Check out _The Mythical Man-Month_ for a refutation of this.
Quoting from memory:
- Nine women cannot have a baby in one month.
- Adding more developers to a late project makes it later.
The problem is that in order for throwing a thousand engineers at the problem to be time-effective, each one must communicate what he has learned to all of the others. That takes time and adds friction.
Your examples are only true because gestation and many software projects are not easily parallelizable. It's a rule of thumb that applies to many scenarios, but obviously not all. If it takes 2 hours for one person to mow his lawn, then 2 people could mow it in about 1 hour. 100 people really can lift 100 times the weight of one person. Not to mention that nine women can have nine babies in nine months.
Making many different aircraft prototypes simultaneously is certainly parallelizable, although it obviously would be enormously expensive.
In experimental tasks, parallelizing does not provide the same gain in success probability as accelerating the process of prototyping.
Building prototypes in parallel does not provide the benefit of a feedback loop, as the iterative process does.
Let's say you have a 10% probability of success on the first attempt, which improves by 40% after each experiment (to 14%, 19.6%...), and you have resources for 5 attempts. The chance of getting at least one successful solution is: parallel ~ 40.95%; iterative ~ 72.19%
Quoting from memory:
- Nine women cannot have a baby in one month.
- Adding more developers to a late project makes it later.
The problem is that in order for throwing a thousand engineers at the problem to be time-effective, each one must communicate what he has learned to all of the others. That takes time and adds friction.