AI-based transport planning for higher efficiency across the entire network

𝗧𝗵𝗲 𝗻𝗲𝘄𝗲𝘀𝘁 𝗲𝗽𝗶𝘀𝗼𝗱𝗲 𝘁𝗮𝗶𝗹𝗼𝗿𝗲𝗱 𝗳𝗼𝗿 𝗲𝘅𝗽𝗲𝗿𝘁𝘀 𝗶𝗻 𝗮𝘂𝘁𝗼𝗺𝗼𝘁𝗶𝘃𝗲 𝗹𝗼𝗴𝗶𝘀𝘁𝗶𝗰𝘀

𝗖𝗼𝗻𝘁𝗲𝗻𝘁:

The automotive industry is under massive pressure to improve efficiency: sales fluctuations, ESG requirements, volatile supply chains, and rising costs are forcing OEMs and suppliers to rethink their logistics strategies. Transportation planning in particular – often characterized by silo structures, manual processes, and a lack of transparency – offers enormous potential for optimization.

In the upcoming episode of our Logistics Series, we show how innovative automotive OEMs and suppliers can achieve significant savings while increasing their supply and production security through AI-supported tactical network planning in conjunction with operational transportation planning.

𝗣𝗮𝗿𝘁 1 – 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝘆 𝗼𝘃𝗲𝗿𝘃𝗶𝗲𝘄 & 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀:

🔹 Typical challenges in transport planning: Manual dispatching, fragmented master data, short-term rescheduling
🔹 Impact on total cost of ownership (TCO), production utilization, inventory levels, and CO₂ emissions
🔹 Why tactical and operational planning must be considered together

𝗣𝗮𝗿𝘁 2 – 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝘄𝗶𝘁𝗵 𝘁𝗵𝗲 𝗦2𝗱𝗮𝘁𝗮 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺:

🔹 MRP inbound optimization: Automated consolidation of delivery call-offs, holistic planning taking into account TCO, warehouse and transport costs
🔹Network optimization: Dynamic planning of FTL, LTL, milk runs & groupage with up to 15% cost savings
🔹 Tactical & operational use: The advantages of a holistic approach to transport planning
🔹 Real-world use cases: OEM & Tier-1 show how AI-supported planning has achieved up to 29% higher utilization and seven-figure savings