Mckinsey Research Methodology logo

Mckinsey Research Methodology

Community
MichaelRochonnn
mckinsey-research-methodology

在商业研究或咨询项目中,快速启动公司研究、识别数据异常值确定研究方向、以及寻找行业最佳实践。适用于需要迅速了解目标公司、诊断问题根源、或快速提升组织表现的分析场景。

Overview

PublisherMichaelRochonnn
Repositorymckinsey-bcg-consulting
Skill namemckinsey-research-methodology
Stars
77
Forks
16
Bundled files
Instructions only
Links
  • 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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Mckinsey Research Methodology 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/MichaelRochonnn/mckinsey-bcg-consulting/tree/main/mckinsey-research-methodology
  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/MichaelRochonnn/mckinsey-bcg-consulting.git /tmp/mckinsey-bcg-consulting
mkdir -p .claude/skills
cp -r /tmp/mckinsey-bcg-consulting/mckinsey-research-methodology .claude/skills/mckinsey-research-methodology
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mckinsey Research Methodology 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 Mckinsey Research Methodology 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 Mckinsey Research Methodology 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.

麦肯锡研究方法论:快速启动与深度诊断

何时使用

以下研究场景立即应用:

  • 需要迅速了解一家公司并展开研究
  • 针对某问题收集大量数据后需要确定研究方向
  • 存在不良表现需要快速医治或提升至行业领先水平
  • 进行企业尽职调查、竞争分析或投资分析

模块一:从年报开始的公司快速研究

执行步骤

  1. 获取年报

    • 优先渠道:公司官网投资者关系页面
    • 备用渠道:证券交易所、金融数据终端
  2. 阅读管理层陈述

    • 重点部分:"股东信息"或"董事长寄语"
    • 关键态度:带着怀疑态度阅读
  3. 提取战略信息

    • 上一年度表现评估
    • 管理层对未来发展方向的期望和战略
  4. 浏览财务指标

    • 股票价格
    • 收益
    • 每股收益
  5. 研究业务架构

    • 业务单元和生产线
    • 高管名单
    • 办公地点和生产设备分布
  6. 深入数字分析

    • 完成上述步骤后开足马力研究数字
    • 年报财务数据背后包含大量信息

模块二:数据异常值识别与深度研究

执行步骤

  1. 数据收集

    • 针对问题的某一个方面收集大量数据
  2. 计算机辅助分析

    • 利用工具进行快速分析处理
  3. 计算关键指标(以销售为例)

    • 输入每个销售人员过去3年的平均销售额
    • 除以该销售人员的交易次数
    • 得到每次交易的平均销售额
  4. 数据录入与排序

    • 录入分析表
    • 从低到高进行排列
  5. 识别异常值

    • 查看最好和最差的两三个数
    • 特别好或者特别差的数据点
  6. 原因分析

    • 找出数据异常的根本原因

关键洞察:异常值代表很有意义的研究领域,一旦找出原因,研究就走上顺利轨道

模块三:行业最佳实践识别与内部推广

核心原则

"人外有人,天外有天"——商业领域也不例外

执行步骤

  1. 确定标杆

    • 找到行业里表现最好的对象
  2. 模仿策略

    • 模仿表现最好的对象的做法
    • 这是医治不良表现的速效药
  3. 创造性获取方法

    关键限制:在图书馆找不到最佳经验,需要创造性思考

    外部渠道:

    • 与行业里其他人交流
    • 供货商、顾客、华尔街分析师、商学院同学
    • 注意:竞争对手不会告诉你秘诀

    内部渠道:

    • 在公司里寻找最佳经验
    • 识别某个人、某个团队、某个部门的表现最好
  4. 分析成功因素

    • 找出内部最佳表现的原因
  5. 推广计划

    • 思考怎样将他们的经验推广到整个公司

方法组合应用

研究阶段主要方法输出
初步扫描年报研究法公司战略方向、财务健康、组织架构概览
问题诊断异常值识别法需要深入调查的高/低绩效案例及根本原因
解决方案最佳实践法经过验证的可复制改进方案

关键检查清单

  • 年报获取是否完整?管理层陈述是否带着怀疑态度阅读?
  • 数据量是否足够识别有意义的异常值?
  • 最佳实践来源是否同时考虑了外部标杆和内部优秀单元?
  • 最佳经验是否评估了可复制性与特殊情境因素?

Frequently asked questions

What does the Mckinsey Research Methodology AI skill do?

在商业研究或咨询项目中,快速启动公司研究、识别数据异常值确定研究方向、以及寻找行业最佳实践。适用于需要迅速了解目标公司、诊断问题根源、或快速提升组织表现的分析场景。

Why use Mckinsey Research Methodology on TypingMind?

Because you install it once and use it with any model. Mckinsey Research Methodology 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 Mckinsey Research Methodology in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/MichaelRochonnn/mckinsey-bcg-consulting/tree/main/mckinsey-research-methodology. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Mckinsey Research Methodology?

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 Mckinsey Research Methodology?

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

Is the Mckinsey Research Methodology AI skill free?

It is published on GitHub by MichaelRochonnn. Check the repository for licensing terms. 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇