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What is Prescriptive Analytics

Definition

Prescriptive analytics goes beyond predicting what will happen to recommend what to do about it, using optimisation, simulation, and decision models to suggest the actions most likely to achieve desired outcomes given constraints and objectives.
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  • Recommends specific actions, not just predictions or descriptions
  • Optimises decisions against goals and constraints
  • Helps choose the best option among many possibilities
  • Turns forecasts directly into actionable guidance

Real World Example

An airline uses prescriptive analytics to recommend optimal ticket prices and seat allocations, weighing demand forecasts against capacity and revenue goals to suggest the actions that maximise revenue.

FAQs

How does prescriptive analytics differ from predictive?

Predictive analytics forecasts what will happen, while prescriptive analytics recommends what actions to take in response.

What techniques power prescriptive analytics?

Optimisation, simulation, and decision modelling, often combined with predictive models.

What is the value of prescriptive analytics?

It turns insight and forecasts into concrete, optimised recommendations for action under real-world constraints.

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