From Meaningful Data Science to Impactful Decisions: The Importance of Being Causally Prescriptive

This article proposes a framework for transition from traditional data science where the focus is on extracting value available to goal-driven analytical decision making business objective defined first. We discuss link between predictive analytics and prescriptive in context of formulating problem, assert that all problem formulations assume causal decisions outcomes. emphasize role inference specifying outcomes accurately, ultimately aligning analysis with objectives. offer practical examples integrate various required tasks describe scenarios versus not required.