Some features of metrics tree construction

When working with the metrics tree, I use the following techniques.

I start building the tree from the top of the target metric, then describe the financial metrics on which the target metric depends. In the next step, I spell out the unit economics metrics and key product metrics, such as the number of B customers.

Next is the hardest step, I place all the product metrics I have on the canvas and start linking them to the unit economics metrics. When doing this, it's important to make sure that each metric has a relationship lined up with the other metrics, up and down the tree. For example, product metrics must be linked to decision metrics and to the atomic metrics from which their values are calculated. 

Each link is a clear understanding of what formula links these metrics to each other. If there is no formula, there is no link. The formulas can be analytical or correlative, the latter are acceptable, but they are worse than analytical. 

The reciprocal position of metrics on the tree does not matter, but I usually put target and financial metrics at the top, followed by unit economics and product metrics, and they can be intermixed. And at the bottom are the atomic metrics. 

Each metric can be linked to several parent and child metrics at once. The main thing is to have a formula that explains each relationship.