Commentary of the Day - July 14, 2011: Where Has All The Money Gone? Guest commentary by Ralph D. Westfall.
A story of how administrative costs at the California State Universities (my Alma Mater) have grown in recent times:
For example, based on data in the California State University Statistical Abstract, the number of full-time faculty in the whole CSU system rose from 11,614 to 12,019 between 1975 and 2008, an increase of only 3.5 percent. In the same time period the total number of administrators rose 221 percent, from 3,800 to 12,183. In 1975, there were three full time faculty members per administrator, but now there are actually slightly more administrators than full-time faculty. If this trend continues, there could be two administrators per full-time faculty in another generation.The author goes on the recognize the pattern as Parkinson's Law, the tendency of bureaucracies to expand exponentially with time regardless of the amount of actual work to do. From Wikipedia (who had the example I was looking for):
The current form of the law is not that which Parkinson refers to by that name in the article. Rather, he assigns to the term a mathematical equation describing the rate at which bureaucracies expand over time. Much of the essay is dedicated to a summary of purportedly scientific observations supporting his law, such as the increase in the number of employees at the Colonial Office while Great Britain's overseas empire declined (indeed, he shows that the Colonial Office had its greatest number of staff at the point when it was folded into the Foreign Office because of a lack of colonies to administer). He explains this growth by two forces: (1) "An official wants to multiply subordinates, not rivals" and (2) "Officials make work for each other." He notes in particular that the total of those employed inside a bureaucracy rose by 5-7% per year "irrespective of any variation in the amount of work (if any) to be done."This, in turn, set me thinking about the three Great Books that explain almost everything you need to know about public policy:
In 1986, Alessandro Natta complained about the swelling bureaucracy in Italy. Mikhail Gorbachev responded that "'Parkinson's Law works everywhere."
1) The Peter Principle - Or why things always go wrong.
"In a hierarchy every employee tends to rise to his level of incompetence"The implications of this are that:
in a hierarchy, members are promoted so long as they work competently. Eventually they are promoted to a position at which they are no longer competent (their "level of incompetence"), and there they remain, being unable to earn further promotions. Peter's Corollary states that "in time, every post tends to be occupied by an employee who is incompetent to carry out their duties" and adds that "work is accomplished by those employees who have not yet reached their level of incompetence". "Managing upward" is the concept of a subordinate finding ways to subtly "manage" superiors in order to limit the damage that they end up doing. This principle can be modelled and has theoretical validity for simulations. However, all of the real-world evidence for it is anecdotal (and often intended to be humorous in nature).or as Peter himself succinctly summed it up:
The cream rises until it sours.2) The above mentioned Parkinson's Law.
My father is responsible for my reading both of these books, which he had around the house in the days that he was active in the nascent Teacher's Unions movement, and busy changing from a class room teacher to one the chief administrators of a small private law school.
The third book I discovered by myself in college. In my very first (of many) statistics courses this book was one of our "texts":
3) "How to Lie with Statistics"
Even if you can't find a source of demonstrable bias, allow yourself some degree of skepticism about the results as long as there is a possibility of bias somewhere. There always is.The great underlying theme of this book is that people "bend" statistics to fit their arguments. It's simply chock full of examples of how people attempt to deceive you when using statistics to make a point. All scientists (and anyone who reads or uses statistics in the press) should read this. Many of them appear to have done so. Unfortunately, instead of taking it as a cautionary exposition, they appear to have adopted it as a users guide.