I am currently enrolled in business school and am taking a data and decisions class, and this week’s lesson is about decision trees. Two of the textbook examples are based on an oil deal and lawn mower installment plan. A better way for me to learn this concept is to use an example that I can relate to - fashion.
In the decision trees, there is an expected monetary value associated with each choice, and the point of the exercise is to determine which has the highest value to the decision maker, or in the case of costs, which has the lowest value. The values are determined by the costs and likelihood of different outcomes at a future point in time.
Applying this concept to shopping for fashion items, I’m going to create a decision tree to compare these 3 obsessions:
All 3 products are high quality and built to last, but to calculate its personal value to me, I need to consider how long I would have this item before I’m over it and want a new one to replace it. I will also estimate resale values at that point in time. I’m guessing that after 3 years, the likelihood that I’ll no longer want them is as follows:
The Brunello Cuccinelli trousers - 50% - mostly it will depend on how they fit by then
The Loewe jacket - 45% - I love this look now but might move on from it
The Max Mara coat - 35% - it doesn’t really get cold enough in Huntington Beach, CA to wear this much
And the estimated resale value in 3 years, based on similar items on TheRealReal are:
The Brunello trousers - $350
The Loewe jacket - $250
The Max Mara coat - $1400
Here’s the decision tree:
The most valuable choice for me now is the Max Mara camel teddy bear coat. All of the present values are negative, but the Max Mara coat has the lowest negative value at -$481.50. In terms of percentage of original cost, the teddy bear coat will have the highest resale value.
Sadly all 3 are way out of my price range, so the best choice for me is probably something from TheRealReal, where people sell designer goods that they bought a few years ago but are now over it.