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7 Strata Strategy

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ace3000chao
7-strata-strategy

用户在制定企业战略、思考竞争差异化、构建护城河、问"我们的战略是什么"/"如何让对手无法复制"/"我们的核心竞争力是什么"时激活。 不适用于：还没找到Product-Market Fit的早期探索阶段、纯运营效率讨论。

Overview

Publisherace3000chao
Repositorybook2startup
Skill name7-strata-strategy
Stars
93
Forks
14
Bundled files
1
LicenseMIT
Links
Skill sourceRepository
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by ace3000chao on GitHub. Read the source before you install it.

Installation

Install the 7 Strata Strategy AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/ace3000chao/book2startup/tree/master/ScalingUp-skills/7-strata-strategy
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/ace3000chao/book2startup.git /tmp/book2startup
mkdir -p .claude/skills
cp -r /tmp/book2startup/ScalingUp-skills/7-strata-strategy .claude/skills/7-strata-strategy
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable 7 Strata Strategy in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads 7 Strata Strategy on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so 7 Strata Strategy is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

7 Strata of Strategy 七层战略框架

R — 原文 (Reading)

"The 7 Strata of Strategy includes: 1. Words You Own (Mindshare) 2. Sandbox and Brand Promises 3. Brand Promise Guarantee 4. One-PHRASE Strategy 5. Differentiating Activities 6. X-Factor (10x-100x underlying advantage) 7. Profit per X and BHAG."

— Verne Harnish, Scaling Up, 第7章

I — 方法论骨架 (Interpretation)

7 Strata of Strategy是一套针对Growth Firm设计的战略框架，集成了Porter/Mintzberg/Collins等大师理论，但专为中型企业设计。

核心思想： 战略不是"我们做什么"，而是"我们在谁的心智中是谁"。7 Strata帮助你从外而内思考：先占据某个词（第一层），再围绕这个词构建7层战略护城河。

七层从浅到深：

L1. Words You Own（占据心智） 你希望在客户心智中占据哪个词？不是"我们做什么"，而是"当他们想到X时，他们第一个想到的是你"。例子：Google="搜索"，Volvo="安全"，西南航空="有趣"。

L2. Sandbox & Brand Promises（客户+承诺） 你的核心客户是谁（Juicy Red Customer）？你对他们的三个品牌承诺是什么？用什么KPI追踪你是否兑现了这些承诺？例子：西南航空承诺"低价、密集航班、有趣体验"。

L3. Brand Promise Guarantee（承诺保证） 如果你的承诺没兑现，你给客户什么保证？一个有意义的保证让你在客户心中与众不同。例子：Oracle说"如果性能不达标，赔偿$10M"。

L4. One-PHRASE Strategy（一句话战略） 用一句话说清楚你的战略，通常这个话会惹恼一部分客户。例子：Apple="封闭系统"（因此性能更好但不够开放）。

L5. Differentiating Activities（差异化活动） 你做的事和竞争对手不同。哈佛Porter说差异化来自于你选择的"少量活动"。例子：IKEA="自己组装"是差异化活动，不是成本领先。

L6. X-Factor（10-100倍优势） 这是最深的护城河——你有一个比所有竞争对手强10-100倍的底层优势。这个优势本身会消灭竞争。例子：Outback的Bloomin' Onion创造了$20亿收入，无法复制。

L7. Profit per X & BHAG（经济引擎+长期目标） 是什么经济驱动引擎让你的Profit不断提升？配合BHAG作为10-25年的方向锚点。

与其他战略框架的区别： 不像Porter的"成本领先/差异化"二分法，7 Strata提供了可操作的7个检查维度。不是选战略类型，而是构建战略层次。

A1 — 书中的应用 (Past Application)

案例1: BuildDirect的7 Strata实践

  • 问题: 2003年创立的建材电商如何在巨头（Home Depot）中找到位置？
  • 方法论的使用:
    • L1: 占据"建材DIY教育"这个词
    • L2: 目标客户是"Debby the Do-It-Herself"——想要自己装修但缺乏知识的女性
    • L3: 提供无偏见的建材内容（而非卖自家产品）
    • L5: 不打价格战，通过内容SEO占据搜索
    • L6: 10x优势是"无偏见内容+价格透明"，对手难以复制
  • 结论: 所有战略都围绕"赋能消费者自己做出好决定"
  • 结果: 年度翻倍增长，2014年运行率达$2亿

案例2: BIC的Core Competency边界

  • 问题: BIC最初只做便宜的一次性笔，后来扩张到打火机、剃须刀
  • 方法论的使用: BIC把自己的核心能力定义为"廉价一次性塑料产品"而非"制笔"
  • 结论: 这个定义让BIC能扩张到多个品类且保持竞争力
  • 结果: BIC成为$20亿市值的公司

案例3: Outback的X-Factor

  • 问题: Outback如何在红海餐饮市场建立护城河？
  • 方法论的使用: Outback的X-Factor是其招牌产品Bloomin' Onion——这道菜本身成为无法复制的护城河
  • 结论: 菜品差异化（而非餐厅装修或服务）成为最深的护城河
  • 结果: Bloomin' Onion单个产品创造$20亿收入

A2 — 触发场景 (Future Trigger) ★

用户会在什么情境下需要这个skill？

  1. 企业找到Product-Market Fit后准备Scaling — 从0到1找到了产品，下一步是怎么建立不可复制的优势
  2. 竞争对手开始模仿但不知道如何应对 — 护城河不够深，需要重新审视战略层次
  3. 战略讨论总是停留在表面 — "我们差异化"但说不清楚具体在哪个层次
  4. 进入新市场前 — 需要系统思考如何在新市场建立同样的7层结构
  5. 出售公司前 — 买家想看到清晰的战略护城河，7 Strata帮助整理战略故事
  6. 团队对战略缺乏共识 — 高管各说各话，需要共同语言

语言信号（用户的话里出现这些就应激活）

  • "我们的战略是什么"
  • "我们的护城河是什么"
  • "竞争对手抄我们怎么办"
  • "我们的差异化在哪里"
  • "我们代表什么"
  • "消费者为什么选我们"
  • "我们的X-Factor是什么"
  • "如何让品牌占据某个词"
  • "战略怎么做才能落地"

与相邻skill的区分

  • 与 bhag-goal-setting 的区别: BHAG是第7层的内容，是整个战略框架的北极星，但不是战略框架本身。BHAG回答"我们要去哪里"，7 Strata回答"我们怎么走"
  • 与 opsp 的区别: OPSP是执行页面，7 Strata是战略思考的深度工作坊。7 Strata填完之后才会生成OPSP的内容

E — 可执行步骤 (Execution)

为skill被激活后，按以下步骤执行（建议3-5人的战略小组，用一整天工作坊完成）：

  1. Layer 1: 找词（Words You Own）

    • 完成标准: 团队列出3-5个想要占据的词，然后做市场调研验证哪个词还没被占据
    • 方法: 搜索"品类+词"看竞争对手占据了什么；用Google Keyword Planner查搜索量和竞争度
    • 判停条件: 若团队无法达成一致，说明对客户心智的理解还不够，回到客户调研

  2. Layer 2: Sandbox & Brand Promises

    • 完成标准:
      • 定义3-5个Juicy Red Core Customer画像
      • 列出对每个客户群落的3个品牌承诺
      • 设计每个承诺对应的Kept Promise Indicators（追踪KPI）
    • 判停条件: 若承诺无法被量化追踪，返回修改承诺定义

  3. Layer 3: Brand Promise Guarantee

    • 完成标准: 设计一个有意义的保证，它应该让你的承诺有差异化且有代价
    • 例子: 无条件退货、最低价保证、性能达标保证
    • 判停条件: 若保证太弱（无代价）或太强（无法承受），重新设计

  4. Layer 4-5: One-PHRASE & Activities

    • 完成标准: 用一句话描述战略，这句话应该让一部分人不舒服（说明够尖锐）；然后列出3-5个你做但竞争对手不做的差异化活动
    • 判停条件: 若一句话战略没有争议感，说明它太泛了

  5. Layer 6: X-Factor挖掘

    • 完成标准: 回答"我们有什么是竞争对手在10年内无法复制的？"——必须具体到活动或能力，不是感觉
    • 判停条件: 若X-Factor只是"产品质量好"，说明护城河不够深，回去重新思考L1-L5

  6. Layer 7: Profit Engine & BHAG

    • 完成标准: 定义Profit per X（核心经济驱动指标，如Profit per Customer/Visit/Transaction）；配合BHAG作为长期方向锚点
    • 判停条件: 若Profit per X与日常运营KPI没有关联，说明经济引擎定义不清晰

B — 边界 (Boundary) ★

不要在以下情况使用此skill

  • 还没找到Product-Market Fit时 — 7 Strata是Scaling工具，不是Product-Market Fit探索工具。先确认你在做的事有人要，再来构建战略
  • 太早期的Startup（2-5人） — 战略框架需要时间来验证，太早写反而限制了探索空间
  • 纯运营效率讨论 — 这个工具用于战略差异化，不用于"怎么让运营更高效"

作者在书中警告的失败模式

  • 战略被过度复杂化 — 很多企业把7 Strata做成100页的战略文档。真正有效的战略一页纸能说清楚
  • Layer 1-2都没做好就跳到X-Factor — X-Factor是第6层，如果前面的层次还没对齐，X-Factor也是空的
  • 模仿竞争对手的Words — "我们也要成为X领域的领导者"——如果这个词已经被占据，你永远只能是第二

作者的盲点/时代局限

  • 平台经济的战略逻辑不同 — 7 Strata主要是针对产品/服务型企业的，对平台型、网络效应型的公司可能需要补充其他框架
  • AI带来的战略加速 — 今天竞争对手可以通过AI快速复制内容营销等战略，曾经的X-Factor可能变得更容易被追赶

容易混淆的邻近方法论

  • Porter's Five Forces: Porter是分析工具，告诉你行业结构；7 Strata是构建工具，告诉你如何建立差异化
  • OPSP: OPSP是执行页面，7 Strata是战略页面的内容来源。先有7 Strata工作坊，才有OPSP的内容

相关skills（阶段3填充）

  • depends-on: bhag-goal-setting（BHAG是第7层输出）
  • depends-on: brand-promises（L2 Brand Promises是战略核心）
  • composes-with: core-values（Core Values是战略的边界条件）
  • contrasts-with: opsp（OPSP是执行层，7 Strata是战略层）

审计信息

  • 验证通过: V1 ✓ / V2 ✓ / V3 ✓
  • 测试通过率: 待阶段4测试
  • 蒸馏时间: 2026-04-26
  • 示范批次: 5个示范SKILL.md之一

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the 7 Strata Strategy AI skill do?

用户在制定企业战略、思考竞争差异化、构建护城河、问"我们的战略是什么"/"如何让对手无法复制"/"我们的核心竞争力是什么"时激活。 不适用于：还没找到Product-Market Fit的早期探索阶段、纯运营效率讨论。

Why use 7 Strata Strategy on TypingMind?

Because you install it once and use it with any model. 7 Strata Strategy is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install 7 Strata Strategy in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ace3000chao/book2startup/tree/master/ScalingUp-skills/7-strata-strategy. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use 7 Strata Strategy?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with 7 Strata Strategy?

As many as you like. As long as a model supports skills, you can use 7 Strata Strategy with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the 7 Strata Strategy AI skill free?

Yes. It is published on GitHub by ace3000chao under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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