In today’s business environment, the complexities arising from volatile consumer demand require a higher degree of planning efficiency. Traditional workflow-based planning solutions don’t emphasize analytics and rely on domain knowledge and guesswork, frequently missing the true drivers of demand. Leveraging analytics enables quick response to demand changes, delivering a consistent customer experience across channels.

This panel discussion will highlight examples of how machine learning and an in-memory planning engine are designed to support demand-driven planning and forecasting capabilities. A discussion around how companies can simplify data management, streamline common planning processes, and provide analytics with sophisticated workflow creation and deployment features.