1. Price and cost are not the same thing.
Unit price dominates sourcing decisions.
But unit price is not the life cycle cost. It's a snapshot.
What actually determines outcomes sits outside the quotation:
- Scalability
- Rework and returns
- Scrap rates
- Engineering change responsiveness
- Management time required to keep things running
McKinsey estimates that 20 to 30% of total landed cost is driven by post-award operational factors, not quoted price, with quality losses, delays, expediting, and internal overhead being the biggest contributors.
Yet most sourcing decisions optimise for the one variable that is easiest to compare and hardest to sustain.
Pricing doesn't reflect lifecycle cost. It reflects negotiation leverage at a point in time.
2. First-batch success is mistaken for ability to scale
Factories are very good at samples and initial batches.
That phase is:
- Highly supervised
- Staffed with top operators
- Manually controlled
But sampling success says very little about what happens at scale.
As volume increases:
- Operational variability rises
- Middle management replaces senior oversight
- Process discipline matters more than individual skill
BCG and World Bank manufacturing studies consistently show that defect rates often increase 2 to 4x during early scale-up phases in emerging-market factories before stabilising.
The mistake is assuming that early performance predicts steady-state behaviour.
It doesn't.
Scaling is a different operating model, not a continuation of sampling.
3. Specifications are "clear" until production begins
Most sourcing teams believe their specifications are clear.
They usually are, on paper.
In practice, interpretation gaps emerge quickly:
- Tolerances applied differently
- Material substitutions viewed as equivalent
- Quality thresholds enforced inconsistently across shifts
According to WTO supply-chain research, quality-related losses during early production ramps are more often caused by interpretation differences than by missing documentation.
The issue is not whether specs exist.
It's whether understanding is shared at every layer of the factory.
And once production is live, correcting these gaps becomes slow, expensive, and political.
4. Supplier behaviour changes after nomination
Before nomination:
- Fast responses
- Senior management involved
- Problems escalated quickly
After the Purchase Order:
- Attention shifts to the next bid
- Issues are filtered through middle layers
- Escalation slows
This is not bad intent, it's rational behaviour.
Once nominated, the supplier's commercial risk drops. The buyer's attention shifts elsewhere.
Multiple Bain and McKinsey post-mortems show that governance intensity typically drops sharply within 60 to 90 days of supplier award, even though execution risk is highest during that same period.
Sourcing doesn't fail at nomination.
It fails when ownership dissolves immediately after.
5. Learning curves are not budgeted, financially or organisationally
Every new supplier has a learning curve:
- Higher defect rates
- Slower cycle times
- Increased management intervention
Yet many sourcing models assume near-immediate steady-state performance.
McKinsey research on supplier transitions suggests that 6 to 12 months of stabilisation is typical before performance normalises, longer for complex products.
When this isn't budgeted:
- Margins disappoint
- Timelines slip
- Internal confidence erodes
The supplier is blamed for behaving exactly as expected.
The model was wrong, not the factory.
The real issue: execution risk is priced at zero
Asia sourcing doesn't fail because suppliers can't execute.
It fails because:
- Pricing is mistaken for strategy
- Sampling is mistaken for scalability
- Specifications are mistaken for shared understanding
- Nomination is mistaken for control
The companies that succeed design sourcing as a lifecycle system, not a transaction.
They:
- Optimise for behaviour, not price
- Govern hardest after award, not before
- Budget learning curves explicitly
- Treat scale-up as a separate risk phase
Everyone else learns the same lessons, just later and more expensively.
Where have you seen sourcing break down most often: pricing assumptions, scale-up, or post-award governance?
