The precognitive decision maker

The precognitive decision maker

The PSI Communication Project at the Newark College of Engineering has been conducting research into the phenomenon of precognition, and the nature of the precognitive maker.

There is now evidence to suggest that the successful "hunch player" may have something more solid going for him or her than the odds of chance.

Experiments that the author has conducted indicate that what the texts call "non-logical" (and what managers privately call "lucky") decisions have some scientific - that is observable, dependable, and explainable - support.

The research project strongly supports the idea that some executives have more "precognitive" ability than others - that is, they are better able to anticipate the future intuitively rather than logically and thus, when put in positions where strong data support may not always exist, will make better decisions.

Moreover, a valid test has been developed for determining which people do, and which do no, have this ability.

The test consists of asking the participants to guess at a 100 digit number not currently in existence. Each of the 100 digits can take on any value from 0 to 9. The target that each participant guesses at is later generated by a computer using random number techniques. Each participant has his or her own specific target to guess at.

As expected, some people guess above the chance level of 10 correct guesses out of the 100 digits, while others guess at, or below, the chance level.

That some people score above chance on this test would, by itself, not prove they have precognitive ability. But the research has revealed some interesting and significant relationships between high scores on this simple guessing game and other kinds of data.

For example, participants are asked to rank their preferences among five metaphors (i.e. "a motionless ocean," "a dashing horseman") that have been adapted from a psychological test.

Based on their choices, the subjects are divided into "dynamic" and "non-dynamic" types. Admittedly, this is not a very sophisticated classification. But invariably, those classified "dynamic" by this relatively simple means, also tend to score above chance in predicting the computer's random numbers.

In tests on 27 different groups, ranging from four members to 100, "dynamic" men outscored "non-dynamic" ones in 22 of the groups. Statistically, the chances of this happening by accident are fewer than 5 in 1,000. Many other groups were tested since this initial 27 groups.

But what does "dynamic" executive mean? Whatever it connotes, it also must be measured somehow by performance.

So four groups of chief operating officers of corporations, all of them in their present jobs at least five years, were asked to take the tests. These men had held office long enough to be responsibility for the reliability of their decisions and the recent performance of their companies.

The first two groups of chief executives who met the above criteria were divided into two classes - those who had at least doubled profits in the past five years, and those who had not, including some who had lost money.

Of the 12 men whose companies met the deliberately extreme test of double profits, 11 scored above the chance level on the computer guessing game. One scored at the chance level. Not a single one fell below chance.

Of the 13 who had not doubled profits, seven scored below chance, one scored at chance, five scored above chance. This last five had improved profits by 50 to 100 percent.

Of the seven who scored below chance, five had improved profits less than 50 percent. Only two of those who scored below chance had improved profits more substantially than that.

The chief executives who had more than doubled their companies' profits in five years had an average score of 12.8.

Those who had not met this criteria scored an average of 8.3, well below what they should have achieved even on a random basis.

To give one striking example of the difference between the two groups:

Over a five year period, one president had increased his company's annual profit from $1.3 million to $19.4 million. His test score: 16.

Another had been able to increase his profit by only $374,000. His score: Eight.

A third group of presidents, 41 members of the Steel Distributors Association, participated in an experiment done at the Princess Hotel in Acapulco, Mexico. Of the 41, 11qualified for the category of "company president of at least five years of tenure." Of the 11, nine had at least doubled their company profits over the last five years. Eight of the nine scored above chance. Their average was 11.44 percent. The remaining two presidents who had not at least doubled their company profits averaged 9.5 percent, with both scoring at chance or less.

The fourth group was composed of 20 Canadians. Of the 20, six "qualified" as company presidents who had been on the job for at least five years. Five of the six at least doubled the profits, while one fell in to the 50 to 95 percent improvement class. Of the five doublers, three scored above chance, while the other two were below chance. The sixth person scored at chance level.

Here is a summary of the results of the four groups:

PRESIDENT'S SCORES

Percent increase in profits over the last five years

Increase:	Above Chance	Chance	Below Chance
Greater than 100%	81.5%	25%	27.3%
50% to 99%	18.5%	50%	18.2%
Below 50%	0%	25%	54.5%

TABLE II - Presidential Scores vs. Profit Improvement

This finding has interesting implications for selection of executives for the "top spot."

Given a group of people who have the usual traits needed for such a position, which one should be selected?

This author feels that it should be the person with the extra something, in this case the ability to make good decisions under conditions of uncertainty.

In the groups of presidents who were tested, had the selection been made on the basis of their scores, there would have been an 81.5 percent chance of choosing a person who at least doubled the company profits, while if a below chance scorer had been chosen, there would have been only a 27.3 percent chance of choosing a person who would have doubled the company profits.

The engineer and problem solving

The function of the engineer is to solve problems. To do this, he must come up with ideas that result in new methods, techniques, processes, products, or equations.

However, the engineer doe snot merely solve "text book" problems that call for selection of the necessary facts or formulas from the appropriate handbook. On the contrary, the vast number of problems that the engineer confronts daily are of the type that do not have just one answer. Several solutions are possible.

Logically, if the many possible alternative solutions could be generated and analyzed, an optimum, or least a satisfactory, solution would be reached.

In solving problems, the engineer will also have to delve into areas beyond the confines of established technical knowledge. The engineer has to consider variability and uncertainty.

In the area of Risk Decision Analysis, the Department of Defense has studied the facets of uncertainty and come up with a breakdown of uncertainty into "known unknowns," where you are aware of your areas of uncertainty, and "unknown unknowns," where you are not aware of your areas of uncertainty.

The engineer has to deal with these uncertainties, when designing a product for future use, where the characteristics of the user and the environment may only be guessed at. In addition the engineer has to deal with these uncertainties when making decisions as to which alternative to pursue. Should method A be chosen over method B? Is material A better than material B? Which of several possible product developments should time and effort be spent on?

A large west coast based electronics company founder recently related to the author how he decided to "go" with a newly developed product, still in its infancy, contrary to the advice of five experts, and of his partner, who, as a result, left him; and he succeeded in building a multi-million dollar corporation around the device.

The variability, uncertainty, and diversity of the components of a technical problem can easily upset the most painstaking engineering calculations.

Besides technical know-how, the engineer has also to have what is usually called engineering judgment.

Development of precognitive abilities

The utilization of precognition ability

Some anecdotes

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