Don't let demand variability and forecast error play havoc on your supply chain. GAINS produces a dynamic, optimal demand plan that is combined with robust inventory and replenishment optimization to reduce inventory and working capital. Our advanced Demand Planning and Forecasting capabilities include demand pattern recognition as well as demand sensing and machine learning that helps automatically detect and respond to changes. It all adds up to higher forecast accuracy and improved service levels, reduced expediting costs and increased revenue -- achieved in a matter of weeks.
Better Accuracy. Faster Response.
Because GAINS operates as a fully-integrated supply chain planning and optimization suite, Demand Planning and Forecasting is a critical prerequisite to optimizing global inventory and maximizing return on assets (ROA). As an integral input to Inventory Optimization, Demand Planning and Forecasting provides highly accurate baseline forecasts. By synchronizing planning across the organization and among enterprises as part of the SI&OP process, GAINS helps accelerate supply chain response time.
- Automatically selects the most plausible model from 40 statistical models
- Facilitates promotions & project management
- Integrates extrinsic leading indicators
- Provides exception planning and improves planner productivity
- Enables collaboration with bottom-up and top-down processes
- Manages customer and collaborative forecasts
- Allocates based on profitability
- Plans new and short-life cycle items
- Offers long-term predictive demand sensing
Automated Multi-echelon Modeling
GAINS Demand Planning and Forecasting drives increased revenue and reduced inventory by generating optimized demand plans derived from automated multi-echelon modeling based on item demand history, point of sale data, machine/fleet usage, leading indicators, and Sales, Inventory & Operations Planning (SI&OP) data.
Multiple data inputs extrinsic to the enterprise are integrated in GAINS, such as interest rates, business cycles, and competitor performance. These forecasts, and the error residual to them, are vetted to ensure effective integration with Inventory Optimization. GAINS pulls from a suite of sophisticated algorithms for:
- Pattern recognition and machine learning based on observed, historical demand
- New item launches based on neural network analysis
- Maintenance applications determining parts needs, based on reliability and fleet usage/effort history and projections
- Incorporating structured, aggregate leading indicator data into the demand planning process
Processes and Key Performance Indicators (KPIs)
- Manage detailed exceptions for expert review
- Incorporate unstructured, aggregate market knowledge into the plan for middle-out or top-down adjustment
- Help review the efficacy of both GAINS “raw” plans as well as the value-add of refinements and adjustments.