Decision Trees
Decision trees map out complex business choices visually, helping you weigh up different options and their potential outcomes. They're particularly useful when facing multiple alternatives with uncertain results.
Each branch represents a possible choice, with probability values showing the likelihood of different outcomes. Multiply probabilities by potential returns to calculate expected values for each option.
The example shows an expansion decision: unsuccessful outcome (0.7 probability × £450,000) plus successful outcome (0.3 probability × £1,200,000) gives total expected value of £675,000. Subtract the £50,000 cost for a net gain of £615,000.
Benefits include logical layout of choices and consideration of multiple scenarios simultaneously. However, remember that probabilities are estimates and may be biased - decision trees work with quantitative data only, potentially missing important qualitative factors.
Watch out: Don't let complex calculations fool you into thinking decision trees eliminate risk entirely - they're tools to help structure thinking, not crystal balls.