PEKON AI Inventory Optimization Engine helps multi-store brands reduce stockouts, slow-moving inventory, and replenishment inefficiencies at the store × SKU level. It connects inventory diagnostics, differentiated replenishment strategies, and execution recommendations in one continuous workflow. A configurable formula engine and six-dimensional inventory health score support store tiering and product classification, helping teams generate more targeted replenishment, transfer, clearance, and inventory return recommendations.
Evaluate each store on a 0–100 scale across six inventory dimensions, including inventory turnover, stockout control, slow-moving inventory, category structure, dormant inventory, and assortment breadth. The scoring model helps retail teams identify inventory risks at store level and provides a consistent basis for store tiering and differentiated inventory strategies.
Configure replenishment logic based on business rules, inventory conditions, sales performance, safety stock, and other operational parameters. Ordering rules can be maintained through configurable parameters, allowing retail teams to adapt replenishment strategies to different store and product conditions without repeatedly rebuilding the underlying workflow.
Apply differentiated inventory strategies based on both store tiers (S/A/B/C) and product ABC classifications. This store × product approach helps brands avoid using the same replenishment logic across every location and SKU, allowing inventory decisions to reflect differences in store performance, product importance, sales velocity, and inventory risk.
Generate actionable recommendations across key inventory scenarios, including: Dormant inventory management, Slow-moving inventory clearance, Active-SKU replenishment, Inter-store inventory transfer, Excess inventory return. Recommendations can be prioritized based on inventory conditions and estimated business impact, helping retail teams focus first on the actions that require the most attention.
Support common inventory management scenarios across day-to-day retail operations: Routine replenishment, Promotion planning, Product transition, New product initial allocation, Allocation for supply-constrained best-sellers, Allocation during prolonged shortages.
Track the difference between system-generated recommendations and actual execution results to identify where inventory parameters may require adjustment. By reviewing indicators such as manual adjustment rate, inventory turnover, stockout conditions, and slow-moving inventory, teams can continuously refine replenishment parameters and inventory strategies based on actual operating results.
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View solution →Learn more about PEKON AI Inventory Optimization Engine
ERP systems remain an important system of record for inventory, purchasing, finance, and other core business processes. PEKON AI Inventory Optimization Engine complements these systems with store-level inventory diagnostics, differentiated replenishment strategies, and execution recommendations across replenishment, transfer, clearance, and inventory return scenarios. Instead of replacing the ERP, PEKON provides an additional optimization layer focused on helping retail teams make more targeted store × SKU inventory decisions.
Typical inputs include product master data, store information, inventory balances, sales transactions, open purchase orders, and related inventory movement data.Brands already using PEKON Smart Retail System can connect relevant operational data directly. Brands using other POS or ERP systems can connect through standard interfaces based on the available system architecture and data structure.
Yes. The engine supports differentiated strategies based on store tiers (S/A/B/C) and product ABC classifications. For example, higher-tier stores and lower-tier stores can use different replenishment parameters, while Class-A, Class-B, and Class-C products can follow different inventory rules based on their business importance and operating characteristics.
Yes. Different inventory scenarios can use different rules and parameter settings. Typical scenarios include promotion planning, new product initial allocation, product transition, routine replenishment, and allocation under supply constraints. This helps retail teams apply more appropriate inventory strategies instead of relying on one fixed replenishment rule for every business situation.
Whether your brand is preparing to launch, expanding stores, or scaling to group operation, our consultants can provide demos and advice based on your stage.
