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opportunity-solution-tree
phuryn/pm-skills
构建机会解决方案树（OST）来规划产品探索流程——将预期结果与机会、解决方案和实验进行关联。
...展开全部机会解决方案树（OST）
一个用于构建持续产品探索的可视化框架。它将预期成果与客户机遇、可能的解决方案以及用于验证这些方案的实验联系起来。
领域背景
机会解决方案树（Teresa Torres，《持续探索习惯》）是现代产品探索的支柱。它通过强制团队首先绘制机会空间图，从而防止团队过早跳到解决方案。
结构（4个层次）：
预期成果（顶层）——团队追求的可量化业务或产品成果。应为单一、明确的指标（例如，“将7天留存率提升至40%”）。该指标源自您的OKR或产品战略。
机遇（第二层）——通过研究发现的客户需求、痛点或愿望。这些是值得解决的问题——而非功能。 从客户视角进行表述：“我很难……”或“我希望……”使用“机会得分”进行优先级排序：重要性 × (1 − 满意度)（丹·奥尔森，《精益产品指南》）。将重要性和满意度标准化为0–1。
解决方案（第三层）——应对每个机遇的可行方法。针对每个机遇生成多种解决方案——不要局限于第一个想法。产品三人组（产品经理 + 设计师 + 工程师）应共同构思。“最好的想法往往来自工程师。”
实验（最底层）—— 通过快速、低成本的测试，验证解决方案是否真正解决了该机会。采用假设验证法（价值、可用性、可行性、实施风险）。优先采用“利益相关”（Alberto Savoia）的实验，而非基于主观意见的验证。
核心原则：
- 一次只关注一个结果。不要试图解决所有问题。将决策树聚焦于单一预期结果。
- 关注机遇，而非功能。“绝不要让客户来设计解决方案。优先考虑机遇（问题），而非功能。”
- 比较与对比。在做出选择之前，针对每个机会始终至少生成 3 个解决方案。避免陷入“第一个想法”的陷阱。
- 探索并非线性过程。若实验失败，请回溯重试。淘汰未经验证的解决方案，探索新分支。
- 持续更新，而非定期更新。每周根据访谈、数据分析和实验结果更新决策树。
操作指南
你正在协助一个产品团队为$ARGUMENTS 构建一个机会解决方案树。
输入要求
- 希望实现的预期成果或需要优化的业务指标
- 客户调研数据（访谈、问卷调查、数据分析、反馈）
- 可选：需要整理的现有商机或解决方案构想
流程
定义预期成果——确认或协助明确树形图顶端的单一、可衡量的成果。
梳理机会——基于提供的调研数据，识别出3-7个客户机会（需求/痛点）。将相关机会进行分组。从客户视角出发，对每个机会进行表述。
确定机会优先级——使用“机会评分”或定性评估进行排序。重点关注排名前2-3位的机会。
生成解决方案——针对每个优先级最高的机遇，分别从产品经理、设计师和工程师的角度进行头脑风暴，提出3个及以上解决方案。
设计实验——针对最具潜力的解决方案，提出1-2个快速实验方案。明确说明：假设、方法、指标、成功阈值。
可视化树形图——以清晰的分层格式呈现完整的 OST。
循序渐进地思考。内容较长时，请保存为 Markdown 格式。
延伸阅读
- 扩展型机会解决方案树
- 什么是产品探索？分步终极指南
- 产品三要素：超越显而易见
- 持续产品探索大师班（CPDM）（视频课程）
---
name: opportunity-solution-tree
description: Build an Opportunity Solution Tree (OST) to structure product discovery — map a desired outcome to opportunities, solutions, and experiments.
---
## Opportunity Solution Tree (OST)
A visual framework for structuring continuous product discovery. Connects a desired **outcome** to customer **opportunities**, possible **solutions**, and **experiments** to validate them.
### Domain Context
The **Opportunity Solution Tree** (Teresa Torres, *Continuous Discovery Habits*) is the backbone of modern product discovery. It prevents teams from jumping to solutions by forcing them to first map the opportunity space.
**Structure (4 levels):**
1. **Desired Outcome** (top) — The measurable business or product outcome the team is pursuing. Should be a single, clear metric (e.g., "increase 7-day retention to 40%"). This comes from your OKRs or product strategy.
2. **Opportunities** (second level) — Customer needs, pain points, or desires discovered through research. These are problems worth solving — not features. Frame them from the customer's perspective: "I struggle to..." or "I wish I could..." Prioritize using Opportunity Score: **Importance × (1 − Satisfaction)** (Dan Olsen, *The Lean Product Playbook*). Normalize Importance and Satisfaction to 0–1.
3. **Solutions** (third level) — Possible ways to address each opportunity. Generate multiple solutions per opportunity — don't commit to the first idea. The **Product Trio** (PM + Designer + Engineer) should ideate together. "Best ideas often come from engineers."
4. **Experiments** (bottom) — Fast, cheap tests to validate whether a solution actually addresses the opportunity. Use assumption testing (Value, Usability, Viability, Feasibility risks). Prefer experiments with "skin-in-the-game" (Alberto Savoia) over opinion-based validation.
**Key principles:**
- **One outcome at a time.** Don't try to solve everything. Focus the tree on a single desired outcome.
- **Opportunities, not features.** "Never allow customers to design solutions. Prioritize opportunities (problems), not features."
- **Compare and contrast.** Always generate at least 3 solutions per opportunity before choosing. Avoid the "first idea" trap.
- **Discovery is not linear.** Loop back if experiments fail. Kill solutions that don't validate. Explore new branches.
- **Continuous, not periodic.** Update the tree weekly as you learn from interviews, analytics, and experiments.
### Instructions
You are helping a product team build an Opportunity Solution Tree for **$ARGUMENTS**.
### Input Requirements
- A desired outcome or business metric to improve
- Customer research data (interviews, surveys, analytics, feedback)
- Optionally: existing opportunities or solution ideas to organize
### Process
1. **Define the desired outcome** — Confirm or help articulate a single, measurable outcome at the top of the tree.
2. **Map opportunities** — From provided research, identify 3-7 customer opportunities (needs/pains). Group related opportunities. Frame each from the customer's perspective.
3. **Prioritize opportunities** — Use Opportunity Score or qualitative assessment to rank. Focus on the top 2-3.
4. **Generate solutions** — For each prioritized opportunity, brainstorm 3+ solutions from PM, Designer, and Engineer perspectives.
5. **Design experiments** — For the most promising solutions, suggest 1-2 fast experiments. Specify: hypothesis, method, metric, success threshold.
6. **Visualize the tree** — Present the full OST in a clear hierarchical format.
Think step by step. Save as markdown if substantial.
---
### Further Reading
- [The Extended Opportunity Solution Tree](https://www.productcompass.pm/p/the-extended-opportunity-solution-tree)
- [What Is Product Discovery? The Ultimate Guide Step-by-Step](https://www.productcompass.pm/p/what-exactly-is-product-discovery)
- [Product Trio: Beyond the Obvious](https://www.productcompass.pm/p/product-trio)
- [Continuous Product Discovery Masterclass (CPDM)](https://www.productcompass.pm/p/cpdm) (video course)
所有文件
1 个文件安装 opportunity-solution-tree
下载技能文件并将其解压到 .claude/skills/ 目录中。
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git clone https://github.com/phuryn/pm-skills/tree/main/pm-product-discovery/skills/opportunity-solution-tree # Copy SKILL.md to your .claude/skills/ directory
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