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.


  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.

  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.


  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.


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