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If they are ready to pay, then they can buy a sample of both and spend some time testing the products. If it is the bean counters who choose, then they are buy
by pif 4y ago
If they are ready to pay, then they can buy a sample of both and spend some time testing the products.
If it is the bean counters who choose, then they are buying cheap for the sake of cheap.
- aidenn0 4y agoPerhaps we do need to define what it means to "pay." For low volume products, what you suggest could multiply the per-unit cost by a large integer factor, when what most buyers want is to pay 10-20% more for a supplier that will spend maybe 1-5% more buying quality parts and doing proper in-house QA. There are plenty of cases where adding an extra "9" to the end will significantly increase the costs, but there is also a lot of low-hanging fruit that stays low-hanging because so much purchasing is low-information. Hence why the original comment you replied to requires a "big, hardass, customer." Small customers often cant amortize the NRE across enough products to determine quality, so even if they are willing to pay 2x on a part for it to be better, they don't know if they are getting something of higher quality or just something with a higher markup.
- pizzachan 4y agoYears ago I remember a Freakonomics podcast episode that delved into the hostility public and private policy makers had to running experiments. It mainly comes down to not wanting to bear the downside risk of an experiment having unfavorable or economically useless results. While if they just don’t know and no else does there is no consequence for doing the status quo even if the results are poor.
- aidenn0 4y agoIn this specific case, my working hypothesis is that the overwhelming majority (if not all) of my choices are of equally mediocre quality, so spending a lot of money to test this is a waste of money. The "big hardass customer" buys enough product to have a reasonable expectation of effecting change in the suppliers, so running both the experiments suggested by GP, and performing post-mortem analysis of failed components can be expected to steadily improve quality over time.