# Prescriptive analytics · Glossary
Analytics that recommends what action to take, typically by combining predictions with optimisation, simulation or business rules.
[Glossary](/glossary) · Analytics engineering and analytics

# Prescriptive analytics

     Analytics that recommends what action to take, typically by combining predictions with optimisation, simulation or business rules. It goes beyond describing what happened or forecasting what will happen.

## Why it matters

     Forecasts alone do not tell a planner what to do. Prescriptive analytics weighs options against constraints and objectives, such as cost, capacity and service levels, and proposes a course of action.

     Recommendations need transparency about their assumptions and a clear point of human decision, especially where constraints are incomplete or the consequences are significant.

## In practice

     For example, a UK grocery wholesaler might combine demand forecasts with warehouse capacity, lead times and shelf-life constraints to recommend daily replenishment quantities, which buyers review and adjust before orders are placed.

## Where Rodan fits

     Rodan builds decision support that connects predictions to action in [AI and Decision Systems](https://rodan.io/what-we-build/ai-decision-systems). See also [what is predictive analytics and how do ecommerce brands use it](https://rodan.io/insights/what-is-predictive-analytics-and-how-do-ecommerce-brands-use-it).

## Related terms

- [Machine learning (ML)](/glossary#machine-learning)

- [Commercial insights](/glossary/insights)

- [Digital twin](/glossary#digital-twin)

- [Human-in-the-loop (HITL)](/glossary#human-in-the-loop)

- [Real-time analytics](/glossary/real-time-analytics)

- [A/B testing](/glossary/ab-testing)
HTML: https://rodan.io/glossary/prescriptive-analytics