On a weekend afternoon, while tidying the bookshelf, I dug out Xiao Jing’s How to Quickly Understand an Industry (《如何快速了解一个行业》). To be honest, I originally bought this book out of a utilitarian mindset—I wanted to quickly build a cognitive framework for unfamiliar industries, as a reference for career choices and investment decisions. But once I really got into it, I found that what the author offers isn’t a quick-fix technique, but a systematic analytical way of thinking.
What moves me most about this book is this: it reduces the seemingly jumbled field of industry research to one clear main thread—the industry life cycle. Once you understand this, you’ll no longer feel at a loss when facing an industry.
1. What Is an Industry? First Get the “Granularity” Straight
Right at the outset, the author points out a problem that’s easy to overlook: the “industry” we usually talk about actually has quite fuzzy boundaries.
Do Southern Weekly and “Toutiao” count as the same industry? One is traditional print media, the other an algorithm-driven content platform—they’re worlds apart in form, but in essence both are information dissemination, and both can be classified under the media industry.
This brings up a key concept: granularity.
- Horizontally: soda, potato chips, pet food, and personal-care products can either be subdivided into separate industries such as food and beverages, pets, and daily chemicals, or lumped together as “fast-moving consumer goods.”
- Vertically: the semiconductor industry chain can be broken down into three links, “design → manufacturing → packaging and testing,” each corresponding to a different subdivided industry.
Core takeaway: before researching an industry, you must first define the granularity, or else you easily run into the problem of inconsistent definitions.
Common industry classification standards include:
- National standards: the Industrial Classification for National Economic Activities (divided by primary, secondary, and tertiary industries)
- CSRC standards: the Guidelines for the Industry Classification of Listed Companies
- Commonly used in the market: the classification systems of Shenwan, CITIC, and East Money
- U.S. stock investing: GICS (Global Industry Classification Standard)
2. The Industry Life Cycle: The Industry’s “Growth Curve”
The author introduces a very valuable analytical framework—the industry life cycle theory. An industry can be divided into four stages based on its revenue:
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The root of these life-cycle characteristics lies in changes in the customer base.
The Diffusion of Innovations Theory: Who’s Using Your Product?
E.M. Rogers’s diffusion of innovations theory divides users into five types:
| User type | Characteristics | New-energy vehicle example |
|---|---|---|
| Innovators | Boldly try new concepts | The first Tesla Model S owners |
| Early adopters | Willing to take on some risk | Tech enthusiasts, environmental pioneers |
| Early majority | Enter only after word-of-mouth is validated | Seeing people around them buy one and thinking it’s good |
| Late majority | More concerns, driven by social pressure | Worried about charging stations, range, etc. |
| Laggards | Conservative, with limited information | Considering only after fuel vehicles are fully replaced |
Characteristics of the Four Stages
Introduction stage: the product is novel but not yet finalized, and only “innovators” buy in. Market prospects are unclear, and a large number of companies get funding to hype concepts. A typical example is today’s humanoid-robot industry.
Growth stage: the product breaks out of its niche; early adopters and the early majority enter; demand surges but capacity may not keep up, supply falls short of demand, and gross margins are decent. But competitors pour in, and a price war begins. The new-energy vehicle industry is at this stage.
Maturity stage: after the late majority enters, new-customer growth slows, and revenue is maintained by repeat purchases. The product is standardized, technological improvement slows, and gross margins decline. The white-goods industry has already entered the maturity stage.
Decline stage: substitutes appear in the market, and users turn elsewhere. Cost control becomes key, and only companies with a scale advantage can survive.
How to Judge the Stage? Look at Penetration
The author proposes a practical judging indicator: penetration.
Penetration = existing users ÷ potential customer base
Rules of thumb:
- When penetration reaches 15%–20%: the industry enters a rapid-improvement stage, corresponding to the growth stage.
- When penetration exceeds 35%–40%: the pace of development begins to slow, corresponding to the maturity stage.
Smartphones are a typical case: after the iPhone 4 launched in 2010, smartphone penetration broke through 20%, then surged from 22% to 40% over the following two years, leaving Nokia utterly bewildered.
3. Different Stages, Completely Different Research Focus
This is the most core view of the book’s entire first chapter: you can’t use the same method to research all industries.
| Life cycle | Core focus | Key questions |
|---|---|---|
| Introduction | Feasibility of the business model | Does the demand really exist? Can profitability be sustained? Can it be scaled? |
| Growth | Market size (scalability) | How much potential space is there? How long can the growth rate be sustained? |
| Maturity | Moat and competitive landscape | Is the defensiveness enough? Can a second curve be opened up? |
| Decline | Threat of substitutes | Where are users turning? Is there any investment value left? |
Introduction Stage: Don’t Be Fooled by Fake Demand
The worst thing to fear is failure of an industry startup. Besides estimating the market space, you must assess the feasibility of the business model:
- Does the demand really exist—not a false demand imagined by the entrepreneur
- Is profitability sustainable—can it be replicated at scale
If the business model doesn’t work, then no matter how big the imaginative space, it’s just a castle in the air. Wearable devices from back in the day, such as smart rings and Google Glass, are typical examples of “concept greater than substance.”
Growth Stage: Calculate the Market Space Clearly
At this point the industry grows fast, and the investment logic is growth. What needs attention:
- How big is the market size?
- How much room is left for penetration to improve?
- How will the competitive landscape evolve?
Maturity Stage: The Moat Matters More Than Growth
The dividend-growth period is over. The research focus is:
- Is the industry’s moat wide enough?
- Does it have the potential to “walk out a second growth curve”? (e.g., the home-appliance industry launching robot vacuums and wet-dry vacuum cleaners)
- If it enters a “stable-market cyclicalization” stage, watch the degree of supply restriction and supply-demand fluctuations
Decline Stage: Pull Out in Time
The research focus should shift to substitutes. No matter how low the valuation, it doesn’t mean it’s worth buying; there’s no need to hang yourself on one tree.
4. Investment Decisions: You Also Need to Consider the Valuation Multiple
The author reminds us that the earlier analytical dimensions (feasibility, scalability, defensiveness, profitability) mainly revolve around fundamentals. But if investment decisions are involved, you must also consider the valuation multiple.
Company market value = net profit (fundamentals) × valuation multiple
The faster a company’s performance grows, the higher its valuation multiple. Different stages apply different valuation logic:
- Introduction: VC evaluation methods
- Growth: growth-stock valuation logic
- Maturity: cyclical-stock evaluation style (if it enters the cyclical-rotation stage)
- Decline: valuations are usually very low, but that doesn’t mean it’s worth buying
5. External Factors: Keep Tracking with the PEST Framework
Besides the industry life cycle, you should also draw on PEST analysis to keep watching for changes in external factors:
- P (Political): tax policy, regulatory changes, industrial policy
- E (Economic): macroeconomy, prosperity fluctuations
- S (Social-cultural): consumption habits, population structure
- T (Technological): technological iteration, the emergence of substitutes
Key reminder: you need to view the industry with a developmental eye, continuously conducting high-frequency tracking of the industry’s prosperity to verify your analysis.
In Closing
After reading the first chapter, my biggest gain was establishing a kind of layered thinking.
In the past, when I looked at an industry, I always wanted to cover everything: business model, industry chain, market space, competitive landscape… and the result was that I looked at everything and remembered nothing. Now I understand: an industry’s different stages have completely different research focuses.
- Seeing a new concept, first ask whether it’s fake demand.
- Seeing a high-growth industry, first calculate how much room penetration has left.
- Seeing a mature industry, first check whether the moat is wide enough.
This kind of thinking framework applies not only to investing, but also to career choices and judgments about entrepreneurial directions. After all, choice matters more than effort, and underneath choice lies cognition.
The next chapter will explain “feasibility” in detail—how to judge whether a business model holds up. This is also the core question of industry research in the introduction stage.
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