Prescriptive Analytics
What is prescriptive analytics? Prescriptive analytics goes a step beyond predicting the future. It tells you what actions to take to achieve the best possible outcome. Think of it as a GPS guiding you with the best route based on real-time traffic conditions.
Let’s have a look on one of a prescriptive analytics examples, if a business knows customer demand is about to increase, prescriptive analytics will recommend steps like boosting inventory or launching targeted promotions. It analyzes data from various sources, applies advanced algorithms, and suggests the best course of action.
In healthcare, if a doctor predicts a patient is at risk for heart disease, prescriptive analytics can help create a personalized treatment plan, recommending lifestyle changes or medications to prevent the condition.
In short, prescriptive analytics doesn't just tell you what might happen. It tells you what to do next to reach your goals, making it powerful prescriptive analytics tools for optimizing decisions and strategies.
Frequently Asked Questions:
What is prescriptive analytics?
It is the process of using data, algorithms, and AI to recommend the best course of action for a given situation.
How does prescriptive analytics work?
It combines historical data, predictive models, and optimisation techniques to suggest specific actions.
What is the main goal of prescriptive analytics?
To guide decision-makers toward the most effective and efficient choices.
How is prescriptive analytics different from predictive analytics?
Predictive analytics forecasts what might happen, while prescriptive analytics advises what should be done.
What tools are used in prescriptive analytics?
Tools include IBM Decision Optimization, SAS, Gurobi, and AI-powered analytics platforms.
Which industries benefit from prescriptive analytics?
It is widely used in supply chain, finance, healthcare, energy, and marketing.
Does prescriptive analytics require AI?
While not mandatory, AI significantly improves its accuracy and decision-making capabilities.
What type of data is needed for prescriptive analytics?
Both historical and real-time data, combined with business rules and constraints.
What are the benefits of prescriptive analytics?
It improves decision accuracy, reduces costs, boosts efficiency, and enhances strategic planning.
What are examples of prescriptive analytics?
Recommending optimal delivery routes, suggesting the best pricing strategy, or allocating resources effectively.
