Maintain the balance between missed revenue potential and excess inventory
Achieve higher service levels and lower costs with SAP Predictive Replenishment, a machine-learning solution that streamlines inventory, predicts demand, and automates order proposals.
Overview
Reduce revenue loss due to stock-outs
Reduce revenue loss by increasing service levels and product availability along with high levels of supply chain transparency.
Reduce inventory carrying costs
Lower inventory carrying costs by optimizing the inventory levels with improved demand calculation and cost-optimized order proposals.
Increase operational productivity
Optimize productivity through intelligent automation and simple, insight-rich manual controls enabled by built-in alerts and retail business context.
Details
Solution type
Business Essentials
Compatibility
Works with
- SAP Order and Delivery Scheduling
- SAP Merchandising for Retail and Wholesale Distribution
- SAP Replenishment Planning
Features
Automated replenishment with order optimization
Automate the calculation of order proposals considering business objectives such as minimum order restrictions for Suppliers and constraints such as range of coverage, minimum order quantities and service levels. Model demand channels to represent true omnichannel networks, with end-to-end visibility across all sales channels.
Flexible integration possibilities
Intelligent solution for retailers, benefitting from a modular and open cloud architecture. Seamless integration with SAP solutions such as SAP S/4HANA Retail Merchandise Management, SAP Order and Delivery Scheduling and SAP Customer Activity Repository, allowing retailers to leverage an existing set up while implementing agile processes, ensuring they remain competitive and responsive in a rapidly changing retail landscape.
Ease of use with modern and intuitive workbenches
Optimized user experience across multiple user personas, with flexible business configurations and comprehensive order proposal review options, with guided alerting to quickly resolve identified issues in the automated process.
