Recently I was talking with a friend who used to run a buying office in Hong Kong, and he described how buying products from Chinese suppliers is, in good part, about risk management.
Risk manager, or buyer?
He compares a buyer to a “risk manager” in a bank.
Let’s say company ABC wants to contract a loan. The bank will ask for the balance sheet and income statement of the past 3 years, for some information about the owners, and so on.
Armed with this information, as well as past data of other customers who contracted a loan, their models predict the risk of not getting reimbursed. And the risk manager can make a decision more easily.
Where is the similarity with a professional buyer?
Let’s say you need to order a widget. Two of your current suppliers can make it, but one has a poor record of quality and on-time shipment performance, and the other offers a relatively high price.
You might ask yourself these questions:
- Is it worth investing time to find other suppliers?
- How reliable will those new suppliers be? Will they drop the ball?
- Where to get accurate data to base the decision on?
- If the buyer makes a gut decision (without data or facts) and the result is disastrous, how will he/she defend that choice?
As the above questions illustrate, it is all about collecting meaningful and accurate data, and slicing them in a way that supports a decision.
A quality related example
Let’s take quality-related data as an example. What type of data can be used this way? Here are a few examples:
- Percentage of inspections that were rejected (pre-shipment)
- Same as above, for first-time production runs
- Percentage of inspections that were rejected (after delivery)
- Percentage of batches that needed to be re-inspected (pre-shipment)
- Percentage of issues that were not closed within 2 months
All these data need to be known at the factory level. If a supplier places production in several facilities, getting averages is not very helpful.
They also need to be sliced by type of product, in case that supplier works across different product ranges.