# Advanced Analytics

*Last updated: 2026-06-18*

> Advanced analytics goes beyond basic reporting and descriptive statistics by combining predictive modelling (what will happen?) with prescriptive optimisation (what is the best course of action?) and machine learning to support operational decisions across logistics and supply chain management.

Advanced analytics goes beyond basic reporting and descriptive statistics by combining predictive modelling (what will happen?) with prescriptive optimisation (what is the best course of action?) and machine learning to support operational decisions across logistics and supply chain management. Freight forwarders and logistics providers apply it to demand forecasting, inventory optimisation, route planning, and early detection of potential shipment delays. The underlying models draw on transaction data, inventory histories, and time-series feeds from operational systems. The outcome is measurably better decision quality – fewer empty runs, lower holding costs, improved on-time delivery. Advanced analytics is distinct from conventional business intelligence (BI), which primarily describes what has already occurred.

**Source:** [https://www.ibm.com/analytics/advanced-analytics](https://www.ibm.com/analytics/advanced-analytics)

## Quick Facts

| Property | Value |
|---|---|
| Term | Advanced Analytics |
| Language | EN |
| Word count | 108 |
| Last updated | 2026-06-18 |
| Source | https://www.ibm.com/analytics/advanced-analytics |

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*Logistics Glossary — Freight Academy: [https://www.freight-academy.com/en/glossary/advanced-analytics](https://www.freight-academy.com/en/glossary/advanced-analytics)*

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