Machine learning improves supply chain forecasting by analyzing historical data and identifying patterns that may not be evident through traditional data analysis. By utilizing algorithms, machine learning can predict future demand, optimizing inventory levels and reducing waste. This capability allows businesses to respond more swiftly to changes in market conditions or consumer preferences. Additionally, machine learning models can continuously refine their predictions over time, leading to increased accuracy and better resource allocation in the supply chain process.