Case Study: Odoo for Cosmetic Quality Control

Case Study: How a Cosmetic Manufacturer Hit Zero Batch Rejections With Odoo Quality Control

Odoo quality control for cosmetic manufacturers may sound niche — until you see batches failing final inspection and going back for rework. This case study shows how a mid-sized manufacturer reduced batch rejection rates from 6.4% to zero in nine months.

The Client

A mid-sized cosmetic manufacturer near Mumbai producing skincare, color cosmetics, and hair care products for domestic and export markets.

• Turnover: ₹85 crore
• 180 batches/month across 120 SKUs
• 140 plant staff, 22 in QC/QA

While they had certifications and trained teams, their processes were fragmented and data unreliable.

The Problem

The plant was facing a 6.4% batch rejection rate — around 11 failed batches every month, costing ₹1.8 crore annually.

• Paper-based QC checklists with missing data
• No real-time visibility into QC stages
• Data spread across multiple Excel files
• No link between raw material and final QC
• Delayed root cause analysis

The Goal

• Reduce rejection rate below 1%
• Digitise 100% of QC processes
• Build a feedback loop to prevent repeat defects

The Solution

Built on Odoo Enterprise using Quality, MRP, Inventory, and Purchase modules, with custom cosmetic workflows.

1. Digital QC Checkpoints

QC checkpoints were embedded into manufacturing stages — no step could be skipped, and all entries were digital.

2. Custom QC Checks

Checks like viscosity, pH, shade matching, and micro testing were auto-triggered based on SKU type.

3. Batch Traceability

Full genealogy tracking reduced recall time from 2 days to 90 seconds.

4. Root Cause Workflow

Every rejection required root cause tagging, building a self-improving QC system.

5. Live Dashboards

Real-time dashboards replaced weekly QC meetings and improved decision-making speed.

Implementation Timeline

• Weeks 1–2: Process mapping & data cleanup
• Weeks 3–5: System configuration
• Weeks 6–7: Pilot rollout
• Weeks 8–9: Full deployment
• Weeks 10–11: Optimization & training

The Results

• Batch rejection rate: 6.4% → 0%
• Paper usage: 3,400 forms/month → 0
• Deviation closure: 4–6 days → < 1 day
• Traceability: 2 days → 90 seconds
• QC effort: 340 hrs → 45 hrs/month

What Made the Difference

• Clean master data
• Pilot-first rollout approach
• QC team ownership (not IT-driven)

Lessons for Manufacturers

• Digitisation alone is not enough — build feedback loops
• Invest in data quality early
• Always run a pilot
• Make business teams own the system

Cost & ROI

Total project cost: ₹42 lakh. Annual rejection loss eliminated: ₹1.8 crore.