Hello, and welcome to The Investor’s Bookshelf.Today’s book is The Investor’s Mind Map, with the subtitle Capturing Tenfold Investment Opportunities in a Decade. From the title alone, you can tell this is a book about investment thinking.
In it, the author likens the capital market to a vast and ever-changing ocean. Institutional and individual investors navigating this market are like fishermen venturing out to sea. These fishermen must not only survive the raging waves but also strive to locate the largest schools of fish.
In this process, experience is undeniably vital. Seasoned fishermen know where the big fish are, understand the patterns of their movement, and naturally enjoy greater harvests. In contrast, inexperienced fishermen—no matter how many times they cast their nets—may end up with nothing.
Viewed in this light, The Investor’s Mind Map can be seen as a “nautical chart” drawn by an experienced veteran of the seas, guiding participants through the capital market. Even those uninterested in investing can find inspiration from this “sea map.” After all, capital is inherently shrewd: by following its flow, one can spot the areas of the market where value is growing most rapidly, as well as trace the underlying rhythms of the economy. In a sense, to understand the mind map in an investor’s head is to understand the value landscape of the economic world we live in.
The author, Jiang Meijun, is a seasoned financial professional with both a strong theoretical foundation and extensive practical experience. He earned his bachelor’s and master’s degrees at Peking University’s Guanghua School of Management, and after graduation devoted himself to capital market investment. Over the past two decades, he has served as general manager of a life insurance company, president and chairman of a securities firm, and managed funds exceeding hundreds of billions of yuan.
In this book, Jiang and his team studied companies in the U.S. and Chinese capital markets whose stock prices rose more than tenfold between 2011 and 2021, seeking to uncover the value growth logic behind them. Their analysis revealed that these “tenfold in ten years” companies were almost never driven purely by speculative hype. Instead, they all rested on a solid foundation of value growth—broadly falling into four categories: snowballing, mudslide, high-cycle, and hard technology.
Among them, “high-cycle” companies are largely influenced by the macroeconomic environment. Accurately predicting macro trends—and understanding how these trends will shape the prospects of cyclical industries—requires years of close observation and hands-on experience. For most people, this is extremely difficult.
That is why, in today’s discussion, we will focus on the remaining three categories: snowballing, mudslide, and hard technology.
Next, based on the author’s research, I will walk you through the value growth logic of these three types of companies—and why they are fertile waters where “tenfold in ten years” big fish are more likely to be found.
(Note: This article shares only the author’s perspectives on company value growth and does not constitute investment advice. Investing carries risks; proceed with caution.)
I. Snowballing
The first category is what we call the “snowball.” The term was popularized by none other than Warren Buffett, the Oracle of Omaha. He defines a snowball-type company as one capable of generating steady and sustained returns over a long period of time. A classic example is Coca-Cola—a company in which Buffett took a large position in 1988 and has held ever since.
According to capital market data, between August 2010 and March 2021—roughly a decade—Coca-Cola’s share price rose about 280%, slightly outperforming the S&P 500. But over the longer term, from March 1986 to March 2021, Coca-Cola’s stock price soared 33-fold. Averaged out, that’s nearly doubling every year—far exceeding the S&P 500’s 16-fold increase over the same period. In those 35 years, very few companies in history have been able to maintain such high returns for so long.
Buffett often says that when investing in snowball-type companies, the snowball may start small, but if it keeps rolling for long enough, gathering more snow along the way, it will eventually become enormous. The key to building a massive snowball is to find a long hill and wet snow.
This book refines that idea for the Chinese market context.
- A long hill means the company operates in an industry that is not easily disrupted by transformational change.
- Wet snow means the company has built a strong competitive advantage within that industry—its own “brand moat.”
This may sound a bit abstract, so let’s use an example.
First, a counterexample: in the technology sector, snowball-type companies are relatively rare. That’s because the industry is prone to disruptive innovations—changes so fundamental they alter consumer behavior entirely. For instance, once smartphones reached a certain level of maturity, very few people still used pagers. Such product replacements are disruptive in nature. Similarly, many chips or smartphones are replaced by newer models every year, making older ones obsolete. The tech industry’s competitive environment is highly uncertain, and a strategy of “unchanging in the face of change” can quickly be overtaken by newcomers.
So, what industries are more likely to produce snowball-type companies? According to the author, they often appear in the consumer goods sector—products tied closely to people’s everyday needs: food, beverages, clothing, stationery, and so on.
Unlike technology, consumer goods rarely face disruptive innovation. Milk, flour, cooking oil, eyeglasses, pens, toilet paper—each corresponds to a basic consumer need. They do not require frequent updates like smartphones or computers. These basic daily necessities are the “long hill” we mentioned earlier. And in a rapidly growing economy, meeting the everyday needs of hundreds of millions of people is not a small matter—it is a vast market.
In the consumer goods sector, wet snow refers to becoming the leading brand within a specific niche. Why? Because consumer habits tend to favor established names. Most consumers cannot professionally evaluate product details, so they trust and prefer leading brands. Once a brand becomes the top player in its niche, it attracts even more customers, who, like snowflakes, make the snowball grow larger and larger.
The data shows that in recent years, the “head effect” in consumer goods has become more pronounced. In industries like liquor or soy sauce, overall market growth has been slow, but the leading companies have grown rapidly. The sector is concentrating toward its leaders, and this trend has been strengthening.
In summary, snowball-type companies are often leading players in specific consumer goods niches. Buffett’s Coca-Cola—a head brand in its category—is a prime example.
Although the author’s research focuses largely on China, there are valuable lessons for U.S. investors as well. In recent years, a notable trend in China’s consumer goods sector has been the rise of “new consumption built on new infrastructure.” Here, “new infrastructure” includes not only improved transportation systems but also new communications and transaction networks powered by mobile internet technology.
This new infrastructure has enabled innovative logistics solutions such as cold chain delivery, instant delivery services, and “front warehouses” that store products near residential communities for rapid fulfillment. Such advancements allow fresh, ready-to-consume goods—like sashimi-grade fish, ready-to-eat bird’s nest, and frozen desserts—to reach a broader audience, free from some traditional time and distance constraints.
New infrastructure has also created new consumer platforms—e-commerce, mobile payment systems, social media—that accelerate word-of-mouth marketing. It has enabled high-emotion, high-social-value products—such as mystery boxes or aesthetically pleasing small appliances—to go viral almost overnight.
These developments mean that brand moats in the consumer sector are no longer as unassailable as before. Many emerging consumer brands have been able to acquire large user bases in a short time and rise to the top of their industries.
As we’ll see, the next category—the “mudslide” type—also relies on new infrastructure. But the way new infrastructure works for snowball companies and mudslide companies is different. For snowball companies, new infrastructure can speed up the growth of the snowball. For mudslide companies, however, new infrastructure is the very foundation that allows them to become a “mudslide” at all—because their defining trait is a new business model built entirely on that foundation.
And that is where we’ll turn next.
II. Mudslide
According to the book, the most prominent “mudslide”-type business model is the platform business model.
We are all familiar with platforms. Think of search engines like Google and Baidu; open mobile operating systems such as Apple’s iOS and Google’s Android; communication platforms like WhatsApp and Telegram; social platforms like Weibo and X; content platforms such as TikTok; and a range of lifestyle service platforms. At their core, these business models connect producers and consumers through an online platform, enabling the exchange of goods, services, and information.
Take Apple as an example. It does not merely manufacture smartphone hardware and software. Rather, it builds a platform around the phone. Through iOS, iTunes, and the App Store, the iPhone connects software developers with users, providing a direct space for transactions. Google’s Android system follows the same logic.
Beyond Apple and Google, many other platforms—though operating in different industries—share the same business model. Amazon, Taobao, and eBay connect product sellers with buyers; ride-hailing apps like Didi link passengers with drivers; Airbnb connects homeowners with short-term renters; YouTube and TikTok connect content creators with audiences. This is what defines a platform.
From 2011 to 2021, many of the U.S. stocks that rose five- to tenfold owed their growth to platform-based business models. Well-known examples include Amazon, Netflix, Apple, and Google. For instance, Google’s share price was $295 on March 9, 2011. By March 9, 2021, it had climbed to $2,040—a 5.9-fold increase—with a peak of $2,145, or 7.27 times the original price.
The author likens the value growth of platform companies to a mudslide—once it starts, it’s unstoppable.
For one, user growth after a platform’s launch is often far faster than in traditional businesses. A conventional company might take decades to build a user base in the hundreds of millions. A platform might take only a year or two—or even less. Kuaishou reached 100 million users in two years; WeChat took 433 days; TikTok did it in about a year.
The growth of a platform’s value mirrors its user growth. The leap from zero to one user and from one to a hundred million users often happens in an almost seamless surge. Apple’s valuation, for example, jumped from $10 million at inception to $1 billion just three years later, and then began its climb toward $2 trillion. Amazon followed a similar trajectory after its IPO. Pinduoduo, founded in 2015, listed on the U.S. market by 2018 with a valuation of $24 billion, and by 2020 had exceeded $100 billion.
So why do platforms experience such “mudslide”-like value growth?
From the book, two key reasons emerge: low customer acquisition costs and network value growth.
1. Low customer acquisition costs
Compared to traditional companies, internet-based platforms can acquire customers far more cheaply, thanks to the rapid spread of information online. Freed from geographical and time constraints, platforms can reach users at a fraction of the cost of physical storefronts or offline advertising. Sometimes, a few viral marketing lines or endorsements from key influencers are enough to trigger explosive growth. This is a universal technological dividend of the internet era.
2. Network value growth
This means the value an individual derives from a platform increases as the platform’s network expands. Take a platform like Yelp: with only a handful of business reviews, it’s unlikely to attract many users. But as the number of reviews grows, more people visit the platform, which encourages even more reviews, which in turn draw even more users. This creates a positive feedback loop that drives platform revenue.
Ride-hailing and e-commerce platforms follow the same pattern. For Uber, the more users it has, the more drivers it attracts; the more drivers available, the faster passengers get rides, which increases passenger loyalty and usage. More transactions mean higher revenue.
When these two factors—low acquisition costs and network value growth—combine, they create a powerful outcome: as the platform expands, revenue grows much faster than costs, leading to exponential profit growth. This is why platform companies can achieve “mudslide”-style surges in value.
But there is a flip side. Without a substantial user base, a platform cannot leverage its low-cost expansion advantage, nor generate meaningful revenue. As some books on platform business models put it: “Go big or go home.” A small platform is practically meaningless—the real power of the model only emerges at massive scale. Moreover, because platform expansion produces exponential profit growth, a single dominant platform can generate far more profit than two mid-sized platforms combined. For both the company itself and the “invisible hand” of the market, platform competition tends toward a winner-takes-all outcome.
This is why, when a platform company enters a given sector, it can be as transformative as a mudslide rushing down a mountain—completely reshaping the industry landscape and rewriting the competitive order. This, the author argues, is the deeper reason for likening the platform business model to a mudslide.
III. Hard Technology
We have now covered the first two categories—“snowball” and “mudslide.” The third category is hard technology.
While mudslide-type companies thrive on new business models built atop emerging technologies, hard technology companies focus on the technologies themselves. Their core mission is achieving breakthroughs in technological research and development, rather than in applications or business models.
A defining characteristic of hard technology companies is exceptionally high R&D spending. In 2019, for example, a research institution analyzed the annual financial reports of 3,088 A-share listed companies and compiled a “Top 100 R&D Intensity” ranking, based on the proportion of R&D expenditure to operating revenue. The vast majority of companies on this list came from three sectors: computer technology, electronics, and biopharmaceuticals—home to many firms engaged in AI, 5G, semiconductor manufacturing, and new drug development.
In 2018, the average R&D-to-revenue ratio for companies on the list was 17%, compared to just 2% for the A-share market as a whole. The top three companies invested a staggering 55%, 48%, and 43% of revenue, respectively, into R&D—nearly half their income. This underscores the heavy R&D commitment of hard technology companies.
When a company’s R&D investment leads to a breakthrough in a key technology, it can attract massive capital inflows. After multiple rounds of technical iteration and financing, the launch and commercialization of a new product can trigger an industry-wide upgrade. The leading company driving that upgrade may see returns hundreds, thousands, or even tens of thousands of times its initial R&D investment.
However, technological innovation carries high uncertainty. For most investors, hard technology is a high-barrier, high-risk category. The author cautions that investing in this space ideally requires some technical background; without it, one risks getting lost in a sea of complex information and making poor investment judgments.
History offers plenty of cautionary tales. The global dot-com bubble around 2000—spanning China, the U.S., and beyond—inflicted heavy losses on investors. When the bubble burst, many former tech darlings such as Amazon, Cisco, and Yahoo saw their stock prices collapse by more than 90%. The bubble was fueled by excessive optimism toward internet stocks, compounded by the herd effect, which pushed valuations far beyond sustainable levels.
Among those hit hard were not only amateur investors but also seasoned professionals who misjudged the market. Yet professional investors typically enter hard technology fields prepared for high failure rates. They understand that most bets will fail, but a single success can yield extraordinary returns, more than offsetting losses. Those with substantial capital therefore adopt diversified investment strategies to improve their overall odds.
The book cites several companies and investors with standout track records and lists the technology domains they continue to monitor:
- Catherine Wood, founder of U.S.-based Ark Invest, focuses on electric vehicles, AI automation, deep learning, streaming media, 3D printing, digital wallets, next-generation DNA sequencing, and biotechnological R&D efficiency.
- Mary Meeker, partner at Bond Capital and former Morgan Stanley chief analyst, emphasizes technology trends shaped by the COVID-19 pandemic—cloud-based work, enterprise digital transformation, and the convergence of technology and healthcare.
In China:
- Tencent concentrates on two main areas: artificial intelligence (particularly AI-powered smart healthcare) and the “Immersive Internet,” which founder Pony Ma envisions as a future where online and offline experiences fully integrate, physical and digital blend, and human-computer interaction becomes richer and more varied.
- Huawei focuses on AI and new energy, with nine key challenges and research directions for the next decade, including 5.5G mobile networks, supercomputing power, industrial internet, and smart energy networks.
The author provides a full list of such focus areas in Chapter 13 of the original book for readers who want to explore further.
From this overview, we can see that fields such as AI, smart healthcare, and new energy are the “big-wave, big-fish” waters where many professional investors cast their nets. As mentioned earlier, the common strategy in hard technology is to spread investments widely across promising fronts.
The author believes that successful technology investors possess a sharp sense for future trends—not only in spotting the big picture but also in identifying nuanced opportunities within it. The outsized returns they earn are the market’s reward for this foresight.
For most investors, identifying a hidden gem at the earliest stage may be difficult. However, in practice, correctly selecting one or several promising innovation tracks and placing multiple bets can lead to returns approaching the industry average. Over the past decade, the overall return rate of the technology sector in both China and the U.S. has outperformed the broader market.
The book also outlines quantitative strategies used by professional investors to identify “seed players” in the hard technology space. While we won’t dive into those details here, they provide further insight into how to navigate this high-risk, high-reward arena.
IV. Conclusion
We have now explored the value growth logic behind the three categories of companies most likely to produce the “tenfold in ten years” giants:
- Snowball companies—operating in industries resistant to disruption, fortified by strong brand moats.
- Mudslide companies—expanding at low cost while benefiting from network value growth.
- Hard Technology companies—achieving breakthroughs in critical technologies through heavy R&D investment, leading to outsized returns.
As you may have noticed during this discussion, while the book uses “tenfold in ten years” stock price growth as its entry point, its real focus is not on predicting stock prices or telling us which stocks to buy. Rather, the author aims to present an investor’s value map—guiding us to explore what kinds of companies can grow faster and more sustainably than others.
This perspective is also rooted in the author’s own investment philosophy: speculation cannot last; investing should be approached with the mindset of an industrialist—growing together with outstanding listed companies over the long term.
You might say, “Isn’t that just Buffett’s famous value investing?” Indeed, the underlying logic is still value investing, as championed by Benjamin Graham—the “Dean of Wall Street”—who taught that buying stocks means buying companies. Yet the author’s framework is broader than Buffett’s.
Buffett’s approach largely centers on the snowball strategy we discussed earlier. He once summed up his investment principles in six words: simple, traditional, and easy. For decades, most of his holdings have been U.S. financial and traditional stocks. The only major tech company he has heavily invested in is Apple—not because of its technological prowess, but for its strong management and robust cash flow. In Buffett’s eyes, Apple is held as if it were a traditional consumer goods company.
A book dedicated to value investing models, The Tale of Buffett and Munger, notes that in the decade following the financial crisis, Buffett’s returns not only trailed the S&P 500 but also significantly underperformed the NASDAQ.
Taken together with today’s book, we might recognize something important: in our fast-changing era, capturing tenfold-in-ten-years opportunities demands more from us than ever before. Beyond the endurance to “be a friend of time” championed by value investing, we also need the stamina to race against time and the vision to see through market cycles.
Only then can we navigate the ocean of capital and identify those snowball, mudslide, and hard technology companies with the greatest potential for value growth.
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