How We Used Historic Order Data to Eliminate Third-Party Vehicles in FMCG Distribution — A Full ML…

📰 Medium · Machine Learning

Learn how to use machine learning to optimize FMCG distribution by predicting retailer demand and smoothing daily load

intermediate Published 8 May 2026

Action Steps

Collect historic order data to train a machine learning model
Build a predictive model to forecast retailer demand
Apply vehicle routing algorithms to discover the optimal fixed fleet
Configure a system to smooth daily load and reduce reliance on third-party vehicles
Test and evaluate the performance of the optimized distribution system
Refine the model and system based on real-world results

Who Needs to Know This

Data scientists and logistics managers can benefit from this approach to improve distribution efficiency and reduce costs

Key Insight

💡 Using machine learning to predict demand and optimize vehicle routing can help eliminate third-party vehicles in FMCG distribution