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Decision Tree overview

Decision Tree is a visual builder for business and financial decisions with uncertain outcomes. You construct a tree of decision and chance nodes, assign USD payoffs and probabilities, and see expected value (EV) calculated live across every path.

What it does​

You start with a Decision node representing a choice you need to make. Each branch of that decision can lead to another decision, a Chance node (where the outcome is uncertain), or a Leaf node (the end of a path with a final payoff). The tool calculates EV continuously — no "Calculate" button — so you see the impact of every change immediately.

Who it's for​

Anyone structuring a high-stakes decision: product launch vs. wait, acquire vs. pass, invest vs. defer. Decision Tree is particularly useful when:

  • There are multiple sequential uncertainties (e.g., regulatory approval, then market performance)
  • You need to communicate the decision logic to stakeholders
  • You want to know which input assumptions most affect the outcome (via sensitivity analysis)
warning

Decision Tree requires a Pro plan. Free users see an upgrade prompt.

Next steps​

  • Core concepts — key terms and mental model
  • How-to — adding and editing nodes, sensitivity analysis, AI editing, CSV export
  • Reference — node types, EV formulas, probability validation states, CSV format