Retail toilet paper manufacturers not setup to handle load from people pooping at home instead of work (and corporate TP factories don't know how to sell to grocery stores):
Obviously you got to distinguish between problems that are going to get better over time and those that are going to get worse. It seems like people are just randomly assigning things to those categories. I mean, switching products from B2B to B2C (toilet paper, milk, flour, etc) is obviously something that can't happen instantly, but must be taking place as fast as humanly possible, right? So if you're writing an article about impending doom in the coming weeks and months, surely you need to pick a different topic, I would think.
>. I mean, switching products from B2B to B2C (toilet paper, milk, flour, etc) is obviously something that can't happen instantly, but must be taking place as fast as humanly possible, right?
No, because half the business world thinks that we're going to all re-open in two weeks, and isn't willing to spend money on any kind of retooling/restructuring for such a short period of time.
Certainly it is happening. My local stores have small amounts of yeast in little beverage cups with improvised seals, made by yeast manufacturers that usually sell large quantities to restaurants and industrial bread producers.
They've also briefly had shitty 1ply commercial toilet paper with big plastic bag and twist-tie packaging.
But is it "taking place as fast as humanly possible"? I believe vkou's comment is that 1/2 of the companies are not switching products, not that none are.
Nope. I said what I meant. Any system optimized for maximal efficiency on any measure becomes deoptimized as soon as that measure changes even a little bit.
> After all, we could use robustness as our optimization criterion.
It's almost impossible to optimize for "robustness". You are always optimizing some measure. You would have to deoptimize for all measures, and that's just silly from an engineering perspective.
The only thing you can do is to simply not optimize to the last 0.1%.
The whole toilet paper fiasco is a good example. Toilet paper is such a low-margin business that everybody optimized it to hell and back. Lines are already running 24/7 even in normal times. The consumer and industrial production is split so they can optimize them independently to squeeze those last couple fractional percentage points out by making commercial toilet paper even shittier.
Consequently, there is zero ability to absorb the demand shock that occurred when lots of commercial usage transferred to consumer usage.
I'm going to assume you are not arguing ad absurdum. Maximizing for X doesn't meant that factors Y, Z, etc. can be completely ignored. Nothing can be optimized "to the last 0.1%" given that other factors become important at that point.
(Eg, it might be possible to make to make space access more robust by spending the next 100 years of the world's combined effort to build a space elevator. But that's not going to happen because there's no perceived need to have that extra robustness given how much human focus is required.)
Forward error correction systems are designed to improve signal robustness in the face of noise - based on a given noise model. It can be made more robust by assuming a much higher noise than what actually exists.
This would probably require more transmission time. But the robustness level, by any usual quality measure, would increase.
"The whole toilet paper fiasco is a good example" ... for my clarified version, yes. That system was was optimized for profit extraction, probably also with the expectation that the government would throw money at them if things went really bad. ("Socialized risk.")
It was not at all optimized for an efficient transition to a widespread shelter-at-home world.
It could have been at least somewhat optimized for that, which is why I think your original statement was too broad. But it wasn't, because it was maximizing for profit, not social stability or happiness or other more nebulous criteria.
In the US, we have a free market that has resulted in the cost of milk production falling below the break even price for a lot of small dairy farms: https://www.jsonline.com/in-depth/news/special-reports/dairy...