Build a total-cost view
Compared material price, conversion behavior, startup waste, complaint risk, and supplier lead-time volatility in one decision model.
Études de cas
Contrôle des coûts avec de meilleurs matériaux
Un projet d'optimisation des matériaux et de la structure a amélioré la stabilité des coûts tout en maintenant les objectifs de qualité et de débit.
Cas client
Contrôle des coûts avec de meilleurs matériaux
Un projet d'optimisation des matériaux et de la structure a amélioré la stabilité des coûts tout en maintenant les objectifs de qualité et de débit.
Food, household, and general consumer productsPackaging cost controlFlexible pouchPrinted cartonCorrugated shipperInsert or liner
At a glance
Customer type
Manufacturer with high-volume SKUs and rising packaging input costs
Packaging formats
Flexible pouch · Printed carton · Corrugated shipper · Insert or liner
Main issue
Material cost was rising, but the team needed to avoid quality drift, line issues, and hidden conversion losses from a rushed material switch.
Project type
Material and structure cost review
Secteurs courants
Food, household, and general consumer products
Region
Australia and export supply chains
Before
- Cost discussions were anchored on quoted material price.
- Production risk was raised late and slowed decisions.
- SKU complexity made the first optimization wave too broad.
After
- Savings options were compared against total delivered cost.
- Material decisions used pilot evidence instead of supplier claims alone.
- The rollout started with SKUs that could prove the model faster.
What we reviewed
Top SKUs by packaging spend and volume
Current material specs, supplier quotes, and MOQ constraints
Line behavior, startup waste, and defect history
Customer complaint records tied to packaging performance
What changed
Pilot alternatives on real constraints
Validated candidate structures against line setup, speed, sealing or forming behavior, and quality checks before conversion.
Sequence high-volume changes first
Prioritized stable, high-volume SKUs where the risk-adjusted return was clearer, then held complex formats for later review.
Could this apply to you?
Input costs are rising faster than pricing can absorb.
You need savings without creating quality or line-speed problems.
There are many SKUs and no clear first wave for optimization.
Procurement and production disagree on what a safe switch means.
Timeline
Cost baseline
Rank SKUs by spend, volume, structure, and material exposure.
Pilot comparison
Validate candidate materials against line and quality constraints.
Wave plan
Choose the first conversion group and define hold conditions for higher-risk formats.
Evidence to track
Total delivered cost
Track material price, startup waste, defect cost, and conversion impact together.
Conversion risk
Track which SKUs passed pilot checks and which need a separate validation path.
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