layers-product-strategy

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/layers-product-strategy

Assumes
/layers-intro
has been loaded for framework context.

Strategy is the first layer of the solution space — the point where problem space understanding converts into deliberate decisions about scope and direction. It is about choices: which user needs to serve, and which business outcomes to target.

Decisions this layer needs to make:

What is the business outcome this work serves?
Which user opportunities (needs, pains, desires) connect genuinely to that outcome?
What solution bets are we placing on those opportunities?
How do we test the riskiest assumptions cheaply?
Which bets to pursue first, and why?

Methods:

Method	When
Opportunity Solution Tree (OST) (Teresa Torres)	Default. Makes outcome → opportunity → solution → experiment connections explicit. Good for ongoing discovery cadences.
Impact mapping (Gojko Adzic)	B2B products with multiple stakeholders who each need to change behaviour.
Jobs portfolio mapping	Many job stories; need to decide which to target. Map by frequency, severity, and strategic fit.
Now / Next / Later roadmap	Team needs a shared timeline view of bets. Lightweight communication tool.
Kano analysis	Candidate features; understand which are hygiene (expected), performance (more is better), or delight (unexpected value).
HEART / North Star (Google / Amplitude)	Clarity on which outcome metric to target. HEART structures the choice; North Star distils to one metric representing core value.
Wardley mapping (Wardley)	Positioning depends on where capabilities sit on the evolution curve. Build/buy/partner decisions; spotting competitive moves.
Bundling / unbundling (Christensen)	Should this product own more of the workflow, or own one job precisely? Competitive positioning lens for established markets.
NPE Canvas	Consumer products: identify the Narrative (core user behaviour being tapped), Primitive (minimal atomic interaction), and Enablers (amplifying features).
Critical User Journeys (CUJs) (Google / Reforge)	Which flows to prioritise. A CUJ is the minimal path to realise core product value. Types: high-traffic, high-revenue, or metric-critical.

Default: Opportunity Solution Trees.

Quality signals — what good looks like:

The desired outcome is measurable, meaningful, and bounded — not "grow the product"
Every opportunity in the tree connects to that outcome; unconnected needs aren't in this tree
Every solution bet has a named assumption — what would have to be true for this to work?
Every prioritised bet has an experiment that's the smallest possible way to validate the core assumption
The tree shows options, not one inevitable path; multiple bets per opportunity

假设已加载
/layers-intro
以获取框架背景信息。

战略是解决方案空间的第一层——将问题空间认知转化为关于范围和方向的审慎决策的节点。核心在于选择：服务哪些用户需求，瞄准哪些业务成果。

本层需要做出的决策：

这项工作要达成的业务成果是什么？
哪些用户机会（需求、痛点、诉求）能真正与该成果关联？
针对这些机会，我们要押注哪些解决方案？
如何低成本测试风险最高的假设？
优先推进哪些赌注，原因是什么？

方法：

方法	适用场景
Opportunity Solution Tree (OST) (Teresa Torres)	默认方法。明确呈现成果→机会→解决方案→实验的关联。适用于持续的探索流程。
Impact mapping (Gojko Adzic)	涉及多个利益相关方且各方均需改变行为的B2B产品。
Jobs portfolio mapping	拥有大量用户任务故事，需决定瞄准哪些任务。按频率、严重程度和战略契合度进行映射。
Now / Next / Later roadmap	团队需要对赌注有统一的时间线视图。轻量化沟通工具。
Kano analysis	候选功能；明确哪些是必备型（预期具备）、绩效型（越多越好）或魅力型（带来意外价值）功能。
HEART / North Star (Google / Amplitude)	明确要瞄准的成果指标。HEART用于构建指标选择框架；North Star提炼为代表核心价值的单一指标。
Wardley mapping (Wardley)	定位取决于能力在演化曲线上的位置。用于决策自研/采购/合作；识别竞争动向。
Bundling / unbundling (Christensen)	产品应覆盖更多工作流，还是精准聚焦一项任务？针对成熟市场的竞争定位视角。
NPE Canvas	消费类产品：识别叙事（挖掘的核心用户行为）、原语（最小原子交互）和赋能者（放大价值的功能）。
Critical User Journeys (CUJs) (Google / Reforge)	优先推进哪些流程。CUJ是实现核心产品价值的最小路径。类型：高流量、高收入或指标关键型。

默认方法：Opportunity Solution Trees。

质量信号——优秀的战略具备以下特征：

预期成果可衡量、有意义且边界清晰——而非“发展产品”这类模糊表述
树中的每个机会都与该成果关联；无关需求不会纳入此树
每个解决方案赌注都有明确的假设——要让该方案奏效，哪些前提必须成立？
每个优先级赌注都有最小化的实验方案，用于验证核心假设
树呈现的是多种选项，而非唯一必然路径；每个机会对应多个赌注

Guided session

引导式会话

Tell me what business outcome you're working toward and what user needs you have, or say "guide me" to start an OST session.

Ask: "Where should I capture the work from this session?" (see

/layers-intro

for options)

Ask: "Do you have job stories or user needs to work from, or are we building strategy from an informal understanding of the user?" Note explicitly that strategy built without grounded user needs is a bet on assumptions.

Also ask: "Is this a new product, a new feature on an existing product, or a strategic review of something in market?"

Phase 1 — Define the desired outcome

The business result this work is trying to move. Not a feature, not a vanity metric — a genuine outcome that matters to the business.

Push toward specificity:

Not "grow the product" but "increase users who activate in the first 30 days"
Not "improve retention" but "reduce churn among users active 3–6 months"

A good outcome is measurable, meaningful, and bounded. If the team has multiple outcomes in mind, choose one for this tree.

Phase 2 — Map the opportunities

Opportunities are user needs, pains, and desires that connect to the desired outcome. Not every user need belongs in this tree — only those where serving the need moves the business outcome.

Express each as a job story. Then ask: "If we served this need well, would it move the desired outcome? How?"

Build from broad to specific — specific opportunities are closer to actionable. Ask whether there are sub-opportunities within any given opportunity.

Phase 3 — Generate solution bets

For each prioritised opportunity, generate bets. These are lightweight hypotheses, not specifications.

Format: "We could [solution], which we believe would [serve the opportunity] because [reasoning]."

For each bet: What assumption is it most dependent on? Are there simpler ways to serve the same opportunity? Generate multiple bets per opportunity — resist early convergence.

Phase 4 — Identify experiments

For the most promising bets: what's the cheapest way to find out if the bet is right? Prototypes, fake door tests, concierge experiments, customer interviews about a specific scenario, data analysis. Days rather than months.

Phase 5 — Build the strategy diagram

Generate a strategy tree: desired outcome at the top, branching downward through opportunities, solution bets, and experiments. Top-to-bottom orientation — the hierarchy reads as dependency, not sequence. In Mermaid:

graph TD

Ask: "Does this tree reflect your current thinking? Branches missing, connections wrong?"

Phase 6 — Prioritise the bets

Choose which bets to pursue first:

Opportunity size — how many users, how often, how severely?
Assumption risk — how uncertain is the core assumption?
Effort — cost to build or test
Reversibility — how hard to undo if it doesn't work?

Start with high opportunity size, manageable assumption risk, and a clear experiment path — not necessarily the most ambitious.

告诉我你正在努力达成的业务成果以及你掌握的用户需求，或者说“引导我”来启动OST会话。

提问：“我应该在哪里记录本次会话的成果？”（可查看

/layers-intro

获取选项）

提问：*“你有用户任务故事或用户需求作为基础，还是要基于对用户的非正式认知来制定战略？”*需明确指出：未基于扎实用户需求制定的战略本质是对假设的赌注。

另外提问：“这是新产品、现有产品的新功能，还是对已上市产品的战略复盘？”

第一阶段——定义预期成果

这项工作试图推动达成的业务结果。不是功能，不是虚荣指标——而是对业务真正重要的成果。

力求具体：

不说“发展产品”，而是“提升30天内完成激活的用户数量”
不说“提升留存”，而是“减少活跃3-6个月用户的流失率”

优秀的成果具备可衡量、有意义、边界清晰的特点。如果团队有多个成果目标，为本次战略树选择其一即可。

第二阶段——映射机会

机会是与预期成果相关的用户需求、痛点和诉求。并非所有用户需求都要纳入此树——只有满足后能推动业务成果的需求才需纳入。

将每个机会表述为用户任务故事。然后提问：“如果我们很好地满足了这个需求，是否会推动预期成果？如何推动？”

从宽泛到具体逐步构建——具体的机会更接近可落地的行动。询问每个机会是否包含子机会。

第三阶段——生成解决方案赌注

针对每个优先级机会，生成赌注。这些是轻量化假设，而非详细规格。

格式：“我们可以[解决方案]，我们认为这将[满足机会需求]，因为[推理依据]。”

针对每个赌注：它最依赖的假设是什么？是否有更简单的方式满足同一机会需求？为每个机会生成多个赌注——避免过早收敛。

第四阶段——确定实验方案

针对最具潜力的赌注：用最低成本验证赌注是否正确的方式是什么？原型测试、假门测试、礼宾式实验、针对特定场景的用户访谈、数据分析。以天为周期，而非数月。

第五阶段——构建战略图

生成战略树：顶部为预期成果，向下分支为机会、解决方案赌注和实验。采用自上而下的结构——层级代表依赖关系，而非顺序。使用Mermaid语法：

graph TD

。

提问：“这棵树是否反映了你当前的想法？是否缺少分支或存在错误关联？”

第六阶段——优先级排序赌注

选择优先推进的赌注：

机会规模——覆盖多少用户，发生频率，严重程度如何？
假设风险——核心假设的不确定性有多高？
投入成本——开发或测试的成本
可逆性——如果无效，撤销的难度有多大？

从机会规模大、假设风险可控且有清晰实验路径的赌注开始——不一定是最具野心的赌注。

Completion

交付成果

Produce:

Desired outcome
Opportunity tree — Mermaid diagram
Prioritised solution bets — top 2–3, with the experiment for each
Deferred bets — other bets worth returning to
Open questions — assumptions untested, needs not yet grounded in evidence

Close with: "The solution bets chosen here define the scope of what needs to be designed. Next: define the conceptual model — the objects, relationships, and vocabulary those solutions will work with. Run
/layers-conceptual-model
."

If user needs were weak or assumed: "This strategy is built on assumed needs. Plan to validate them before committing to build."

生成：

预期成果
机会树——Mermaid图表
优先级解决方案赌注——排名前2-3的赌注，附带每个赌注的实验方案
暂缓赌注——值得后续回归的其他赌注
待解决问题——未验证的假设、尚未有证据支撑的需求

收尾提示：“此处选择的解决方案赌注定义了需要设计的范围。下一步：定义概念模型——解决方案将涉及的对象、关系和术语。运行
/layers-conceptual-model
。”

如果用户需求薄弱或仅为假设：“本战略基于假设的用户需求制定。建议在投入开发前先验证这些需求。”