| > Berglas's corollary, namely that no amount of automation will have any significant effect on the size or efficiency of a bureaucracy The article you're seeking demonstrates this one way. You can approach it another way: Amdahl's Law. Any process that takes time T has two parts: a part which can improve and a part which cannot improve. Let p be the percentage of the program which may improve. Symbolically, T = part that can improve + part that cannot improve or T = pT + (1-p)T Suppose we can introduce an improvement of factor k. Then the improved process time T' is T' = pT/k + (1-p)T or T' = T[p/k + (1-p)] The overall speedup S, then, is the ratio of the original time to the improved time. S = T/T' or S = 1/[p/k + (1-p)] It's so simple to derive, I love it. Say you have a bureaucratic process and you're asked to "automate it". You can plug in the numbers and play with them to get a feel for how much overall improvement you can expect. For example, how would the overall process improve in the (unlikely) case that you provided infinite improvement :) Bureaucracy is not necessarily, although often synonymous with, "composed of many, many parts." This implies that the "part which can improve" is small relative to the part which cannot improve. Amdahl's Law kicks in and improving those tiny parts have minuscule effects overall.
No amount of automation will have any significant effect on the size or efficiency of a bureaucracy. However, this raises an important philosophical question: if you improve a part, do you replace it? How many parts can you replace in a process before it is no longer the same process? |