scamper
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ChineseSCAMPER
SCAMPER
What this technique does
该方法的作用
Take one existing thing — a feature, a product, a workflow — and push it through seven transformation lenses in fixed order. Each lens asks a different question: what could you swap out, what could you fuse it with, what could you borrow, what could you exaggerate or shrink, what else it could do, what could you cut, what could you flip. The value is coverage: the checklist forces you past the two or three variations you would have thought of unaided and into the ones you would have skipped. It is a divergent tool for an idea that already exists, not a way to invent one from nothing.
Source: Bob Eberle, SCAMPER: Games for Imagination Development (1971), building on Alex Osborn's checklist of idea-spurring questions.
选取一个现有事物——功能、产品、工作流——按固定顺序通过七个变换视角进行推演。每个视角对应不同的问题:可以替换什么、可以融合什么、可以借鉴什么、可以放大或缩小什么、还能用来做什么、可以删减什么、可以反转什么。其价值在于全面性:这份清单能帮你跳出自己原本能想到的两三个变体,挖掘出那些你原本会忽略的想法。它是针对已有想法的发散性工具,而非从零创造想法的方法。
来源:Bob Eberle,《SCAMPER:想象力开发游戏》(1971),基于Alex Osborn提出的创意激发问题清单构建。
Workflow
工作流程
Step 1: Confirm the target
步骤1:确认目标
A valid target is an existing idea, artifact, or process: a shipped feature, a signup flow, a pricing model, a ritual your team runs. SCAMPER transforms something that already works; it cannot operate on a blank page. If the user brings no starting idea — "help me think of a product" — refuse and point them to a generative technique (a random-stimulus or free-association method) that manufactures ideas from nothing. This one needs raw material.
If the target is unclear, ask one focused question — "What's the existing idea, and what part of it is fixed versus open to change?" — then proceed.
Refuse requests to perform analytical work — "debug this", "review this code", "implement this change" — and suggest an analytical approach instead. But redesigning or reinventing such a process is a valid creative target: "reinvent our code-review ritual" is in scope; "review this PR" is not.
有效的目标是已存在的想法、产物或流程:已上线的功能、注册流程、定价模型、团队执行的常规流程。SCAMPER用于改造已可行的事物;无法在空白状态下运作。如果用户没有提供初始想法——比如“帮我构思一款产品”——应拒绝并推荐能从零生成想法的创意方法(如随机刺激或自由联想方法)。本方法需要原始素材。
如果目标不明确,先问一个聚焦的问题——“现有想法是什么,其中哪些部分是固定的、哪些部分可修改?”——再继续推进。
拒绝执行分析类工作的请求——比如“调试这个”“审查这段代码”“实现这个改动”——转而推荐分析类方法。但重新设计或重塑这类流程属于有效的创意目标:“重塑我们的代码审查流程”在范围内;“审查这个PR”则不在。
Step 2: Run all seven operations in order
步骤2:按顺序执行全部七个变换
Work the lenses in sequence — Substitute, Combine, Adapt, Modify/Magnify, Put to other use, Eliminate, Reverse/Rearrange. For each one, pull 3-4 pointed questions from and answer only the ones that actually bite against this target. Ignore the rest; the bank is a menu, not a form.
references/question-bank.mdZero hits on an operation is normal and expected. When a lens yields nothing real, mark it empty and move on — do not manufacture a variant to fill the slot.
按顺序逐一运用这些视角:Substitute(替换)、Combine(组合)、Adapt(适配)、Modify/Magnify(修改/放大)、Put to other use(移作他用)、Eliminate(删除)、Reverse/Rearrange(反转/重组)。针对每个视角,从中选取3-4个针对性问题,只回答那些与当前目标切实相关的问题。忽略其余问题;问题库是菜单,而非必填表单。
references/question-bank.md某个变换没有产出是正常且可预期的。当某个视角没有实际产出时,标记为空并继续——不要为了填补空白而编造变体。
Step 3: Collect the hits into concrete variants
步骤3:将有效产出整理为具体变体
Gather the questions that landed into named variants. Each variant states three things plainly: what changes, what it costs, and what it risks. A variant with no cost and no risk is usually a variant you have not thought through.
将得到的有效问题整理为命名变体。每个变体需明确说明三点:改动内容、成本和风险。没有成本和风险的变体通常是考虑不周全的。
Step 4: Meta-pattern scan
步骤4:元模式扫描
Look back across the run: which operations kept producing hits, and which came up dry? Concentrated production is a signal. If Substitute and Eliminate both kept biting, the idea is probably carrying weight it does not need or resting on a swappable assumption — that is where it is soft. Name the pattern explicitly; it is often more useful than any single variant.
回顾整个推演过程:哪些变换持续产出有效结果,哪些毫无收获?集中产出是一个信号。如果Substitute(替换)和Eliminate(删除)都有有效产出,说明该想法可能承载了不必要的负担,或基于可替换的假设——这就是它的可优化之处。明确命名该模式;它往往比单个变体更有价值。
Step 5: Honest ranking with next-move offers
步骤5:如实排序并提供后续行动选项
Rank the variants by real promise, say which ones are weak and why, and stop there. Offer next moves — go deeper on one variant, rerun a single operation harder, switch to a convergent technique to narrow, or stop — and let the user pick. Never push the user to commit.
根据实际潜力对变体进行排序,说明哪些变体较弱及原因,到此为止。提供后续行动选项——深入研究某个变体、针对单个变换进一步推演、切换到收敛性方法缩小范围,或停止——让用户自行选择。切勿催促用户做出决定。
Honesty mechanics
如实性机制
Operations with no bite are shown empty, not padded. Write the emptiness plainly, for example:
Eliminate: nothing left to remove — this idea is already minimal. Moving on.
A SCAMPER run where all seven operations "work" is a tell that the output is manufactured. On a real target, expect 3-5 of the seven to bite and the rest to come up empty. Showing the empty ones is what proves the run was genuine rather than retrofitted.
没有有效产出的变换需如实标记为空,而非填充内容。直白地写出空白情况,例如:
Eliminate(删除): 没有可移除的内容——这个想法已经足够精简。继续推进。
如果一次SCAMPER推演中七个变换都“有产出”,说明结果是编造的。针对真实目标,通常七个变换中有3-5个会产生有效产出,其余则无。如实展示空白的变换才能证明推演是真实的,而非事后伪造的。
What NOT to do
禁忌事项
- Don't answer every question in the bank. Pick the ones with teeth against this specific target; skip the rest without comment.
- Don't disguise the same variant under two operations. If "let users trigger it manually" shows up under both Substitute and Reverse, it is one idea, not two. Count it once.
- Don't SCAMPER a vague target. Sharpen it first. Transforming a fuzzy idea produces seven fuzzy variants.
- Don't pad empty operations. An honestly empty lens is a result, not a gap to fill.
- Don't push the user toward a decision. The technique is divergent; convergence belongs to the user.
- 不要回答问题库中的所有问题。只选择与当前目标切实相关的问题;直接跳过其余问题,无需说明。
- 不要将同一个变体伪装成两个变换的产出。如果“让用户手动触发”同时出现在Substitute(替换)和Reverse(反转)下,它只是一个想法,而非两个。只统计一次。
- 不要对模糊的目标使用SCAMPER。先明确目标。改造模糊的想法只会产生七个模糊的变体。
- 不要填充空白的变换。如实呈现空白是结果,而非需要填补的缺口。
- 不要催促用户做出决定。本方法是发散性的;收敛决策应由用户主导。
References
参考资料
- — the seven operations with pointed questions to pull from
references/question-bank.md - — a real run showing the full shape, empty operations included
references/worked-example.md
- ——包含七个变换及可选针对性问题的库
references/question-bank.md - ——包含空白变换在内的完整真实推演示例
references/worked-example.md