AI-Powered Supply Chain Forecasting Framework
Modern supply chain forecasting requires more than historical sales data. Advanced AI-driven frameworks now integrate a wide range of internal and external signals - from inventory levels, promotions, and logistics activity to macroeconomic indicators, weather patterns, and mobility trends. By combining diverse data sources with state-of-the-art machine learning architectures — such as Temporal Fusion Transformers (TFT) and Mixture of Experts models — organizations can achieve unprecedented levels of forecasting accuracy, adaptability, and scalability across their supply networks.
Our Forecasting Framework
This next-generation approach moves beyond traditional planning tools that often deliver inconsistent results and rely heavily on manual adjustments. It enables unified forecasting across regions, warehouses, and retail operations, supporting end-to-end visibility and synchronized decision-making.
While one-size-fits-all forecasting models struggle to perform well across diverse scenarios, the Mixture of Experts Framework takes a best-of-breed approach. It combines multiple specialized models, each tuned to different patterns, and uses a gating network to choose the right expert for each prediction. This adaptive design delivers higher accuracy and efficiency than any single model could achieve on its own.
Challenge
Traditional forecasting tools rely too heavily on historical data, struggle with external signals, and require constant manual adjustment. They deliver inconsistent accuracy and fail to adapt to fast-changing market conditions.
Outcome
The outcome is a data-driven supply chain forecasting ecosystem that improves precision, accelerates response times, and enhances resilience in rapidly changing market conditions.
Regional Demand Forecast
Provides the baseline forecast (pre-season and in-season) for regional-level purchase orders by consolidating market signals, macroeconomic trends, and sales data.
Store Demand Forecast
Delivers precise demand forecasts (pre-season and in-season) at store level across thousands of locations worldwide, capturing local seasonality and promotions.
Warehouse Demand Forecast
Generates demand projections at multiple echelons of the supply chain, enabling planners to redirect product flows dynamically across the network.
Logistics Forecast
Anticipates operational metrics such as the number of packages, orders, and workloads across logistics hubs for enhanced capacity planning.
Cold Start Forecast
Designed for new or reintroduced products without sales history, using product attributes and learning from similar categories to estimate early demand.
Additional Forecasts
The framework extends to capacity, lost sales, cashflow, and expense forecasting, creating an integrated ecosystem for end-to-end business planning.