With the spread of multi- and many-core processors more and more typical task is to re-implement some source code written originally for a single processor to run on more than one cores. Since it is a serious investment, it is important to decide how much efforts pays off, and whether the resulting implementation has as good performability as it could be. The Amdahl's law provides some theoretical upper limits for the performance gain reachable through parallelizing the code, but it needs the detailed architectural knowledge of the program code, does not consider the housekeeping activity needed for parallelization and cannot tell how the actual stage of parallelization implementation performs. The present paper suggests a quantitative measure for that goal. This figure of merit is derived experimentally, from measured running time, and number of threads/cores. It can be used to quantify the used parallelization technology, the connection between the computing units, the acceleration technology under the given conditions, communication method within SoC, or the performance of the software team/compiler.