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.