What Is Prescriptive Analytics?
Prescriptive analytics goes beyond prediction to recommend specific actions. Learn how it helps businesses decide what to do, not just what might happen.
Key Takeaways
- Prescriptive analytics recommends specific actions to take based on predictions, constraints, and business objectives.
- It sits at the top of the analytics maturity curve: descriptive (what happened), predictive (what will happen), prescriptive (what should we do).
- It uses optimization algorithms, simulation, and decision modelling to evaluate multiple possible actions and select the best one.
Beyond prediction
Predictive analytics tells you that demand for a product will likely increase by 20% next month. Prescriptive analytics goes further: given that prediction, your current inventory levels, supplier lead times, and budget constraints, it recommends ordering 500 additional units from Supplier A by next Tuesday and increasing your advertising spend by 15% on the product's highest-converting channel. It translates forecasts into specific, optimised decisions.
How it works
Prescriptive analytics combines predictive models with optimization algorithms. It defines an objective (maximise profit, minimise cost, reduce waste), identifies constraints (budget, capacity, time), evaluates multiple possible actions through simulation, and recommends the option that best achieves the objective within the constraints. Linear programming, Monte Carlo simulation, and reinforcement learning are common techniques used in prescriptive systems.
Real-world applications
Supply chain optimization determines the most cost-effective way to move goods from suppliers to customers. Dynamic pricing adjusts prices in real time based on demand, competition, and inventory levels. Workforce scheduling assigns staff to shifts that match predicted demand while respecting labour regulations. For African logistics companies navigating complex multi-modal transport networks, prescriptive analytics can optimise routes across road, rail, and water transport simultaneously.
When prescriptive analytics makes sense
Prescriptive analytics delivers the highest value when decisions are complex, repetitive, and have measurable outcomes. If your business makes hundreds of pricing, inventory, or routing decisions daily, automation through prescriptive models can significantly outperform human judgement. It requires mature data infrastructure and confidence in your predictive models. Most businesses should master descriptive and predictive analytics before investing in prescriptive capabilities.