Demand Forecasting

Why this use case matters

Applications powered by machine learning & custom predictions can help consumer packaged goods (CPG) manufacturers maintain strategic relationships with retailers by reliably meeting retail inventory demand. A late delivery forecasting model built from historical data offers advanced warning so that they can take action to avoid late deliveries.


Supervised Machine Learning, Classification, Anomaly Detection


Support Vector Machines (SVM), Logistic Regression, Tree-Based Learning, Extreme Gradient Boosting (XGBoost), LSTM, Neural Net Architectures, Bayes Network, k-NN


Reduction in late fess paid to retailers & distributors for out-of-stock products.

Mosaic designed and deployed an AI model to predict shipments at risk of late fees for one the world’s largest CPG businesses.

Mosaic has compiled our industry expertise into a Machine Learning playbook for Manufacturing.