4R Systems Intelligent Inventory Optimization vs SAS Intelligent Inventory Management

4R Systems Intelligent Inventory Optimization is a cloud-delivered web suite for retailers managing supply-chain and inventory decisions. It covers demand planning, replenishment, allocation, assortment, and markdowns. Forecasting accounts for promotions, seasonality, pricing, and localized demand while identifying underlying demand, including lost sales. Replenishment models multi-echelon inventory and recommends stock by SKU and location. Allocation recommendations consider stock, weather trends, inbound orders, and future requirements. Assortment tools use store clusters, product attributes, and local demand to suggest store-specific mixes. Markdown optimization recommends timing and depth for end-of-season and end-of-life reductions. Planning as a Service combines AI tools with strategic planning and execution support. Customers use a web portal after establishing data exchanges; the One Predictive Engine integrates with core operating systems, although specific systems are not named. The vendor lists auto parts, convenience, apparel and footwear, hardware, and home furnishings retailers. Pricing is not published; visitors are directed to request a demo.

SAS Intelligent Inventory Management is a web-based suite for retail and consumer packaged goods companies planning sizes, purchasing and inventory. It combines SAS Size Optimization and SAS Inventory Optimization, using historical sales, analytics and machine learning to produce size, demand and inventory intelligence. Size features create demand-based profiles, support event scenarios, detect active size ranges and work across hierarchy levels. Products can be grouped by hierarchy or attributes, with new products matched to attribute profiles. Pack recommendations can apply usage and variation constraints, combine packs with bulk and account for supply-chain costs, lifecycle changes and promotions. Inventory planning calculates stock levels across the supply chain and supports replenishment policies based on lead times, costs and target service levels. What-if analysis compares scenarios, proposal costs and policy effects across single- and multi-echelon networks. SAS says the Viya version can deploy on Microsoft Azure and Amazon Web Services, but SAS Intelligent Inventory Optimization is unavailable on Viya from release 2024.04 onward.