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[Sam Kimery: Possible yucks submission]

I posted this to yucks months ago when the list was much smaller.
It bears repeating, however, as an examination of the mssage headers
reveals that there are more people on the list now who didn't see it
the first time than there are who did!

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Date:    Wed, 24 Oct 90 08:45:12 -0500 
From:    Sam Kimery <kimery@ecn.purdue.edu>
To:      spaf@ecn.purdue.edu
Subject: Possible yucks submission

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   From:  landers@zeus.mgmt.purdue.edu (Chris Landers)
   Subject:  light reading 

   PACHYDERMIC PERSONNEL PREDICTION by Peter C. Olsen

   A bold new proposal for matching high-technology people and professions

   Over the years, the problem of finding the right person for the right
   job has consumed thousands of worker-years of research and millions of
   dollars in funding.  This is particularly true for high-technology
   organizations where talent is scarce and expensive.  Recently, however,
   years of detailed study by the finest minds in the field of
   psychoindustrial interpersonnel optimization have resulted in the
   development of a simple and foolproof test to determine the best match
   between personality and profession.  Now, at last, people can be
   infallibly assigned to the jobs for which they are truly best suited.

   The procedure is simple: Each subject is sent to Africa to hunt
   elephants.  The subsequent elephant-hunting behavior is then categorized
   by comparison to the classification rules outlined below.  The subject
   should be assigned to the general job classification that best matches
   the observed behavior.

   CLASSIFICATION GUIDELINES

   Mathematicians hunt elephants by going to Africa, throwing out
   everything that is not an elephant, and catching one of whatever is
   left.  Experienced mathematicians will attempt to prove the existence of
   at least one unique elephant before proceeding to step 1 as a
   subordinate excercise.  Professors of mathematics will prove the
   existence of at least one unique elephant and then leave the detection
   and capture of an actual elephant as an excercise for their graduate
   students.

   Computer scientists hunt elephants by excercising Algorithm A:
   1. Go to Africa.
   2. Start at the Cape of Good Hope.
   3. Work northward in an orderly manner, traversing the continent
      alternately east and west.
   4. During each traverse pass,
      a. Catch each animl seen.
      b. Compare each animal caught to a known elephant.
      c. Stop when a match is detected.

   Experienced computer programmers modify Algorithm A by placing a known
   elephant in Cairo to ensure that the algorithm will terminate.  Assembly
   language programmers prefer to execute Algorithm A on their hands and
   knees.

   Engineers hunt elephants by going to Africa, catching gray animals at
   random, and stopping when any one of them weighs within plus or minus 15
   percent of any previously observed elephant.

   Economists don't hunt elephants, but they believe that if elephants are
   paid enough, they will hunt themselves.

   Statisticians hunt the first animal they see N times and call it an
   elephant.

   Consultants don't hunt elephants, and many have never hunted anything at
   all, but they can be hired by the hour to advise those people who do.
   Operations research consultants can also measure the correlation of hat
   size and bullet color to the efficiency of elephant-hunting strategies,
   if someone else will only identify the elephants.

   Planners, who haven't the faintest idea what an elephant looks like or
   where it lives, will nonetheless plan a perfect utopia in which these
   hypothetical elephants are to be hunted.  Of course, this utopia (with
   five, ten, fifteen, and twenty year horizon plans) will never be
   achieved.  This is because all the other hunters are too damn busy
   already hunting or can't afford the costs of administering the best-case
   social delivery system of manufactured alternative Indian Palm Trees.
   Of course, it really doesn't matter, a federal grant paid for all those
   studies.

   Politicians don't hunt elephants, but they will share the elephants you
   catch with the people who voted for them.

   Lawyers don't hunt elephants, but they do follow the herds around
   arguing about who owns the droppings.  Software lawyers will claim that
   they own an entire herd based on the look and feel of one dropping.

   Vice presidents of engineering, research, and development try hard to
   hunt elephants, but their staffs are designed to prevent it.  When the
   vice president does get to hunt elephants, the staff will try to ensure
   that all possible elephants are completely prehunted before the vice
   president sees them.  If the vice president does see a nonprehunted
   elephant, the staff will (1) compliment the vice president's keen
   eyesight and (2) enlarge itself to prevent any recurrence.

   Senior managers set broad elephant-hunting policy based on the
   assumption that elephants are just like field mice, but with deeper
   voices.

   Quality assurance inspectors ignore the elephants and look for mistakes
   the other hunters made when they were packing the jeep.

   Salespeople don't hunt elephants but spend their time selling elephants
   they haven't caught, for delivery two days before the season opens.
   Software salespeople ship the first thing they catch and write up an
   invoice for an elephant.  Hardware salespeople catch rabbits, paint them
   gray, and sell them as desktop elephants.

   VALIDATION

   A validation survey was conducted about these rules.  Almost all the
   people surveyed about these rules were valid.  A few were invalid, but
   they expected to recover soon.  Based on the survey, a statistical
   confidence level was determined.  Ninety-five percent of the people
   surveyed have at least 67 percent confidence in statistics.

   ACKNOWLEDGMENT

   This study has benefited from the suggestions and observations of many
   people, all of whom would prefer not to be mentioned by name.

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