Use cases

AI in the supply chain: efficient, resilient and sustainable

Supply chains that are as smooth as possible are essential for a functioning economy and for each individual company – they determine how efficiently, reliably and cost-effectively goods and services reach customers. Delays, inefficiencies and a lack of transparency can cause enormous costs and jeopardize competitiveness. The two important trading partners China and the United Kingdom are among the groups with a high economic risk for Germany. The USA, Japan and European partner countries, on the other hand, show potential for further expansion within German supply chains (ifo Research Reports, No. 133). Artificial intelligence (AI) can help you identify opportunities and risks in the context of your supply chains:

Typical AI use cases in the supply chain sector

Dynamic route planning

Problem: Maximize the efficiency of your route planning.
Solution: Use supervised learning to plan optimal routes in real time based on your drivers’ experience as well as historical and current data.
Benefits: Faster deliveries, reduced transport costs and lower resource consumption.

Demand forecast

Problem: Inaccurate forecasts lead to overstocking or supply bottlenecks.
Solution: AI creates precise forecasts based on historical data, seasonal trends and external factors.
Benefits: Accurate planning, reduced storage costs and fewer shortages.

Anomaly detection in the supply chain

Problem: Deviations and disruptions are often detected late, which leads to delays. Solution: AI continuously monitors the supply chain, detects deviations and suggests measures. Benefits: Faster problem detection, fewer disruptions and more stable processes.

Optimization of stock levels

Problem: Stock levels are often either too high or insufficient.
Solution: AI analyzes order patterns and consumption data to calculate optimal stock levels.
Benefits: Reduced inventory costs, optimized capacity utilization and improved delivery capability.

Sustainability management

Problem: Supply chain processes are often not optimized for sustainability, which increases environmental and regulatory risks. Solution: AI evaluates the carbon footprint of the supply chain and suggests more sustainable alternatives. Benefits: Fulfillment of sustainability goals, compliance with legal requirements and positive contribution to corporate reputation.

Further use cases

Discover more exciting use cases from different areas of the company – for new ideas, perspectives and possibilities.

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