Prescriptive analytics is a branch of business analytics that focuses on providing recommendations on what actions should be taken based on the results of analytics. It involves using optimization and simulation techniques to identify the best course of action, given a set of constraints and objectives.
Prescriptive analytics uses a combination of descriptive and predictive analytics to identify potential outcomes and recommend the best course of action. For example, a business might use prescriptive analytics to optimize its supply chain, by identifying the most cost-effective sourcing options, minimizing inventory holding costs, and optimizing transportation routes.
Some common techniques used in prescriptive analytics include linear programming, integer programming, simulation modeling, and heuristic optimization. These techniques can be used to model complex systems, identify trade-offs between different objectives, and optimize decisions based on a set of constraints.
Overall, prescriptive analytics is a valuable tool for identifying the best course of action in complex business scenarios. By using prescriptive analytics, businesses can optimize their operations, reduce costs, and improve their overall performance.