Expecting a double in parallelism to yield a two times performance improvement is a best-case scenario that is unlikely. So there are a number of reasons why parallelism can be limited:

* Processes that are split typically must have their results merged, which may force the creation of an additional process or, if the merge process already exists, it may take more time to complete.

In reality, with every additional parallel resource (for example, CPU core), a fraction of the power effectively becomes unavailable or lost. As mentioned, if a batch process is split, there may be the need to merge the results. The merge process is the direct result of the increased parallelism, and this constitutes a piece of perceived processing gain we effectively lose. It's true that overall we can reduce elapsed time, but the scalability effect is real, and it grows as the number of parallel streams increases.