It's still impressive. A 5x increase at that scale can be a phenomenal challenge. Where do you source the ingredients? Where do you build the factories (plural because at that scale you almost certainly have multiple locations in different geographic locales subject to different regulatory structures). Where do you hire the people? How do you manage it? What about the storage and shipping and maintenance of all the equipment and on and on? How much do you do in house how much do you outsource to partners? What happens when a partner goes belly up or can't meet your ever increasing needs?
Your comment is a great example of what the OP pointed out.
> The menu team comes up with interesting ideas like including kale in salads. The procurement team and suppliers then try to get the menu team to understand the challenges. How do you bring kale to 14,000 restaurants? As one example, when they introduced Blueberry Smoothies in the U.S., McDonald’s ended up consuming one third of the blueberry market overnight.
https://www.forbes.com/sites/stevebanker/2015/10/14/mcdonald...
I couldn't find any other source to back it up, but still wow! That's an absurd number.
In the case in animal product, there are almost certainly major operations worldwide that have been built and financed purely to serve McDonalds demand. They probably have to even build these out well before entering some markets.
They raise a lot of chickens in the US. I’ve hauled chicken nuggets or chicken breasts for McDonald’s in the past quite often.
I can’t even tell you where they grow blueberries.
Taking the software example, you can easily scale from 1 to 100 users on your own machine. You can handle thousands by moving to a shared host. Using off-the-shelf web servers and load balancers will help you serve a million+. From there on you'll have to spend a lot more effort optimizing and fixing bottlenecks to get to tens, maybe hundreds of millions. What if you want to handle a billion users? Five billion? Ten billion? It always gets harder, not easier.
Pushing the established limits of a problem takes exponentially more effort than reusing existing solutions, even though the marginal improvement may be a lot smaller. Getting from 99.9% to 99.99% efficiency takes more effort than getting from 90% to 99%, which takes more effort than getting from 50% to 90%.
You never pierce the scaling wall. It only keeps getting higher.
Each employee adds some overhead, which requires more employees... which requires more employees.
To add something useful as well besides snark, first of all, there are hard physical limits, which are sometimes well within context (you really shouldn’t try to outcompete light speed for example, relevant in some high-freq trading, infrastructure projects). Then you can try to increase headcount to any number, you won’t produce for example a better compiler. There are simply jobs that are more “serial” - the only way to win at those is to try to employ the very best of the field in a small team.
“Never underestimate the bandwidth of a station wagon full of tapes hurtling down the highway.“ -Andrew Tannenbaum
1M users and 10k employees is not in the range where you have crushingly impactful logistics.
That's a 2X increase. Now do it again and a half for a 5x. Crazy to say there's a "scaling wall" that once you "pierce" it's easy to scale up. It's the opposite, McDonald's already knows how to supply and sell X McRibs a year, there's no company that's ever sold 5X those McRibs so they have to figure it out themselves.
Anecdotally I experienced this when scaling my software product from 1 --> 10 --> 100's --> 1000's etc. of users.
Thats not to say 2x can't be a substantial challenge, as you pointed out. It gets harder (and IMO more fun) when you're at the bleeding edge of your industry.
This is absolutely not true. The closer you are to peak performance, the harder it is to scale, and the returns diminish heavily. At many major tech companies, there's a huge amount of effort into just 1% - 5% optimizations -- these efforts really require creative thinking and complex engineering (not just "scaling existing processes".) At the volumes these companies operate, even a 1% optimization is quite significant.
If you're on 100M users you're probably scaling vertically. So adding 5x more hardware shouldn't be a problem.
But when you're at 500M all of a sudden it makes sense to optimize further since the capital saved will be the same percentage(ish) but the money is worth peoples time all of a sudden.
I know that we don't care particularly about power savings in the DCs I've worked in, because they're relatively small. While bigtech will do all kinds of shenanigans to save a couple watts here and there, because it's worth it across your hundreds of thousands of servers.
If only things were that simple. https://en.wikipedia.org/wiki/Amdahl%27s_law
Building five "Netflixes" with identical content is possible; the amount of content wouldn't change (it would decrease, the cynic says); you just need parallel copies of everything (servers, bandwidth, etc).
The fun would come in syncing usernames, etc through the system.
It's an entirely different class of problem compared to "acquire resource, convert it, sell it".
Sorry, you gotta overhaul majority of your architecture and its components to scale by every 10x. It's not a single "scaling wall" to break through but it's more of a relentless stream of uphill battles. And this gets even more interesting when you reached to the point where there's no prior art for your problem, usually at hundreds of billions of users.
Making 5 things and making 5,000 things is as different as making 50,000 things and 1m things. There are always cost constraints at each level, and each design can only go so far.