What a logic tree is

A logic tree (also called an issue tree or decision tree) is a visual map that breaks one large problem into progressively smaller, more manageable parts. You start with the core problem at the root, then branch it into its main components, then branch each of those again, until you reach pieces small enough to investigate or act on directly.

The point is to turn a vague, overwhelming question into a structured set of sub-questions — so you can see the whole problem at once, spot where the real drivers are, and divide the work sensibly.

Build the branches to be MECE

A logic tree is only trustworthy if each level of branching is MECE — mutually exclusive (the branches don’t overlap) and collectively exhaustive (together they cover the whole problem with no gaps). If your branches overlap, you’ll double-count and waste effort; if they leave gaps, you might miss the part that actually matters.

Two common shapes

• Problem trees break a problem down into its possible causes. “Why did sign-ups drop?” branches into traffic, conversion, and so on — each branching further until you reach testable causes.
• Solution (or decision) trees break a goal down into the ways you could reach it. “How do we grow revenue?” branches into new customers, existing customers, and former customers — each a distinct lever you can pursue.

How to draw one

1. State the core problem or goal clearly at the root.
2. Branch it into 2–5 main components that are MECE.
3. Keep branching each component into its own sub-parts, the same way.
4. Stop when a branch is concrete enough to either analyse with data or act on directly.
5. Prune the branches that turn out to matter little, and dig deeper into the ones that drive most of the outcome.

Used well, a logic tree does two jobs at once: it makes sure you’ve considered the whole problem, and it shows you exactly where to focus.