Sometimes an organization is complex because it has a lot of employees, rather than needing a lot of employees because it's inherently complex. You see the same thing with large software projects.
Twitter is a great example. I bet they have 20+ people working on a specific anti-abuse system. Another 20+ working on a specific ad type that makes the company money. Another team that just works on account security. Another team that works on internal tooling. Or the shared UI components team. Etc until you get the current state of Twitter.
All of those teams don't need to exist when Twitter is small, but do when they scale.
I was going off what I figured the poster was getting at: they don't understand how Uber has even 80% of their employees.
Uber is discussing laying off 20% of employees. 100 - 20 = 80.
It's completely reasonable to assume the OP was trying to figure out how they have so many employees, even after the layoffs.
eg look at datastores. If you can fit your data in postgres on a single (potentially really expensive!) computer, you probably need two or three of those computers for a primary plus a couple replicas and a DBA.
Once you outgrow that, going distributed costs a team. There is a big elbow in the cost and headcount curve.
Once you want a different specific capability beyond the standard distributed datastores, that costs multiple teams. Yet another big elbow in the cost and headcount curve.
This happens on data stores, applications, translations, currency, etc etc etc. Imagine a Greek person with a Greek bank account driving Uber in France being paid with an American amex card.
I don't have any insider knowledge, but I imagine just the support and operations org to manage and respond to all those riders and drivers can't be small.