Prescriptive Analytics

Service Description

Definition: Prescriptive analytics is a broader, more modern discipline that builds on descriptive and predictive analytics to determine the best possible course of action. It integrates statistics, machine learning, optimization, simulation, and AI to recommend or even automate decisions in complex systems. Purpose: To recommend or implement actions that will lead to desired outcomes—essentially answering, “What should we do next, and why?” Key Tools & Methods: Optimization and linear programming Monte Carlo simulation Reinforcement learning Scenario modeling and decision automation Example: After predictive analytics forecasts which machines are likely to fail, prescriptive analytics uses optimization algorithms to determine the best maintenance schedule and resource allocation to minimize downtime and cost.