This post is a continuation of my first blog post. In the first post, I mentioned pre-built computers—computers with parts pre-assembled by manufacturers—can be a cost-efficient alternative to a custom-built computer—computers with individual parts bought and assembled by the consumer. This should strike you as strange as it violates common sense. This is implying computer parts plus the labor to assemble those parts cost more than solely computer parts. You might be wondering why is this the case
If you recall from blogpost #1, GPUs are one of the essential parts of a computer. They have always been traditionally expensive, but a new trend has emerged. The price of GPUs began to skyrocket around the middle of 2020 which correlates well to when one would expect the externalities related to COVID-19 would take place. We saw production prices spike for roughly 20-30% when comparing 2020’s prices to 2022’s prices. While this is not insignificant, it was not enough to explain why GPUs skyrocketed in price. A closer examination showed that both crypto and secondary markets in conjunction with a supply shortage caused hyper-inflation among high-end GPU models.
The above information isn’t random and is very pertinent to the hypothesis: “pre-built PCs can be more cost-efficient to buy than custom-built PCs. We are starting to see that a phenomena called PC shucking being applied to GPUs. To be clear, PC shucking is the act of a consumer buying a pre-built PC and stripping it apart for parts. The consumer applying this strategy never had the intentions of using the pre-built PC. Rather, they disassemble the entire PC for one high quality part to either:
A. Use this part as it is an upgrade to their current part.
B. The consumer plans on reselling the part in secondary markets.
Usually, the consumer plans on selling the parts not targeted. Since GPU’s are being shucked, the non-GPU parts are being sold to compensate the buyer for the pre-built hence:
Effective price GPUshuck = Cost of PCprebuilt – Cost of non-GPU partsprebuilt (1)
Since the shucker is clearly savy and understands the parts can be bought individually then we know:
Effective price GPUshuck < GPUmarket-price (2)
and therefore we get,
Price GPUindividual > Cost of PCprebuilt – Cost of non-GPU partsprebuilt (3)
Price GPUindividual + Cost of non-GPU partsprebuilt > Cost of PCprebuilt (4)
(Price GPU+ Cost of non-GPU parts)disassembled > (Cost of PC)assembled (5)
Which is what we were looking for.
Since the parts are the left-hand side of (5) are now all in a disassembled state, we are effectively showing that the cost of disassembled parts are more expensive than the cost of a pre-built PC. This isn’t an exact “proof” that all parts individually bought are more expensive than all parts assembled, but it shows consumers who are knowledgeable with computers are asserting that pre-builts with equivalent parts can be cheaper than custom-built PCs.
Here is the link to pt.3 explaining why I think this scenario can occur: