Identify the most profitable policies in the face of statistical uncertainties.
Ensure you always have the right product, at the right time, in the right place.
Traditional demand forecasting methods rely primarily on historical data, but if that data too heavily influences the forecast, a supplier can miss out on strong growth opportunities.
Improved forecast accuracy can be attained through reinforcement learning, a machine learning technique that helps determine which actions will lead to the greatest rewards. Combining the potential of reinforcement learning with human decision making can deliver far more effective forecasting models, for both direct to store and centralized distribution business frameworks.