Many research and anecdotal reports point to the concept of intuition as a means by which psychic functioning merges with normal information processing to produce effective decision-making and assessment under conditions of insufficient sensory information. In business, intuition is increasingly valued as a way to deal with a world of greater choices, massive information overload, and less time to screen alternatives. Mainstream psychology has traditionally viewed intuition as simply a rapid or unusual use of our standard complement of cognitive functions. Many anecdotal accounts, however, contain prominent elements that cannot be fitted into that model and seem to fall in the domain of parapsychology. Converging lines of research from intuition studies, anecdotal material and parapsychological research support an effort to identify "intuitively advantaged" individuals by creating talent identification tools suitable for eventual deployment in the workplace.

As an initial exploration in this area we have developed the "Intuitive Market Trader," (IMT) a computerized stock market simulation employing a simple "buy low-sell high" strategy using shares from a selection of imaginary companies. Behind the simulation is a binary precognition test based on 200,000 trials with a Marsaglia pseudorandom number generator. In this exploratory research we examine the effectiveness of three different methods of data analysis for the purposes of talent identification. Two of these methods are "pure psi" methods and one is a hybrid that combines psi information with normal information. The hybrid method embodies how decision-making functions in the real world, however it is subject to the statistical problem of optional stopping and cannot be used as evidence of psi ability as such. Along with the IMT we administered Taggart's Personal Styles Inventory (PSI), a 30-item test that assesses six information-processing modes and leads to a classification of rational or intuitive. This test is aimed at business and workplace situations.

Data were obtained from a total of 77 participants, 39 males and 38 females, from a wide range of professions and occupations. Overall scoring was at a rate of 50.02%, which resulted in z = 2.394, p(2t) = .017. This amounts to a binary trial effect size of 6.1 x 10^-4. Using a single-mean t-test for a subject-based analysis the overall result is t = 1.828, df = 76, p= .071. The principal pure psi analysis identified two participants who produced significant results (2-scores of 1.99 and 2.78). The hybrid analysis, which capitalized on the effects of the participants' sell decisions as well as buy decisions, identified seven participants, including those identified by the first method. Individual PSI factors did not correlate significantly with the results of the pure psi analysis but the group of participants classified as Intuitive produced overall significant scores, t = 2.072, df = 55, p(2t) = .043, while the Rational group were close to chance, t = 0.141, df = 20, p = .889. The groups were not significantly different from one another, however. The identification of two participants out of 77 is not unexpected by chance, but it should be noted that one of those was the only stock market day-trader in the group and the owner of a thriving small business. The other person identified was his wife and business partner. In addition to these, the hybrid analysis identified a number of high-performing professionals in different fields. We regard this as an encouraging start for talent-identification using business simulations and recommend further work that collects a greater amount of data from each participant.