The decision tree is related to the cost-benefit table, but incorporates a different way of visualizing possible outcomes of a certain option, decision or alternative and the probabilities of these outcomes. The figure just above gives an example of two different options, with each a different probability for a certain payout.

Executing the Method

  • Create Branches

    For each alternative, create a new branch. More complex trees can also have child options.

  • Assign Probabilities and Values

    In this example, there is a 50% change that option A will be a success (returning a benefit of 100.000) and a 50% chance that it will fail (returning only a benefit of 20.000).

  • Calculate Expected Value

    The expected value for option A is 0.5*100.000 + 0.5* 20.000 = 60.000. In this case, option A is more attractive than option B.