Supply Chain Planning Optimization
This application focuses on optimizing end-to-end supply chain planning so manufacturers can respond quickly and efficiently to demand and supply changes. It integrates forecasting, inventory optimization, production planning, and logistics decisions into a single, data-driven system that continuously updates plans rather than relying on slow, periodic cycles. The goal is to reduce fragility, shorten reaction times, and improve service levels while holding less inventory and using capacity more effectively. AI is used to unify siloed data, generate more accurate demand forecasts, predict disruptions, and automatically propose or execute planning decisions across the network. By dynamically adjusting inventory targets, production schedules, and replenishment plans, these systems help manufacturers maintain resilience in the face of variability and shocks. As a result, organizations can reduce stockouts and excess inventory, improve on-time delivery, and operate with a more agile and resilient supply chain.
The Problem
“Continuous supply chain plans that re-optimize as demand, supply, and capacity shift”
Organizations face these key challenges:
Monthly/weekly planning cycles that become stale within days
Too much inventory in the wrong places while still experiencing stockouts
Production plans that ignore real constraints (materials, changeovers, labor, transport)