OneTaskBy Tim King · Updated
Decision Tree Maker
Type It, Get the Best Choice
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If this tool saved you time, a coffee helps keep new ones coming.
How the Decision Tree Maker works
This decision tree maker draws the choice and calculates it as well. Type the options as an indented list, add probabilities to uncertain outcomes and a payoff to each end, and the page lays out squares for decisions, circles for chance and triangles for outcomes. It works out the expected value of every branch, highlights the best choice and downloads as SVG or PNG.
Decision tree maker: draw the choice, then do the sums
A decision tree breaks a choice into the things you control and the things you do not. A square is a decision you make. A circle is a chance event with several possible outcomes, each with a probability. A triangle is where a path ends, with its payoff. Working backwards from the ends, each chance node is worth the probability-weighted average of its outcomes and each decision is worth its best option. That "roll back" gives the expected value of every choice.
Writing the tree
- The first line is the starting question.
- Indent each branch two spaces under the node it comes from.
- Write a branch as "branch label: node name". "Launch: Market response" is the branch "Launch" leading to the node "Market response".
- Put a probability in brackets after the branch label, "Strong (30%)", to make its parent a chance node. Every branch from that node needs one and they must add up to 100%. Decimals such as "(0.3)" work too.
- End an outcome line with "= value" for its payoff: "Big win = 500000". Negative numbers are losses.
Lines starting with "#" are comments.
How to read the result
Each decision and chance node shows its expected value (EV) underneath. On every decision the branch with the highest EV is drawn bold, and the stats show the best first choice and its EV. In the sample, launching straight away is worth 500,000 × 30% + 120,000 × 50% − 150,000 × 20% = 180,000, a pilot is worth 300,000 × 60% − 20,000 × 40% = 172,000, and doing nothing is worth 0.
What expected value does not tell you
EV is the long-run average if the same bet could be made many times. A one-off decision with a small chance of a ruinous loss may still be the wrong call even with the best EV, so look at the worst outcome on each branch as well. The probabilities are usually estimates, so try changing them to see how sensitive the answer is. If the best choice flips with a small change, the decision is close and more information may be worth paying for. To list the forces behind a decision first, a SWOT analysis or a fishbone diagram helps.
FAQ
Why does a node show no expected value?
An expected value needs a payoff on every outcome below it. If any end of a branch has no "= value", the nodes above it cannot be calculated. Add the missing payoffs and the values appear.
What if my probabilities do not add up to 100%?
The page stops and tells you which line has the problem and what the branches currently add up to. Adjust the percentages so the outcomes of each chance node cover every possibility exactly once.
Can I use costs instead of profits?
Yes, but write costs as negative numbers so that "best" still means the highest value. If every payoff is a cost, the highlighted choice is the one with the smallest expected cost.
Does it work for classification decision trees from machine learning?
No. Those trees split data on features to predict a label. This tool is for decision analysis: choices, uncertain outcomes and payoffs, rolled back to an expected value.
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