Some architects may be familiar with Amdahl’s law that looks at the maximum improvement when only a part of the system can be optimised, as it is often used in parallel computing processing. The important part here of Amdahl’s law is to see that savings in part of a system usually will show that to realise savings you first need to achieve a critical mass before seeing substantial benefits. Since however virtually all improvements are are only part of a larger system it is important to apply Amdahl’s law beyond computing.
Another saving topic is that of experience or what is usually referred as to ‘ well traveled road effect’ where potential savings are underestimated as the experienced people will usually underestimate time spent on any task and as such cannot see any room for improvement. So if you are trying to realise savings in any area it is usually advisable not to rely on to too experienced people in the process.
The opposite of the underestimation of savings through the ‘ well traveled road effect’ is the time saving bias that afflicts everyone of us, when we stop to consciousness think about it. The time saving bias is best demonstrated in traffic where we misestimate the time we save by increasing our speed. The same miscalculation is also observed when a lot of additional doctors are hired too decrease the waiting times in hospitals often estimating a huge decrease in waiting times by employing 10 % more doctors and often finding out after a while that the increase did not lead to any shorting of waiting lists at all.
As such we all need to be careful about the the many traps we as humans are likely to fall for when estimating and calculating savings.