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ERP for hygiene products manufacturer with AI Demand Planning & Lean Inventory


Full-company ERP for a hygiene products manufacturer — production, procurement, sales and finance in one system. AI demand forecasting plans material needs against supplier lead times, implementing Lean Inventory without risking production stoppages.


The client manufactured protective maxi pads, medical garments, rubber gloves and wet wipes. Production, procurement, sales and finance ran in separate tools — Excel, standalone accounting software and a basic WMS. Growth was exposing the gaps: materials arrived late, stock levels were unpredictable and management had no real-time picture of the business.


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The challenge

A fast-growing manufacturer
with no single system

The root problem was disconnection. Procurement didn't know what production had planned. Sales didn't know what stock was available. Finance was always working from data that was days old. The result: both overstocking and stockouts happened simultaneously — excess inventory in some raw materials, shortages in others — because nobody had a unified, current view.

The brief

Build a full-company ERP covering production, procurement, sales, warehouse and finance — with an AI demand planning module that calculates material requirements against supplier lead times to implement Lean Inventory without risking production stoppages.

The solution

Full ERP with AI-driven
Lean Inventory at the core

We designed the system around a single principle: every module feeds every other. A confirmed sales order immediately updates production planning, which immediately updates material requirements, which immediately shows procurement what needs ordering and when — accounting for each supplier's delivery lead time.
📦
Production Planning
Production orders, BOMs, work-in-progress tracking across all product lines — maxi pads, medical garments, gloves, wet wipes. Real-time production status visible to every department.
BOM · Work orders · WIP tracking
🤖
AI Demand Forecasting
ML model forecasts demand per SKU from order history, seasonality and customer patterns. Forecast drives material requirements planning (MRP) — the system knows what to order, how much and when, accounting for each supplier's lead time.
ML forecasting · MRP · Lead time aware
📐
Lean Inventory Engine
Dynamic reorder points and safety stock levels calculated per material based on demand variability and supplier reliability. Target: minimum inventory that guarantees zero production stoppages — eliminating the safety-stock guesswork that drove overstocking.
Dynamic reorder points · Safety stock · Min/max
🛒
Procurement Management
Supplier management, purchase orders, goods receipt and three-way matching (PO / GR / invoice). System generates procurement recommendations from the Lean Inventory engine — buyer reviews and approves rather than manually calculates.
PO management · Supplier portal · 3-way match
🏪
Warehouse &Inventory
Bin-level inventory tracking across raw materials, WIP and finished goods. Barcode-based goods movements. Real-time stock valuation. Lot and expiry date tracking for materials with shelf life.
Bin management · Barcode · Lot tracking
💰
Finance &Management Reporting
Accounts payable, accounts receivable, cost of goods sold and product margin reporting — all generated from operational data with no manual re-entry. Management P &L on demand, not at month end.
AP/AR · COGS · Margin reporting · P &L
Outcomes

Lean Inventory that
actually worked

Results measured 12 months post go-live.
–35%
raw material inventory value vs the year before
0
production stoppages due to material shortage in 12 months
–42%
time from sales order to production schedule
Real-time
P&L and stock visibility for management

The AI forecasting module paid for the project in 8 months through inventory reduction alone — before any productivity gains were counted.

Why Lean Inventory worked here

Previous attempts at stock reduction had failed because they used static minimum stock levels that nobody trusted. The AI model made the reorder points dynamic and explainable — showing the buyer exactly why a particular quantity was being recommended based on demand forecast and supplier lead time. Trust in the system replaced the instinct to over-order "just in case".

Technology

Stack &architecture

Built as a unified platform — all modules share the same database, no integration gaps between systems.
Frontend
React + TypeScript
Role-based dashboards for production, procurement, warehouse and management
Backend
Java / Spring Boot
Business logic, MRP engine, AI model serving
AI / ML
Prophet + XGBoost
Demand forecasting with seasonality, safety stock calculation
Database
PostgreSQL
Single source of truth, full audit trail
Barcode
Zebra / mobile scan
Warehouse goods movements, goods receipt
Infrastructure
AWS / on-prem option
Hosted SaaS or on-premise deployment
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