Decision science studio

Counterfactual Lab

A rigorous workspace for leaders who need to know what would have changed if the decision, timing, policy, or constraint had been different.

24hfirst causal map for focused questions
3xbaseline, intervention, and stress scenario
0.8confidence target before a recommendation ships
causal inference console
Observed world

Week 7 launch, elevated support load, slower activation.

Counterfactual

Earlier onboarding QA, modeled against retention, cost, and operational risk.

From intuition to falsifiable alternate worlds.

Each engagement turns a messy strategic question into a compact model your team can inspect, challenge, and reuse.

1

Frame the fork

Define the decision point, rival hypotheses, and the outcomes that would actually change the next move.

2

Map the mechanism

Separate causes from correlations with diagrams, priors, historical analogs, and data quality checks.

3

Stress the answer

Run sensitivity passes so the final recommendation shows where it is strong, fragile, or unknowable.

A small workbench for big what-ifs.

Select a question type and see how the lab reframes it into an actionable counterfactual.

Question type

72%

If launch moved two weeks later, activation likely improves while pipeline risk rises. The useful question is where that trade flips.