3 * O(n^2) vs O(n^3)
Multiplying $O\left(n^2\right)$ by $3$ doesn't change it.  Literally, it remains the same thing:

$$3{\cdot}O\left(n^2\right)~=~O\left(3n^2\right)~=~O\left(n^2\right).$$

This is because such complexity qualifications don't track scalar multipliers.

The reason that we discard scalar multipliers is pretty simple: the actual run time will depend on how fast particular computer instructions work, such that if we cared about scalar factors, our complexity qualifications would become extremely context-specific.

For example, many real-world systems will speed up as they run a long-running algorithm due to optimizations that kick in as an algorithm runs (e.g., branch profiling CPU's and hot-spot code optimizations in VM's).  So, any scalar projection of run-time behavior would have to account for these factors.  Such an analysis could still be quite helpful and worth studying when appropriate, but that's not the role that complexity classes intend to fill.

So, as general performance analyses qualifications, complexity classes tend to focus on the largest order-affecting factors while hand-waving the scalar stuff as implementation-dependent.