'They have been fine, mostly'
You are deciding where to place next season's orders. One factory is cheaper. Another has been around longer. Your buyer remembers a late shipment from the first and a quality problem with the second, but cannot say how often either happened. The product manager has a different impression. Nobody can put numbers on it.
The decision gets made on price and whoever argues most convincingly.
Why factory performance is hard to see
The facts exist, but in different systems and inboxes: agreed and actual ship dates in purchase orders and shipment records, inspection results in reports, document problems in broker queries, defects in returns and claims. Nothing brings them together per factory. So performance is remembered, and memory is biased towards recent and dramatic events.
| Measure | Where the data is |
|---|---|
| Ship date against agreed date | Purchase orders and shipment tracking |
| Inspection results | Inspection reports |
| Document accuracy and timing | Document tracker or email |
| Defects and claims | Returns and claims records |
| Responsiveness | Production updates and emails |
What gut-feel judgements cost
Orders go to factories that cost more in delays, quality problems and admin than their price suggests. Good factories are not recognised or rewarded. Supplier reviews become arguments. And when you need to move production, you do not have the evidence to choose well.
It also weakens negotiations. A factory that is told it is often late can dispute it; a factory shown its own shipment record usually does not.
Hidden costs are the main thing gut feel misses. A factory whose documents are often wrong causes clearance delays and broker queries that never appear in its unit price. A factory that ships late causes stockouts and air freight. When those costs are not tied back to the factory, the cheapest quote keeps winning even when it is not the cheapest supplier.
Staff changes make it worse. When the buyer who dealt with a factory for years leaves, their impression of that factory leaves with them, and the new buyer starts again from the last email thread.
The scorecards we build
- Data is pulled from the systems you already have: purchase orders, shipment tracking, inspection results, document checks, returns and claims.
- For each factory, measures are calculated over periods you choose: on-time shipping against agreed dates, inspection pass rate, document problems per shipment, defect claims, and response to update requests.
- The scorecard shows each measure with a trend and the underlying records, so any figure can be checked.
- Factories can be compared side by side, and weighted by what matters most to you.
- A review pack per factory can be produced for supplier meetings, with the facts laid out.
- Measures built from your own records.
- Every figure traceable to the orders and shipments behind it.
- Your weighting, not a generic score.
The scorecard is only as complete as the data behind it. Where some records are missing, we show that plainly rather than filling gaps.
How supplier decisions change
Sourcing decisions weigh price against a clear record of delivery, quality and admin. Supplier reviews start from facts both sides can see. Good factories can be told so, with evidence. And when a factory's performance slips, it shows up as a trend before it becomes a crisis.
Is this how you judge factories?
- Factory performance is judged on memory.
- You cannot say how often a factory ships late.
- Supplier reviews turn into arguments.
- Sourcing decisions are made mainly on price.
- You have no record of defects per factory.