Translating predictive model performance into profit and savings estimates
Gooder addresses one particular place where there’s a need for a new category of software: the metrics. It’s a business user console for understanding potential value and making decisions about deployment. Typically, data scientists present technical metrics like area under the curve, precision, or recall, but very rarely go to stakeholders and say if you deploy this model, it has potential value of this much profit or savings. We provide visualization where both dimensions are business relevant, like the decision threshold and business metrics like savings or profit, so stakeholders can see exactly what their options are.
— The Value Translation Gap: AI’s Deployment Problem · The Edge