Trinamix Multi- Echelon

Inventory Optimization

Multi-level, Multi-node Supply Chain

Inventory Optimization and Safety Stock Planning

Product Overview and Demo


In recent decades, value chains have grown in length and complexity as companies expanded around the world in pursuit of margin improvements. However, the way value chains have shaped with global environmental changes and organizations are subjected to more disruptions with growing frequency. To be resilient against these risk, companies needs to be ready for anything. To be ready, companies needs to optimally place buffer across the supply chain decoupling any variability.

Solution Overview

Trinamix Multi- Echelon Inventory Optimization – A comprehensive solution for Multi-level, Multi-node Supply Chain Inventory Optimization and Safety Stock Planning

Multi-echelon Inventory Optimization is a micro service that works with Oracle supply planning to convert uncertainty to variability, decoupling demand and supply variability by placing the right inventory, at right location and time, creating a more robust and resilient supply chain.

Multi-echelon Inventory Optimization (MEIO) uses time-tested advanced mathematical algorithms to accurately model inventory flows through the interdependent stages and locations of a supply chain, and analyzes historical behavior under all conditions. The model helps create an optimal configuration of inventory buffers and locations adequate to handle any degree of demand and supply uncertainty, seasonality, etc., while achieving desired service levels for minimum cost. MEIO typically recommends specific strategies for postponing inventory at earlier stages of manufacturing and distribution processes.

Architecture: Trinamix Resilient Planning (MEIO)

Key Features

Automate planning to increase productivity

Planners can focus on more productive and highest value added activities


Optimal Inventory Spending

Marginal Utility of Inventory optimized based on budget constraint


Guarantee high service levels at lowest cost

Position inventory across the network to efficiently meet high customer service level with minimum inventory investment

Master demand uncertainty

Stochastic-based forecasting identifies a range of outcomes and the probability of occurrence to calculate optimal inventory targets

Digital Supply Chain Twin

Leverages machine learning to convert supply and demand uncertainty to variability


Key Benefits

Free up working capital
Meet high service levels while minimizing inventory
Optimize inventory for uncertain demand