Causal Mechanism Mapping¶
Map the mechanism connecting a proposed cause to an effect before intervening.
The Diagnostic Story¶
Symptom: The team is confident that A causes B — the correlation is clear, the timeline is right, and the story feels compelling. But repeated interventions on A keep failing to move B, and nobody can describe the actual pathway that connects them. The root cause has become a slogan rather than an explanation, and rival causal stories compete without any evidence about the mechanism itself.
Pivot: Turn the causal claim into an inspectable pathway: name the proposed cause and effect, break the connection into mechanism links, attach evidence and uncertainty to each link, surface rival explanations and confounders, and identify where in the pathway an intervention could plausibly change outcomes.
Resolution: Interventions become better targeted because they act on identified links in the mechanism rather than on superficially correlated factors. Uncertainty about each link is visible, so decisions to act, wait, or test further are grounded rather than based on assumption. Causal claims stay revisable as new evidence arrives.
Reach for this when you hear…¶
[public health] “We keep funding the awareness campaign because rates went down after the last one, but we have no idea whether it was the campaign or the simultaneous policy change or just seasonal variation.”
[software reliability] “The post-mortem says the root cause was insufficient monitoring, but that's not a root cause — that's a symptom, and we keep fixing the same symptom every quarter.”
[organizational development] “Every engagement survey shows trust is low and we keep adding perks, but if we can't say how perks are supposed to change trust we're guessing.”
Mechanisms / Implementations¶
- Causal Diagram:
causal_diagramimplements the archetype as a artifact by represents candidate causal links visually so assumptions, missing mediators, feedback paths, and confounders can be inspected together. - Mechanism Map:
mechanism_mapimplements the archetype as a template by breaks a broad causal story into ordered link records, each with an actor, process, evidence basis, uncertainty, and test implication. - Root-Cause Analysis:
root_cause_analysisimplements the archetype as a method by investigates upstream contributors to a failure or incident and can instantiate the archetype when it maps how the contributor produced the failure. - Causal-Loop Map:
causal_loop_mapimplements the archetype as a artifact by shows reinforcing or balancing feedback loops when causal influence cycles through the system rather than moving in a one-way chain. - Process Tracing:
process_tracingimplements the archetype as a method by uses sequence evidence, signatures, and within-case observations to test whether the proposed mechanism actually occurred. - Intervention Test:
intervention_testimplements the archetype as a test_or_assessment by changes a selected intervention point and observes whether intermediate and final outcomes move as predicted by the mechanism. - Causal Inference Review:
causal_inference_reviewimplements the archetype as a procedure by reviews identification assumptions, comparison groups, confounders, and evidence limits before accepting a causal claim. - Theory of Change Model:
theory_of_change_modelimplements the archetype as a document by documents how activities are expected to produce outputs, outcomes, and impacts through explicit causal pathways. - Contribution Analysis:
contribution_analysisimplements the archetype as a method by assesses whether an intervention plausibly contributed to observed outcomes when randomized control or clean isolation is not available. - Failure Tree Analysis:
failure_tree_analysisimplements the archetype as a artifact by represents combinations of component failures or conditions that can produce an undesired event.
Related Abstractions¶
Abstractions this archetype builds on — directly (a source ingredient) or as a related pattern. Links follow the typed catalog namespace.
Built directly on (2)
- Causality: Cause-effect relationships.
- Confounding: Hidden variable interference.
Also references 5 related abstractions
- Causal Layered Analysis (CLA): Multi-layered future analysis.
- Counterfactual Reasoning: Hypothetical alternatives.
- Counterfactuals: Alternate hypothetical scenarios.
- Hypothesis Testing (Null vs. Alternative): Null vs alternative evaluation.
- Uncertainty: Incomplete knowledge.
Variants¶
Narrower or domain-specific specializations that share this archetype's core structure. Recognized variants are established; candidate variants are provisional.
Causal Pathway Mapping · subtype · recognized
A variant that emphasizes ordered mediating steps between a cause and an effect.
Intervention Point Mapping · implementation variant · recognized
A variant focused on choosing where to act inside a causal mechanism chain.
Process-Tracing Mechanism Map · method family variant · recognized
A variant that tests mechanism occurrence through within-case sequence evidence and diagnostic observations.
Theory-of-Change Mapping · domain variant · recognized
A program-design variant that maps how activities are expected to produce outputs, outcomes, and impact.
Failure Pathway Mapping · risk or failure variant · candidate
A variant focused on how conditions combine to produce a failure state and where safeguards can interrupt the path.