Second- & Third-Order Effects Mapping
Purpose
Surfaces the effects of a decision or solution that are easy to miss because
they aren't immediate: what the first effect triggers next (second order),
and what that in turn triggers more broadly in the market, competition, or
regulation (third order). Most decisions are evaluated only on their
first-order effect — this skill forces the view further out.
Anchored in research
- Systems thinking and "second-order thinking" technique in strategic
decision-making (widely known, e.g. the "consequence scanning" practice in
consulting).
- Liedtka (1998) — systems perspective and thinking in time; the same roots
as
../scenario-and-foresight/SKILL.md,
but this skill operationalizes order-of-effect thinking specifically around
one decision, rather than building broader alternative futures.
- A research report on AI Business Designer skills for the age of AI,
supplied by the pack owner (2026) — explicitly raises this in the context
of evaluating an AI solution's business case: how the solution changes
customer behavior over the long run, and what new competitors it might
attract into the market.
Method
- Name the decision or solution under review (e.g. a new AI feature, a
pricing change, automation, a new business model).
- Map the first-order effect: what's the direct, immediate consequence?
This is usually the only effect considered in decision-making by default.
- Map the second-order effects: what does the first effect trigger next?
For example, how does the customer actually change their behavior once
the solution has been in use for a while — not just their first reaction.
- Map the third-order effects: what do the second-order changes trigger
more broadly — competitor reactions, new market entrants, tighter
regulation, shifting stakeholder expectations?
- For each order, ask separately: who is affected (customer, competitor,
your own organization, regulator, the wider ecosystem), and is the effect
likely positive, negative, or ambivalent?
- Identify which second-/third-order effects are likely and significant
enough to change the original decision — go back and adjust the
decision if needed.
- Produce a structured effect chain (1st → 2nd → 3rd order) to support
the decision; mark clearly what's reasoned inference and what's
speculation (
[assumption — verify]).
What this skill does NOT do
- Doesn't predict the future with certainty — second-/third-order effects are
plausible hypotheses, not probability calculations.
- Doesn't replace
../scenario-and-foresight/SKILL.md
— this skill follows one decision's effect chain forward; scenario-and-foresight
builds alternative futures from broader uncertainty.
- Doesn't make the decision for you — it surfaces effects that would
otherwise go unnoticed; the decision itself stays with the human.
Refinement notes
Areas to keep deepening with real practice:
- your own rules of thumb for how far down the effect chain it's worth going
before it turns too speculative to be useful
- concrete templates (into
../../references/)
- reference cases / your own examples where a second-/third-order effect
changed the original decision
- what this skill deliberately does not do (guardrails, common mistakes) —
add to the list above
This is an internal working note, not a claim about the skill's current
usability. Track depth privately via the maturity field in
skills_index.json (see
../../../meta/maturity_levels.md).
Don't add new fields to the frontmatter — name and description are
the only ones allowed (see
../../../meta/frontmatter_schema.md).
Continue from here
References
1---2name: second-and-third-order-effects-mapping3description: Anticipates the second- and third-order effects of a strategic decision or AI solution — how it changes customer behavior, the competitive landscape, and your own organization over time, beyond the direct first-order effect.4---56# Second- & Third-Order Effects Mapping78## Purpose910Surfaces the effects of a decision or solution that are easy to miss because11they aren't immediate: what the first effect triggers next (second order),12and what that in turn triggers more broadly in the market, competition, or13regulation (third order). Most decisions are evaluated only on their14first-order effect — this skill forces the view further out.1516## Anchored in research1718- Systems thinking and "second-order thinking" technique in strategic19 decision-making (widely known, e.g. the "consequence scanning" practice in20 consulting).21- Liedtka (1998) — systems perspective and thinking in time; the same roots22 as [`../scenario-and-foresight/SKILL.md`](../scenario-and-foresight/SKILL.md),23 but this skill operationalizes order-of-effect thinking specifically around24 one decision, rather than building broader alternative futures.25- A research report on AI Business Designer skills for the age of AI,26 supplied by the pack owner (2026) — explicitly raises this in the context27 of evaluating an AI solution's business case: how the solution changes28 customer behavior over the long run, and what new competitors it might29 attract into the market.3031## Method32331. **Name the decision or solution under review** (e.g. a new AI feature, a34 pricing change, automation, a new business model).352. **Map the first-order effect**: what's the direct, immediate consequence?36 This is usually the only effect considered in decision-making by default.373. **Map the second-order effects**: what does the first effect trigger next?38 For example, how does the customer actually *change* their behavior once39 the solution has been in use for a while — not just their first reaction.404. **Map the third-order effects**: what do the second-order changes trigger41 more broadly — competitor reactions, new market entrants, tighter42 regulation, shifting stakeholder expectations?435. **For each order, ask separately**: who is affected (customer, competitor,44 your own organization, regulator, the wider ecosystem), and is the effect45 likely positive, negative, or ambivalent?466. **Identify which second-/third-order effects are likely and significant47 enough to change the original decision** — go back and adjust the48 decision if needed.497. **Produce a structured effect chain (1st → 2nd → 3rd order)** to support50 the decision; mark clearly what's reasoned inference and what's51 speculation (`[assumption — verify]`).5253## What this skill does NOT do5455- Doesn't predict the future with certainty — second-/third-order effects are56 plausible hypotheses, not probability calculations.57- Doesn't replace [`../scenario-and-foresight/SKILL.md`](../scenario-and-foresight/SKILL.md)58 — this skill follows one decision's effect chain forward; scenario-and-foresight59 builds alternative futures from broader uncertainty.60- Doesn't make the decision for you — it surfaces effects that would61 otherwise go unnoticed; the decision itself stays with the human.6263## Refinement notes6465Areas to keep deepening with real practice:6667- your own rules of thumb for how far down the effect chain it's worth going68 before it turns too speculative to be useful69- concrete templates (into [`../../references/`](../../references/))70- reference cases / your own examples where a second-/third-order effect71 changed the original decision72- what this skill deliberately does *not* do (guardrails, common mistakes) —73 add to the list above7475This is an internal working note, not a claim about the skill's current76usability. Track depth privately via the `maturity` field in77`skills_index.json` (see78[`../../../meta/maturity_levels.md`](../../../meta/maturity_levels.md)).79**Don't add new fields to the frontmatter** — `name` and `description` are80the only ones allowed (see81[`../../../meta/frontmatter_schema.md`](../../../meta/frontmatter_schema.md)).8283## Continue from here8485- In this pack: [`../scenario-and-foresight/SKILL.md`](../scenario-and-foresight/SKILL.md)86 (complementary, handles broader uncertainty),87 [`../strategic-options-evaluation/SKILL.md`](../strategic-options-evaluation/SKILL.md)88 (carries the effect-chain findings into an options comparison).89- Related skill in another pack:90 [`../../../ai-strategy-and-governance/skills/ai-opportunity-portfolio/SKILL.md`](../../../ai-strategy-and-governance/skills/ai-opportunity-portfolio/SKILL.md),91 [`../../../business-case-and-analysis/skills/risk-matrix-and-mitigation/SKILL.md`](../../../business-case-and-analysis/skills/risk-matrix-and-mitigation/SKILL.md)92- A ready-made skill chain for this situation: see [`../../../playbooks/`](../../../playbooks/)93- This pack's shared guardrails: [`../../CLAUDE.md`](../../CLAUDE.md)9495## References9697- [`../../references/`](../../references/) — the pack's shared background material98- [`../../CLAUDE.md`](../../CLAUDE.md) — the pack's shared guardrails