Path A
Phase the expansion.
Keep the offer stable. Add capacity in stages and examine the demand required at each step.
Inevitable / Causal reasoning
What drives it?
What changes it?
A correlation can suggest where to look. A decision needs a better account of the mechanism. Causal reasoning connects drivers, dependencies, and interventions so your team can examine the alternatives.
- 18
- Causal models
- Multiple drivers
- Explore interventions together
- Assumptions
- Visible beside the mechanism
In practice / Illustrative
Explore the levers that change the decision.
Price alone is not a growth strategy. Examine adoption, cost, capacity, and their relationships before comparing alternative paths.
PriceAdoptionDelivery costCapacity
Path B
Revisit the offer.
Change pricing and scope together. Examine adoption and delivery cost before committing capacity.
Alternatives with a mechanism behind them.
Explore business-driver interventions here. Deliverable edits and downstream regeneration belong to the task-execution layer.
01 / Capabilities
18 causal models. A question-led approach.
Different decisions need different methods. The data and assumptions determine which analyses are appropriate.
Mechanisms and dependencies
Map candidate causal relationships, mediators, confounders, and feedback loops.
Interventions and scenarios
Compare changes to several drivers, separately or together, and examine the resulting paths.
Alternative explanations
Compare model conclusions, retain disagreement, and identify the observations that could distinguish between them.
02 / The workflow
Show the mechanism.
Keep the assumptions.
Inspect the conditions under which a conclusion holds. See the evidence, model-derived relationships, and scenario estimates behind each proposed intervention.
- Structure
- The variables, direction of relationships, and assumptions in the proposed mechanism.
- Evidence
- The sources, observations, and analytical support available for those relationships.
- Limits
- Data gaps, identification assumptions, and uncertainty that could change the result.
03 / In the stack
Two ways to revisit a decision.
Causal exploration changes the business drivers inside an analysis. In task execution, counterfactuals are deliverable edits: revise the research or analysis itself, then regenerate work that depends on it. Both let a team revisit the decision, but they operate on different things.