That’s part of the communication challenge. If the audience doesn’t understand exponential growth (kind of surprising for a bank exec) then you still have to explain the problem in a way they will understand.

“The current growth trajectory means we’ll be out of capacity in a month, and it takes 3 weeks to install more capacity, so you’ve got a week to find the budget. If we don’t do this, customers will experience a slower service which may lead to complaints and reputational damage.”

It’s also possible that the execs understood perfectly and were happy to accept the risk of the service being slower for a short period of time. Maybe the Internet-using customer base was tiny, or the service in question wasn’t critical, or the execs were handling general financial pressures leading them to want to sweat every asset until it was impossible to ignore, or maybe they just understood that “the internet being slow” was normal for the 90s and it would be unlikely to hit their reputation in the long term.

Also the behavior of queues is surprising. Average wait time does not tell you much about the distribution of wait time, and is an extremely nonlinear function of the number of queues.

https://en.wikipedia.org/wiki/Queueing_theory

Perhaps using a log-scale y-axis would help!