Order Right is a replenishment planning and demand forecasting solution designed to optimize inventory management for retailers and brands. It leverages thousands of retail ML algorithms to dynamically adjust to SKU-store level demand patterns and supply chain disruptions, delivering hyperlocal precision to replenishment plans. The software addresses challenges such as product cannibalization by balancing demand between products, considering promotions and availability, and automatically adjusting replenishment levels. It also mitigates supply chain disruptions through adaptive self-learning models that optimize lead times, fill rates, safety stock, and pending orders. Order Right supports holistic inventory optimization across Direct Store Orders, Stock Transfer Orders, and Warehouse Orders. Predictive alerts help pre-empt risks like stockouts, excess stock, and expiring products, enabling proactive corrective action. The robust data framework handles data challenges such as sparse data, outliers, and new product introductions with custom retail-tuned algorithms. Key benefits include higher availability, improved inventory ROI by operating with less inventory without risking stockouts, reduced shrinkage and wastage by considering demand and supply factors along with product expiry dates, and enhanced planning efficiency and transparency through automation and actionable insights delivered via a unified interface.

Features & Benefits

• Hyperlocal Demand Forecasting: Dynamically adjusts to SKU-store level demand patterns and supply chain disruptions for precise replenishment plans.
• Cannibalization Management: Balances demand between products, considering promotions and availability to curb chaos.
• Supply Chain Disruption Mitigation: Uses adaptive self-learning models to optimize replenishment plans amidst lead time variations and other disruptions.
• Holistic Inventory Optimization: Supports Direct Store Orders, Stock Transfer Orders, and Warehouse Orders for comprehensive inventory management.
• Predictive Alerts: Identifies potential stockouts, excess stock, and expiring products for proactive risk mitigation.
• Robust Data Framework: Handles data challenges like sparse data, outliers, and new product introductions with custom retail-tuned algorithms.