In this session, we introduce Optilogic's new Demand Modeling web application and walk through what it takes to go from raw historical demand data to hierarchy-consistent, well-informed forecasts. You'll see how the engine improves on traditional statistical forecasting by learning across every level of your product and location hierarchy at once, keeping those forecasts aligned, and supporting both scenario and uncertainty analysis.

From there, we walk through the app itself — creating a project, uploading the core input tables (demand, product hierarchy, and location hierarchy), and reviewing the optional causal tables that let you bring in drivers like promotions, GDP, or fuel prices. We run a live Demand Model and explore the outputs across the Detail, Hierarchical, and Growth Projections tabs, showing how to read error metrics, compare algorithms, and identify which product-location combinations are growing, declining, or carrying the most risk. Finally, we take a quick look at how those demand signals flow directly into Cosmic Frog to power network optimization scenarios.

Key features explained 🏆

• What Demand Modeling Does and How It Differs from Traditional Forecasting
• Touring the Web App: Inputs, Configuration, and Outputs
• Required Input Tables: Demand, Product Hierarchy, and Location Hierarchy
• Optional Causal Tables: Mapped Causes, External Causal, and Configuration
• Creating a Project and Uploading Data
• Running a Demand Model and Reviewing Error Logs
• Exploring the Detail and Hierarchical Forecast Tabs
• Reading the Growth Projections Page and Risk Quadrant
• Feeding Demand Signals into Cosmic Frog for Network Optimization