Map the second-order effects and unintended consequences of a decision
Traces what happens after the obvious first effect of a decision, who reacts and how, and which knock-on risks need a plan.
The prompt
Help me think through the knock-on effects of a decision before we make it.
The decision: [WHAT WE PLAN TO DO - e.g. "move support to a ticket-only model", "cut the travel budget 40%"]
The intended result: [WHAT WE WANT TO ACHIEVE]
Who is affected: [TEAMS, CUSTOMERS, PARTNERS, SUPPLIERS, REGULATORS]
Context: [timing, current pressures, how the organization usually reacts to change]
Steps:
1. List the first-order effects: the direct, intended results and the obvious costs.
2. For each, ask "and then what?" twice to get second- and third-order effects. Look at how people's behavior and incentives change, how customers and competitors respond, effects on other teams and metrics, and what happens over 6-18 months, not just next quarter.
3. Flag unintended consequences, especially ones that work against the goal (e.g. a cost cut that raises churn).
4. Rate each effect by likelihood and impact.
Return:
1. A consequence map as an indented list: Decision > first-order > second-order > third-order.
2. A table: Effect | Who it hits | Order (1st/2nd/3rd) | Likelihood | Impact | Positive or negative | Early warning sign.
3. The top 3 risks, each with a way to reduce it or a change to the decision's design.
4. What to measure after launch to catch problems early.
Rules: keep it plausible and specific to my situation; label speculation as such. Don't invent figures; mark any estimate as [ESTIMATE].
Highlighted [brackets] are blanks to replace with your own details.
Fill in the blanks and use this promptMore Thinking & Decisions prompts
What to fill in
- WHAT WE WANT TO ACHIEVE
- TEAMS, CUSTOMERS, PARTNERS, SUPPLIERS, REGULATORS
- ESTIMATE
How this prompt is built
This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.
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