Automated Supply Chain
Manager
How a mid-size manufacturer cut procurement overhead by 62% and eliminated stockout events through end-to-end supply chain automation.
The Company
NovaBuild Industries is a mid-size contract manufacturer supplying precision components to aerospace and automotive OEMs. With over 340 SKUs, 60+ active suppliers, and fluctuating lead times, their procurement team was drowning in manual purchase orders, spreadsheet forecasts, and reactive firefighting.
In 2023, NovaBuild partnered with our team to design and deploy an Automated Supply Chain Manager — a continuously learning platform that monitors inventory, predicts demand, negotiates reorders, and coordinates logistics without human intervention.
Challenge & Solution
⚡ The Challenge
Manual PO processing averaged 4.8 days per cycle. Planners spent 60% of their week on data reconciliation. Demand forecasts were based on 12-month rolling averages with no signal integration, leading to chronic over- and under-stock situations.
✦ The Solution
A real-time, multi-agent automation layer ingesting ERP data, supplier APIs, logistics feeds, and market signals. Autonomous reorder agents execute purchases within pre-approved thresholds, escalating edge cases to human planners only.
How It Works
Unified Data Ingestion
Live connectors to SAP ERP, supplier portals, 3PL APIs, and external market indices stream inventory levels, demand signals, and supplier capacity data into a central knowledge graph.
Probabilistic Demand Forecasting
An ensemble of gradient-boosted trees and a Transformer-based sequence model predict 14/30/90-day demand per SKU, weighting recent signals more heavily than historical patterns.
Autonomous Reorder Execution
When inventory breaches dynamic safety-stock thresholds, a purchasing agent selects the optimal supplier (price + lead time + quality score) and issues POs via EDI or API — no human touch needed.
Exception Routing & Human-in-the-Loop
Orders outside approved parameters, new suppliers, or anomaly-flagged items are routed to a planner dashboard with AI-drafted justifications and recommended actions.
Continuous Learning
Every fulfilled order, delay, and forecast error feeds back into the models. The system self-calibrates weekly, with monthly planner review sessions to audit decisions and tune policy guardrails.
Results After 12 Months
Procurement Cost
Overhead dropped 62% as manual PO processing was fully automated for 91% of SKUs.
Zero Stockouts
From 14 critical stockout events in the prior year to zero in the 12 months post-launch.
Cycle Time
Average reorder cycle compressed from 4.8 days to 27 hours — a 4.1× improvement.
Planner Capacity
Procurement team redirected 55% of their time to strategic sourcing and supplier development.
Inventory Carrying Cost
Tighter forecasting reduced average inventory value by 23%, freeing $2.4M in working capital.
Supplier Relations
Consistent, predictable ordering improved on-time delivery rates across the supplier base from 78% to 94%.
We used to start every Monday firefighting last week’s supply gaps. Now our planners spend Mondays on strategic initiatives. The system handles the routine with a precision we simply couldn’t match manually.
Stack & Integrations
The platform was built to integrate with NovaBuild’s existing SAP S/4HANA environment and extended to a proprietary supplier network. Core capabilities include:
