← Use Case Library

Use CaseSupply Chain

Optimise supply chain

Use historic data to model supply chains to identify and predict the way potentially complex and opaque demand patterns ripple through the system under different scenarios (e.g. weather changes). This can be used to predict potential pricing.

⚙

Operational Support

Operational Support - Performance tracking

⚙

Operational

Operational - Enables Just in Time approach

£

Cost

Cost - Reduced waiting times

£

Cost

Cost - Reduced inventory costs

Description

Optimise supply chain

Linked Case Studies

Global Transport Provider

A global transport provider gains a significant competitive advantage by implementing AI for supply chain visibility

Alliance Boots achieves inventory savings and improved service levels with machine learning optimisation algorithm

University of Pittsburgh Medical Center (UPMC)

University of Pittsburgh Medical Center (UPMC) improves hospital supply chain performance to achieve 92% on-time payments with AI

Infinera will optimise its supply chain management to make better predictions about delivery dates using machine learning

Kiabi increases in-store product availability by 7% by optimising supply chain management with machine learning

Gousto, a British meal kit retailer, grows customer base by 700% by using machine learning to forecast demand and personalise recommendations

Granarolo reduces inventory levels by more than 50% and cuts capital and lead time in half using machine learning

Leroy-Merlin forecasts sales and suggests orders to department managers to optimise supply chain with machine learning

Unnamed global manufacturer

Unnamed global manufacturer reduces inventory costs by 25-35% and frees up working capital using machine learning

Lennox improves service levels by 16% and increases inventory turns by 25% with machine learning powered demand predictions

Schneider Electric

Schneider Electric saves €8 million by optimising its supply chain using machine learning

Shell saves over a million dollars annually by doing inventory analysis 32 times faster using machine learning

Instacart predicts availability of 200 million grocery items every 30 minutes using machine learning

←Back to Use Case Library

Source: kaggle.com · Editor: original-sdg