Pachydermic Personnel Prediction
by Peter C. Olsen
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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 interpersonal 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.
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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 rule 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
exercise.
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 exercise for their graduate students.
Computer scientists hunt elephants by exercising Algorithm A:
- Go to Africa.
- Start at the Cape of Good Hope.
- Work northward in an orderly manner, traversing the continent alternately
east and west.
- During each traverse pass,
- Catch each animal seen.
- Compare each animal caught to a known elephant.
- 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 big 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
the 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.
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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
are 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.
This article first appeared in Byte, 1989
STOP BIT, Peter C. Olsen.
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