period. Clearly, Apple is the furthest along in terms of saturation.
Growth rates are always a declining function of market penetration.
Remember that the latest point on this chart for each company is two years ago. For all of these companies, current revenues represent the far right of the graph, and the corresponding value for subsequent growth will be available 2 years from now. Again, my expectation is that most of those growth rates will slow toward 10%, and gradually toward about 4% (which reflects the structural growth rate that can be expected for U.S. nominal GDP when one assumes a moderate pickup in productivity, inflation slightly over 2%, baked-in-the-cake demographics like population growth, and limited scope for a further cyclical decline in the rate of unemployment).
Below, I’ve embedded some analysis about the dynamics of growth from a few years ago. I expect that these considerations will become increasingly relevant for the entire FAANG group in the years ahead.
Consider a very large, untapped market for some product. We can model the growth process in terms of how quickly that product is adopted by new users, whether there are any “network” effects where new buyers are attracted to the product because other people already use it, how frequently existing users replace their products, whether late-adopters come in more slowly than early-adopters because of budget constraints, how quickly the untapped market grows, and a variety of other factors.
Whether you do this sort of modeling with a spreadsheet or with differential equations, you’ll get essentially the same results. Specifically, growth rates are always a declining function of market penetration. Most strikingly, the growth rates begin to come down hard even at the point that a company hits 20-30% market penetration. Network effects accelerate the early growth, but also cause growth to hit the wall more abruptly. Replacement helps to accelerate the early growth rates too, but ultimately has much more effect on the sustainable level of sales than it has on long-term growth. In fact, if the replacement rate (the percentage of existing users that replace their product each year) is less than the adoption rate (the percentage of untapped prospects that are converted to new users), it’s very hard to keep the growth rate of sales from falling below the rate of economic growth.
The chart below gives the general picture of various growth curves and the effect that different factors can exert. The paths are less important for their actual growth rates as they are for their general profiles (below, I’ve assumed that 15% of the untapped market adopts the product each period). It may seem odd that you could get a growth rate below the adoption rate. But notice that with an adoption rate of 15% and a total potential market of 1000 units, for example, you’ll sell 150 units the first year, but the next year’s sales will only be 15% of the 850 remaining untapped prospects, so growth will actually be negative unless you have other factors contributing, such as discovery, replacement, network effects, and so forth.
To see how all of this has played out in the actual data for past market darlings, let’s take a look at several extraordinary growth companies that can now reasonably be viewed as having reached their “mature” level of market penetration: Microsoft, Cisco, Intel, Oracle, IBM, Dell and Wal-Mart. The chart below presents the combined scatter of historical revenue growth and penetration data for these companies. Again, the key feature is that growth rates are a rapidly decreasing function of market penetration.
Investors should, but rarely do, anticipate the enormous growth deceleration that occurs once tiny companies in emerging industries become behemoths in mature industries. You can’t just look backward and extrapolate.
Several years ago, I observed:
“We’ve seen very rapid adoption rates, very high replacement, and very strong network effects in Apple’s products. All of this is an extraordinary achievement that reflects Steve Jobs’ genius. I suspect, however, that investors observe the rapid adoption and very high recent replacement rate of three very popular but semi-durable products, and don’t recognize how improbable it is to maintain these dynamics indefinitely. Despite great near-term prospects, within a small number of years, Apple will have to maintain an extraordinarily high rate of new adoption if replacement rates wane, simply to avoid becoming a no-growth company. That’s not a criticism of Apple, it’s just a standard feature of growth companies as their market share expands. It’s something that Cisco and Microsoft and every growth juggernaut encounters. Apple is now valued at 4% of U.S. GDP, but then, Cisco and Microsoft were each valued at 6% of GDP at the 2000 bubble peak. Not that things worked out well for investors who paid those valuations.”
Presently, Apple is valued at 5.1% of GDP, Amazon at 4.8%, Alphabet (Google) at 4.6%, Facebook at 3.3%, and Netflix at 0.8% of GDP. That’s a total market capitalization of nearly 20% of GDP across 5 stocks. It’s worth remembering that historically, the pre-bubble norm for market capitalization to GDP, adding up every nonfinancial company in the stock market, was only about 60%. At secular lows like 1974 and 1982, the ratio fell to 30% of GDP – for the entire market.
Despite these extremes, my impression is that the FAANG stocks are not overvalued nearly to the extent that the glamour tech stocks were in 2000, when I expected that group to lose -83% of their value. I expect the Nasdaq 100 to fall by only about -57% this time around. That’s actually a big difference, because an -83% loss requires a -57% loss followed by a loss of -60% of what’s left.
My expectation for a -57% loss in the Nasdaq is also somewhat less than I expect the S&P 500 (-64%), Russell 2000 (-68%) and Dow Jones Industrial Average (-69%) over the completion of this cycle. Then again, given the severity of our projections, and the likelihood that they’ll be far from precise, those are probably distinctions without a difference.
This movie has played so many times in the historical data that we’ve practically memorized the lines. Near the end of the tech bubble, I got myself a nice bit of scorn on CNBC after Alan Abelson of Barron’s Magazine published my projections for Cisco, EMC, Sun Microsystems and Oracle – all in the range of about 15-20% of the prices where they had recently changed hands. Those projections actually turned out to be slightly optimistic.
There’s always the hope that this time it’s different.