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 psyco- industrial interpersonal optimization have resulted in the development of a simple 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 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 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.
Computer scientists hunt elephants by exercising Algorithm A:
- Goto Africa
- Start at the Cape of Good Hope
- Work northward in an orderly manner, traversing the continent alternately east and west
- During each traverse path
- 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 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 who do.
Operations research consultants can also measure the correlation of size and bullet color to the efficiency of elephant-hunting strategies, if someone 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. 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 administrating the best case social delivery system of manufactured alternative Indian Palm trees. Of course, it really doesn't matter, a federal grant paid for those studies.
Politicians don't hunt elephants, but they do follow the herds around arguing about who owns the droppings.
Software lawyers will claim that they own the entire heard based on the look and feel of one dropping.
Vice Presidents of Engineering, Research or Development try hard to hunt elephants, but their staffs are designed to prevent it. When the VP does go to hunt elephants, the staff will try to ensure that all possible elephants are completely pre-hunted before the VP sees them. If the VP does see a non-pre-hunted elephant, the staff will (1) compliment the VP'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 have 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 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 sixty seven percent confidence in statistics.