Decomposing Success Metrics

A team reports that its model reaches high precision and recall on an internal test set. The executive hears good news and asks a fair follow-up: what does that do for margin? The room goes quiet, because precision and recall are properties of a classifier, not of a business. Between a model score and a financial result lies a chain of operational facts: how many cases the model touches, what happens when it is wrong, how much human work remains, and how fast the process moves. This topic gives you a framework to walk that chain deliberately, so that technical quality can be translated into money before the budget is spent rather than argued about afterwards.…