Figure 4

Summary of Strategic Patterns

Overview of Total Research Study

Chapter 2 reviews the findings of major authors in the field of intuition research and forms the foundation for the testable hypotheses to be used to examine the research question. 

Chapter 2

Literature Review

Intuition is a relatively new subject of academic interest.  Literature on the subject, particularly on its use in decision-making did not become prevalent until the early 1970s (Argyris, 1973a, 1973b; Clark, 1973; Dean, Mihalasky, Ostrander, & Schroeder, 1974; Jung, 1971; Leavitt, 1975a, 1975b; Livingston, 1971; Mintzberg, 1973, 1975, 1976; and Simon, 1977).  These works, along with research in the 1980s, incorporated intuition related literature and research prior to the 1970s and as far back as the 1950s (Riggs, 1987). 

This research study concentrates specifically on the research literature as it relates to the use of intuition in decision-making among organization managers and executives. Various organizational environments are examined in the literature review and thus, may be reasonably considered an overview of the subject.   This research is classified into two categories: (1) theoretical developments concerning the concept of intuition, and (2) survey studies supporting the premise for using intuition in decision-making. The overview provides information on the use of intuition in business organizations as a function of leadership and decision-making; and explores various well- established methodologies as well as those still in development.

Definition of Intuition

The term intuition is defined as “knowing something instinctively; a state of being aware of or knowing something without having to discover or perceive it…”.  (Encarta, 1999). Intuition is seen as an innate capacity not directly accessible by considering the process which gives rise to a judgment or action involving it.  Thus, intuition seems to be a residual process accommodating whatever can’t be explained by other means.

The literature reflects the inherent lack of obvious conceptual framework for the term intuition.   Some of the alternative descriptors are ESP, psi, judgment, insight, and gut feelings (Dean, Mihalasky, Ostrander, and Schroeder, 1974); hunch (Barnard, 1968); extrasensory perception (Leavitt, 1975b); non-rational (Cohen and March, 1974); recognition (Goldberg, 1983; Ray and Myers, 1986), and edge (Tichy, 1997).  Such non-specific definitions suggest that different authors and researchers could be describing different processes or even measuring different phenomenon. Conversely, experts could be referring to the same phenomenon with different labels.

Major Theorists

This study attempts to capture the value of various theorists’ approaches by focusing on the central contribution of each, and how these compare or contrast to Organizational Engineering theory.

Theorists are often classified as personality based such as Jung or transpersonal based such as Vaughan. The more classical theorists’ approach view intuition as a distinct pattern of thought from the rational mode (Jung, 1971), while the transpersonal theorists’ approach considers the integration of rational and intuitive approaches and considers them both valid and separate, as well as complementary (Goldberg, 1983; Vaughan, 1979)

One of the most important figures to focus on the concept of intuition is Carl Jung.   His theory of psychological types is the basis for the development of the widely used Myers-Briggs Type Indicator (MBTI) (Kroeger and Thuesen, 1992).   Jung’s theory of intuition suggests intuition is a psychological function present in all people to varying degrees and is manifested in personality types.

Jung defines intuition as a perception and comprehension of the whole at the expense of details attributable to unconscious process.   Intuition is thus viewed as a cognitive function outside the province of reason and given consideration whenever established rational or other cognitive concepts do not work.   In short, it is the perception of reality in which the intuitive knows, but does not know how he knows (Clark, 1973).   Later, Jung broadens his thoughts on personality types by introducing the concept of synchronicity, which further helps to explain intuitive-type feelings and visions not attributable to coincidence (Rowan, 1986).  Jung uses such phrases for intuition as hunches, inspiration, and insight to problem-solving methods, all of which reflect little patience for detail or routine (Behling and Eckel, 1991).

Vaughan (1979) describes four levels of intuition: physical, emotional, mental and spiritual.   The theorists, writers and researchers describe intuition in both psychological and physiological terms.   Intuition experienced through physical levels includes bodily sensations such as tension or discomfort. This is not to say however that every bodily sensation indicates an intuitive message, but these physical symptoms can be used for self-awareness, as well as a source of warnings and signs.  

Emotional intuitive messages take several forms, such as liking or disliking something or someone for no apparent reason, feeling the need to perform an action or do something, and sensing energy levels in oneself or others.   Emotional level intuition can be used to deepen one’s self-awareness and to understand others (Vaughan, 1979).  

The mental level of intuition is typically experienced as images or ideas. It may appear as the perception of patterns, insights, or images, especially in problem-solving situations.   Intuition at the mental level can be used to trigger creativity, explore problem-solving areas not previously mined, and to enhance learning (Vaughan, 1979).  

Spiritual intuition does not rely on sensations, feelings, or thoughts. In fact, these are considered being distracters at the spiritual level (Blackwell, 1987; Vaughan, 1979).  Spiritual intuition is a means for improving self-awareness and transpersonal experiences.    

Vaughan does not clarify whether a single intuition mode is responsible for all four types or whether unique factors exist for each type.  This generality suggests Vaughan is defining taxonomy rather than a theoretical specification which can be tested and validated through scientific methods.

Salton’s Organizational Engineering theory however does account for all facets of Vaughan’s taxonomy.   Salton’s theory focuses on inputs and outputs, regardless of the source or the outcome. Vaughan’s physical, emotional, mental or spiritual intuitive factors can be accounted for with equal facility.  Salton’s Organizational Engineering theory argues intuition is the result of a single process. Therefore, there is no operational need to specify the source or destination of the input-output chain (Salton, 2000).  Vaughan’s approach may be of value in describing intuition but it is not suitable to test the concept. Like Vaughan, Salton is indifferent to the source of the input providing the initial drive toward an external response. Further, Salton makes no judgment about the value, or lack of value, of these explanations.

The rational approach to intuition accepts the notion that the human mind has alternative methods of processing information and these methods influence behaviors.  For example, Jung posits four independent but interacting categories of cognition—intuition, thinking, feeling, and sensing.  Each of these categories can be operational at any particular time and any combination favored by a particular individual and gives rise to unique behaviors.

There are two views regarding the availability of intuition in individuals.   One view suggests intuition is potentially available to everyone (Goldberg, 1983; Vaughan, 1979), while the other group professes individuals to be either intuitive or non-intuitive (Jung, 1971; Agor, 1984b). Researchers have even estimated what percentage of population they believe is in each category.   Peavey (1963) as reported by Thornton (1971) agrees with Jung’s notion that intuitives are rare, only 25% of his research sample were individuals whom he would define as intuitives.

Salton views intuition as a probabilistic outcome of a particular information processing strategy.  The combination of an unpatterned method in acquiring input and a thought mode of output produce unexpected insights easily classified as intuition.  This strategic posture, termed Changer within Organizational Engineering, serves a function within particular segments of a social group.  The Changer is characterized by rapid idea generation, high failure rates, quick application, uneven optimality, high uniqueness, and potentially high disruptive potential (Salton and Fields, 1999).  Therefore, while valuable, social system can only tolerate a certain proportion of its members subscribing to this strategic pattern.  Beyond that level, the system will become unstable and the pattern will become dysfunctional (Salton and Fields, 1999).  In periods of relative economic and social stability it is reasonable to expect the relative proportion of people subscribing to the Changer strategic pattern (Salton’s equivalent of an intuitive) will be a minority within the population.

A study by MacKinnon in 1962 as reported by Thornton (1971), which used a select group of creative individuals, reflects a preference for intuition among 90% of that sample, in contrast to the general population figure of 25% most frequently cited.  Peavey (1963) as reported by Thornton (1971) found approximately 25% of his sample were intuitives.

Salton’s Changer orientation accommodates such cases as MacKinnon’s.  Organizational areas where the roles and responsibilities of individuals are to identify and create new products or initiatives, such as in Research and Development, must attract and retain more creative people in order to be strategically competitive (Salton, 2000).

Intuition as a concept and theory has been explained and defined in a variety of ways.   Jung (1971) explains intuition as form of perception (one of four; the other three being; thinking, feeling, and sensing). Agor (1984b) and Goldberg (1983) view intuition as a process of knowing something without understanding how one knows it.   Vaughan (1979) views intuition as a non-rational mode of knowing as opposed to a rational mode. She describes intuition as a distinct process characterized by directness, immediacy, perception, and unconscious processing of information.

The base theorist for the current concept of intuition is Carl Jung whose psychological types are explained in his general theory of personality (Jung, 1971). Jung elaborates on intuition as a core aspect of human experience within the field of psychology.   Jung relates the concept of subconscious to intuition and in his early research relates unconscious to refer to what is currently known as subconscious.   His theory connects intuition as a function of personality rather than knowledge experience.   Jung does not believe intuition is related to inference.   Jung believes intuition operates beneath the conscious realm and is made without the limitations and constraints of rationalism and logic.   Jung also believes the intuitive process and how it accesses knowledge is indiscernible. In other words, the intuitive or intuitor knows, but does not know how he/she knows.  This theory is also the basis, either directly or indirectly, for many of the instruments, which have been designed to measure intuition preference levels.

In Jungian Theory (1971), human experience is composed of four basic functions: intuition, sensation, feeling, and thinking. Individuals possess and utilize all four functions to varying degrees.   He further divides these functions into rational or concrete functions (thinking and feeling) in which people evaluate experiences and come to conclusions and non-rational or abstract functions (intuition and sensation) in which people capture experiences and gather information.  Concrete intuition balances perceptions concerned with the actuality of things; it is a reactive process, which responds to given facts. Abstract intuition is what mediates perceptions of ideals and connections, and is stimulated by an act of will or intent.   

Jung’s theory of personality is more complex than just intuition and included various other aspects.  “Intuition fully described is ‘introverted intuition with thinking,’ or ‘extraverted intuition with feeling,’ and on through all combinations of the function” (Blackwell, 1987).   Jungian psychology which identifies the four types has been viewed as useful in understanding and developing decision-making and problem-solving skills in business (Catford, 1987).  Jung also believes that people have a tendency to favor or have one dominant type over the others.    Jung suggests there are innate, unconscious modes of understanding which regulate our perception itself.   These are referred to as archetypes, which is an inborn form of intuition (Hyde and McGuinness, 1994).   

Jung’s theory of intuition believes there is psychological functions present in all people in varying degrees and manifested in personality types.   Intuition is a perception and comprehension of the whole at the expense of details based on unconscious processes.  Furthermore, intuition is a cognitive function outside the province of reason and is used wherever established values and concepts do not work.   In other words, it is the perception of reality not known to consciousness self in which the intuitive knows, but does not know how he/she knows (Clark, 1973).

Jung (1971) also further delineates intuitive types as extroverted or introverted.  The extroverted intuitive personality perceives implications and possibilities in the external world, while the introverted intuitive focuses on the inner world and perceives the implications and possibilities of his/her own conscious processes, both personal and collective. 

Later, Jung broadens his thoughts on personality types by discussing the subject of synchronicity which further helps to explain intuitive-type feelings and visions separate from coincidence (Rowan, 1986).   Jung relates such phrases as hunches, inspiration, and insight to problem-solving with little patience for detail and routine (Behling and Eckel, 1991).    Jung’s general theory of personality is the basis for the Myers-Briggs Type Indicator self-reporting instrument (Myers and McCaulley, 1985; and Kroeger and Thuesen, 1992). 

However, Salton’s Organizational Engineering is indifferent to the Jungian approach.  Jung’s concepts of introvert may be applied to Salton’s Relational Innovator and Hypothetical Analyzer strategic patterns which exhibit behaviors roughly consistent with those of the introvert, but, this does not mean they are the same, simply that they are correlated or share similar traits.

This study recognizes the continuing contribution of Jung to the field, especially as applied to individuals.  However, in modern society, groups of individuals are the principal contributors to the common well being.  Unfortunately, Jungian theory does not lend itself to the consolidation of individuals in groups.  The principles of Salton’s Organizational Engineering, on the other hand, have been shown to produce statistically significant and reliable results when applied to individuals in interactive groups (Soltysik, 2000.  Therefore, Salton’s Organizational Engineering methodology is the more appropriate choice for studying organizational development initiatives.    

Having said this, both Organizational Engineering and Jungian theory offer alternative explanations to intuition.  Jungian is psychologically based and assumed to be a fixed component of the individual.  The hypothesized organizational prescription will be to identify individuals and/or groups endowed with intuition and place them in a position that makes use of their talent.  In contrast, Organizational Engineering views intuition as a strategic response to an environment, individuals and groups can be taught to make use of the strategic styles or patterns (Salton, 1996).      

For the purpose of this study, both Organizational Engineering and Jungian theory are relevant and identified in the literature review and useful in exploring intuition. The theories actually address two slightly different things, i.e., Organizational Engineering focuses on the individual as participant in group behavior, while Jungian theory focuses more narrowly on the individual. Subscribing to Organizational Engineering principles does not preclude simultaneously subscribing to those of Jung.  These facts will suggest there is no need to prove one wrong and the other right.  They both can coexist.      

Maslow (1970) addresses intuition in his theories of human psychology.  Maslow characterizes intuition as intrinsically and innately tied to the human psyche.   Maslow suggests this inner capability is what contributes to the existence of the evolution of self and self-actualization.  Maslow also relates this inner nature with creativity.  Maslow purports creativity in self-actualizing people is spontaneous and easy, as well as less concerned with the absolute truth or correct answer.  Figure 5 illustrates Maslow’s hierarchy.

Figure 5

Maslow's Hierarchy of Needs (Adapted from Maslow’s Need Hierarchy, Abraham Maslow, 1954)

Maslow (1970) also discusses intuition and its suppression in his theory of denial.    Here, he states, people tend to suppress their intuition or creativeness out of fear of knowing themselves or to avoid identifying personal areas in need of development.  This is similar to rational versus non-rational thought processes and was discovered in the literature to contribute to less identification of intuition in decision-making. Maslow indicates when one has knowledge, action follows and choices can be made without internal conflict.    However, with such self-discovery comes responsibility for action and often means change accompanies such actions that typically go against some norm.   Therefore, Maslow suggests, most people take the path of least resistance; they conform to rational norms, behaviors, and thought processes that are acceptable to the majority.  This tendency is sometimes described in decision-making situations as siding with the status quo, a common and sometimes dominant response.    

Salton’s Organizational Engineering theory agrees with Maslow’s underlying precepts.  Intuition is available to all and is an innate part of the human structure.  Salton makes no assertions as to why people are as they are beyond those dictated by the environment within which they exist.  Concepts such as self-discovery and self-actualization lie in the realm of psychology and by Salton’s Organizational Engineering standards may or may not be true.  While the other factors and causal sequences Maslow notes may be meritorious and worthy of pursuit, Salton claims only to be able to explain observed behavior by reference to method and mode. For example, physics explains how nuclear energy can be produced, but does not tell society what to do with it.  Similarly, Salton explains how intuition arises; he does not assign a generalized value to it.  Intuition is viewed simply as one of many variables needed to run a successful social structure or business enterprise (Salton, 2000).      

Therefore, Salton’s views do not contradict those of Maslow.  In fact, Salton agrees with Maslow’s core thinking but is indifferent to the applications. As in the case of Jung, there is no need to design an experimental study to disprove one or the other; both schools of thought can coexist. While Maslow suggests an individual’s motivation and subsequent actions are based on their needs, Salton suggests an individual’s actions are based on their preferences.

Researcher

Researchers, academicians, and writers most noted for their contribution to the use or potential use of intuition in business, more specifically, management and decision-making include Agor (1983a, 1983b, 1984a, 1984b, 1985a, 1985b, 1986a, 1986b, 1986c, 1986d, 1987a, 1987b, 1988a, 1988b, 1989b, 1989c, 1992a, 1992b, 1992c, 1992d, 1993); Barnard (1938, 1968); Cappon (1993, 1994); Dean, Mihalasky, Ostrander, and Schroeder (1974); Frantz and Pattakos (1996); Isenberg  (1984, 1985); Jackson (1989); Kroeger and Thuesen, (1992); Leavitt (1975a, 1975b); Mintzberg (1973, 1975, 1976, 1979); Peters and Waterman (1982); Raudsepp  (1981); and Parikh (1994).  Others contributors to the study the use of intuition include Vaughan (1979); Goldberg (1983) Rowan (1986); and Emery  (1994, 1995).   These numerous recent studies testify to the increasing importance assigned the subject of intuition as applied to organized endeavors, such as work or project teams, leader selection and recruitment, organizational design, and research application.  The subject matter would seem to be of substantive interest to the academic community. The findings of these researchers will be elaborated upon further throughout this study. 

One of the first authors to discuss the use of non-logical processes in decision-making was Chester Barnard in The Functions of the Executive (1968)Barnard suggests that managers use non-logical decision-making, which balances rational and intuitive, and discussed his research insights in a public presentation:

I have found it convenient and significant for practical purposes to consider these mental processes consist of two groups, which I shall call ‘non-logical’ and ‘logical’.   These are not scientific classifications, but I shall ask you to keep them in your minds for the present, as I shall use them throughout this lecture.   In ordinary experience the two classes of intellectual operations are not clearly separated but meld into each other.   By ‘logical processes’ I mean conscious thinking which could be expressed in words or other symbols, that is, reasoning.   By ‘non-logical processes’ I mean those not capable of being expressed in words or as reasoning, which is only known by judgment, decision or action. (p. 302)

It seems to me clear that, whatever else may be desirable, it is certainly well to develop the efficiency of the non-logical processes.  It is the process by which an immense amount of material is unconsciously acquired for the mind to use, and intelligence can aid in selecting the field for action, the line of experience, that is promising. (p.321)

Barnard suggests both logical and non-logical thinking is necessary in the everyday affairs of a successful manager.   In fact, Barnard’s theory of cooperative behavior in formal organizations may be considered a forerunner to the shared values discussed in today’s corporations. 

Barnard (1968), along with Herbert Simon (1977), argue organizational decision- making is a distributed activity, extending over time, and involving a number of people. Because decision-making is a process rather than a discrete event, one critical management task is to shape the environment of decision-making in a way that produces desired ends. This perspective contrasts sharply with the psychological theories which view decision-making as a personal responsibility, rather than as a shared, dispersed activity an individual must orchestrate and lead (Barnard, 1968 and Simon, 1977).

Given Barnard’s perspective on distributed decision-making and the value of intuition within the executive’s skill repertoire, it is reasonable to suggest that Barnard believes intuition is a phenomenon which should be reorganized and managed like any other element in the decision-making environment.  If this inference is true and if managers follow Barnard’s prescription, even without knowing it. This study hypothesizes Salton’s intuitive strategic profiles of Relational Innovator and Reactive Stimulator will be distributed within working groups and those groups making the most important decisions will tend to have greater representation of the intuitive patterns (Salton, 2000).

Salton seems to support Barnard’s position regarding the importance of intuition as a component of organizational decision-making, and emphasizes Organizational Engineering’s value as a tool to describe group as well as individual decision-making behaviors (Soltysik, 2000).  Therefore, Organizational Engineering incorporates both Barnard’s organizational theory, as well as Jung’s psychological approach to the use of intuition.

Westcott (1968) was one of the first to do experimentation examining psychological research on intuition. In fact, he is one of only a few researchers, to date, involving only about a dozen studies for a period of about fifty years which had described, observed, or attempted to measure to some degree the function of intuition.  Westcott believes intuition or intuitive knowledge is learning process-related, rather than detail- or content-related. He further suggests intuitive knowledge is generally not acceptable to the general public, which on the whole, requires a more rational approach.  

Westcott (1968) defines intuition as occurring when an individual reaches a conclusion on the basis of less explicit information than is ordinarily required to reach that decision.    Westcott (1968) conducted studies of intuition with college students.   He classified them on the basis of their ability to solve problems using as few clues as possible and labeling those using the fewest number of clues as intuitive thinkers.  These studies examined intuition as inference and subliminal perception, and found that individuals varied in the amount of explicit information they needed before attempting to solve problems.  

Westcott’s findings are generally compatible with Salton’s Organizational Engineering theory.  Like Wescott, Salton theorizes individuals will differ in the amount of explicit information they need to resolve problems and issues.  Unlike Westcott, however Salton sees this as an outcome of the strategy used, rather than as an innate quality of the individual using it.  Again, Salton is indifferent to the judgmental attributes assigned to intuition, such as Wescott’s self-confidence attribution, seeing this as immaterial to his study of intuition.

Salton’s Organizational Engineering theory agrees with Westcott as it relates to intuition and the need for information by the subject in order to make a decision.  However, Salton’s sees intuition as a strategic preference, which deliberately trades speed of response for certainty of outcome.  Put another way, an individual processing information at higher speeds is presented with more opportunities to get it right, given the outcome levels of risk and importance.  Westcott, on the other hand, sees intuition as an innate human quality influenced by the structure of the mind, and perhaps requiring the individual to process information in a more structured manner regardless of the situation. The basic definition of intuition remains the same, but the amount of information needed by an individual prior to making a decision may differ sharply between Westcott and Salton’s methodology.

The systematic data available from the research study database and the relatively thin data and loose rigor of Westcott’s study precludes a definitive resolution of differences between Westcott and Salton’s Organizational Engineering theory.  For this study, it is sufficient to note the behavioral outcomes of both theories are consistent.  Thus, any choice between them would rest on their value in organizational application, as well as in future research and the expansion of knowledge.  In this regard, Salton’s work with its greater scope, and higher scientific rigor with verifiable results and predictive capabilities, would seem to be the more attractive alternative for business applications.

Clark (1973) questions the notion of developing intuition.  He notes intuitive knowledge tends to be general rather than specific, subjective rather than objective.  Thus, it is characteristically experienced as subjectively meaningful.   It is important to note that having intuitive capacity and/or capability does not necessarily mean one uses it or can develop its use. Therefore, the capacity for intuitive problem-solving was found to be significantly related to mathematical aptitude, self-confidence and individual spontaneity (Clark, 1973).

Breakthrough research was conducted in the 1960s and later documented in the book Executive ESP (Dean, Mihalasky, Ostrander, and Schroeder, 1974).   This major study brought together the two elements of intuition and decision-making in management (Agor, 1984b).  This study measured how CEOs of various corporations performed on tests for ESP and how this skill was linked to higher corporate earnings performance for respective organizations.  Dean, Mihalasky, Ostrander, and Schroeder sought to identify intuition as a factor, which would help distinguish the extraordinary manager from the merely competent.  The study spanned more than three years during which over 5000 tests were recorded and measured.   The hypothesis was to validate management level personnel, in determining the importance of future information, relying upon the use of intuition.    This study found the executives with the highest scores also corresponded respectively to companies with the best records of increased profits.  Their findings suggest these results do not prove profit making and precognitive ability are related. However the results do indicate the probability of achieving superior profit making is enhanced by choosing a person who scores well in precognition ability  (Dean, Mihalasky, Ostrander, and Schroeder, 1974).

Again, Salton’s Organizational Engineering theory is consistent with the work of Dean, Mihalasky, Ostrander, and Schroeder.  Unlike Dean, Mihalasky, Ostrander, and Schroeder, it does not view intuition as the outcome of some undefined process such as ESP.  Yet, it also does not deny there may be process available to humans yet to be recognized.  Stripped of the ESP references, Salton suggests that intuitive strategic patterns are favored at higher organizational (i.e. leadership) levels.  The reason is the nature of the issues being confronted at that level tend to be vague, uncertain and ill defined.  The use of structured strategies based on details and explicit relations are a poor fit.

By contrast, Dean, Mihalasky, Ostrander, and Schroeder (1974) assume the CEO is the decision-maker. Their theory does not recognize the existence of other, lower-level decision-makers who also simultaneously influence successful outcomes.  Barnard (1968) on the other hand, sees the CEO as one variable among many within a network of decision-makers.  It is notable that Salton equally supports both theories.  The individual intuitive abilities stressed by Dean, Mihalasky, Ostrander, and Schroeder are characterized by choice of method and mode.  The network aspects stressed by Barnard are comparable to the group-based methodologies suggested within Salton’s Organizational Engineering theory.  The reconciliation of the two theories can best be seen in Organizational Engineering’s Leader AnalysisTM which describes the ease or difficulty with which a leader will experience when attempting to persuade a group of individuals toward his or her preferences.  The analysis measures the leader’s preferences along a continuum and compares them to the composite preferences of the subordinate group.  The greater the discrepancy, the more difficulty the leader will have with others in the organization — whether their preferences are founded on ESP or some rational basis (Salton, 2000).

Dean, Mihalasky, Ostrander, and Schroeder,  (1974) reinforce their argument through anecdotal evidence.  For example, they cite business notables who had acknowledged they used intuition in the process of making decisions such as Leon Hess, Amerada-Hess Oil Co.; Conrad Hilton, Hilton Hotels; William C. Durant and Alfred P. Sloan, General Motors; Charles Kemmons Wilson, founder of Holiday Inns; Dwight Joyce, President, Glidden Co.; and Benjamin Fairless, former Chairman of the Board of U.S.Steel just to name a few.

Anecdotes are also used by Kanter (1977) who suggests Cornelius Vanderbilt, instrumental in building the railroad, acted on impulse and intuition, and could not explain his process for making the decisions he enacted.   Ray and Myers (1986) discuss notable business leaders in their Master’s classes at Stanford University’s Business School who acknowledge using intuition in making decisions.  Some of those identified are: Alexander Poniatoff, Founder and Chairman of the Board, Emeritus, Ampex Corporation; Paul Cook, Raychem; Robert Marcus, Alumax; Steve Jobs, Apple Computer; Charles Schwab, Charles Schwab Discount Brokers; James Treybig, Tandem Computers; Nolan Bushnell, Atari; and Bob Swanson, Genentech. 

Rowan (1986) presents anecdotal evidence, citing a multitude of business leaders who reported they used intuition in significant decision-making situations.   The most prominently identified were H. Ross Perot, founder, Electronic Data Systems; Ray Kroc, former Chairman of McDonald’s; Mary Kay Ash, founder, Mary Kay Cosmetics; Edgar Bronfman, Chairman, Seagram; Debbi Fields, founder of Mrs. Fields’ Cookies; Fred Smith, founder of Federal Express; and John Fetzer, former Owner of the Detroit Tigers, and founder, Fetzer Broadcasting Company. 

This support of anecdotal traits has continued in current research.  Spitzer and Evans (1997) make reference to such well-known leaders in business and academia as Scott Davidson, CEO of ICI Acrylics; Ray Marshall, former Secretary, U. S. Department of Labor; Ralph Larsen, Chairman and CEO, Johnson & Johnson; Richard Teerlink, President and CEO, Harley-Davidson; and C. K. Prahalad, Professor, University of Michigan.

While the list of people identified as using intuition is impressive, it is nonetheless, anecdotal, whether self-reported or observer-noted.  An anecdote is a personal account of some incident or event (Encarta, 1999).  As such, anecdotal evidence is a form of proof, based on hearsay or self-report. Thus, it has minimal value as a foundation upon which to base empirical research.

During the mid-1970s Harold Leavitt (1975a, 1975b), a managerial psychologist, discussed the consequences of over-emphasizing analytical problem-solving in management education.  Leavitt coined the term “Analysis Paralysis”, suggesting the intuitive and emotional elements of information processing deserve the same attention as the logical and analytical.   He (1975b) notes his discomfort with the concept of intuition and his rationale for not wanting to research it further. Leavitt’s articles were published following the first major research study on intuition (ESP) done by Dean, Mihalasky, Ostrander, and Schroeder,  (1974) as previously discussed.

Later, Leavitt as reported by Ray and Myers (1986) while lecturing at Stanford University, discussed a concept he labeled pathfinding, which refers to how people define their personal mission.  He identified three approaches: proactive, reactive, and enactive.  He defines enactive as working on a problem until the individual finds the right path or solution, trusting the problem and solution constitute a personal dialogue, an exercise in communication between one’s inner and outer selves.  This form of intuition places high trust in an undefined process that guides an individual’s choice to select a right choice or solution. While Leavitt omitted the term intuition in his writings, it appears he subscribes to the belief in some existing variable the guides the decision-making process.

Henry Mintzberg (1976) reported the results of his brain dominance research of management in his classical piece published in the Harvard Business Review.   He suggests management researchers have not been successful in finding the perfect technique for managing because critical elements have been overlooked, i.e., the right hemisphere of the brain controls emotional, intuitive, creative, non-linear, visual, spatial, and relational thinking processes (Agor, 1984b; Isaack, 1978; and Mintzberg, 1976).   Mintzberg (1973, 1975) had earlier noted observations of five chief executives whose decisions were made primarily through impressions, feelings, hearsay, gossip, and other sources, rather than relying on empirical data.   The terms most often referenced by Mintzberg are hunch and judgment, which he describes as incorporation of the thought processes, which the intellect does not articulate (1976).  

Isaack (1978) also uses terms like hunch, guess, and feel, to describe intuition as used in decision-making.   Mintzberg (1976) emphasizes that managers need more than analytical skills to do their jobs well; they also needed the intuitive (right brain in Mintzberg’s terms) skills.    However, he does not suggest managers discard the use of analytical thinking. Rather, he argues for a balance between analytical thinking and intuition.  He notes how very little is mentioned in management textbooks on the topic of intuition during the mid-seventies.  When reference was made in management textbooks, three of twenty-four stated intuition should not be considered in the study of management     

Vaughan (1979) sees intuition as a non-rational or non-linear mode of knowing.   However, she states intuition has the capability of being developed and therefore has the aspects of being both a capacity and an experiential inference.   This view has had very little empirical research to test whether people can actually develop intuition.

Vaughan agrees with Maslow regarding the significance of experiencing intuition because it affords personal freedom, which is then expressed in personal choices and decisive action.  In addition, both Vaughan (1979) and Maslow (1970) contend there is a connection between intuition and creativity. Vaughan believes there is a close relationship between using intuition and one’s willingness to risk discovery of one’s deeper self-regarding life experiences.  

This view is entirely consistent with Salton.  Salton’s Organizational Engineering theory argues intuition and creativity are simply points along the same continuum running from weakly defined suspicions to highly articulated, actionable proposals. The use of an unpatterned method and a thought mode increases the probability of finding the unexpected.  If the discovery is of a new ill-defined relationship, which has not been recognized but can be acted upon, it can be termed intuition.  If the same process yields an explicit discovery that can be articulated and defined, it can be termed creative.        

While there are similarities between Salton’s view of intuition and that of these other theorists, there are also differences.  For example, Vaughan defines intuition in terms of experiences being dealt with in four distinct and separate levels of awareness.  These include the physical (i.e., heart rate or sense of uneasiness), emotional (paying attention to one’s feelings or expression in the artistic world), mental (inner awareness/vision or creativity)and spiritual (holistic perception of reality transcending rational) as cited in Brown (1990).  Vaughan states:

Experiences, which are commonly called intuitive, include mystical apprehension of absolute truth, insight into the nature of reality, unitive consciousness, artistic aspiration, scientific discovery and invention, creative problem-solving, perception of patterns of possibilities, extrasensory perception, clairvoyance, telepathy, precognition, retrocognition, feelings of attraction and aversion, picking up ‘vibes’, knowing or perceiving through body rather than through rational mind, hunches and premonitions. (Clark, 1973, p.156)

Vaughan’s book entitled Awakening Intuition (1979), could best be characterized as a prescription for understanding and developing tools in the area of intuition capability.  The three steps involved in awakening an individual’s intuition are: (1) quieting the mind;  (2) focusing attention on the issue at hand or desired and (3) accepting or developing a non-judgmental frame of mind which allows intuitive thoughts to flow freely. Vaughan reported that many of her adult patients feel they were more intuitive as children and had since curtailed the use of intuition due to ridicule and skepticism from others (Agor, 1984b). 

Salton’s methods for developing one’s intuition is radically different from Vaughan’s.  In a series of publications, Salton (2000) outlines methods of developing different strategic styles.  The exact strategy for emulating the ReIational Innovator/Reactive Stimulator depends on the strategic style a person currently prefers to use.  Therefore, there is no universal one size fits all prescription.  However, all of Salton’s prescriptions distill down to use whatever information is  available (rather than searching for it), quickly testing its viability relative to the issue needing attention  (rather than planning), and rapidly discarding things which do not work.  This strategy allows a high volume of tests and, every once in a while, something unexpected will surface.  As this strategy is practiced, ever-greater volumes can be processed, therefore significantly increasing  the likelihood of involving intuition and creativity.

Vaughan’s (1979) research concerning imaging, as it relates to intuition, asserts meditation is an extremely productive method to increase intuitive awareness. Dean, Mihalasky, Ostrander, and Schroeder (1974), and Goldberg (1983) also support this thinking. However, Vaughan cautions that information gathered during an exercise of imaging is not judged on face value, as the event may not present itself until a later time versus closer to the present.

Salton’s views imaging as a good vehicle for discovering unexpected relationships.  Unlike analysis, imaging involves visualizing a situation in all of its complexity as a single episode.  This increases the likelihood something unexpected will be discovered.  Analytical structures preclude this phenomenon due to the focus on using predetermined formulas, methodologies and proven techniques.

Raudsepp (1982) believes the steps used in intuition are the same as those used in analytical methods, merely faster processing.   This view supports the notion that intuition occurs without one knowing how they know or upon what one’s thoughts, experiences, and knowledge are based.  Raudsepp (1982) defines intuition as an experiential, holistic way of knowing or reasoning where the weighing and balancing of evidence are carried on unconsciously.  Although a certain amount of fact finding and data gathering are necessary when using intuition not every decision or problem to be solved uses intuition.   Similarly, he suggests the use of intuition in complex problem-solving results in the identification of other opportunities not necessarily noticed or developed by those who are using greater levels of details and seeking more facts.  In summary, Raudsepp (1981) suggests:

Usually, intuitive thinking rests on familiarity with the domain of knowledge involved and with its structure, which makes it possible for the thinker to leap about, skipping steps, and employing short cuts in a manner that requires a later rechecking of conclusions by more analytic means, whether they are deductive or inductive. (p.36)

While they may disagree on the cause of intuitive behavior, Raudsepp and Salton agree on the practical outcomes of its use.  Quickly apprehending things readily at hand, rapidly applying them to an issue of interest, and discarding those which do not work.

Cosier and Aplin (1982) imply intuition is closely allied with ESP.  Current research challenges this stance, and therefore Cosier and Aplin’s views are not widely accepted or cited in the literature.

Peters and Waterman (1982) assert the use of a rational model in decision-making is contributing to the decline of productivity and quality in America.    Peters and Waterman, as reported by Catford (1987), while researching excellent organizations found that successful decision-making and problem-solving are more inspirational than rational involving attention to several factors simultaneously.  They suggest business schools have trained inexperienced managers to think the correct answer can be obtained through analysis based on numerical data.   Rowan (1987b) agrees  our society and business schools in particular put heavy emphasis on left brain thinking which encourages analysis paralysis.  Unlike the work of Cosier and Aplin (1982), Rowan’s position is based on a logical foundation and should be seriously considered.

Management Oriented Research

Weston Agor has done the most recent and extensive research in the field of intuition in management decision-making.   Agor is retired from the faculty of the University of Texas–El Paso and was founder of The Global Intuition Network, now known as the Intuition Network.   Agor (1983c) suggests “managers in the future will need to make decisions in a more rapid manner and with less complete data”.   Therefore, managers who develop their intuitive skills will be more adept at making decisions.   This timeliness in making those decisions can be the difference between success and failure.  Agor (1984a) concludes most decisions are made either on the basis of incomplete information or because information is not available within the time restrictions. Agor (1986a, 1986c) studied, over a period of two years, 2,000 managers using a portion of the Myers-Briggs Type Indicator which later developed into what is now known as The AIM Survey.   This study indicates top executives rated significantly higher in intuition than middle or low level managers.

Agor (1986) completed a follow-up study of 200 of those executives who scored in the top 10 percent on the intuition scale from others surveyed using a more specific set of questions.    Of these 200 surveyed, seventy responded and all but one of the executives stated they used their intuitive ability to guide their most important decisions.   They further went on to clarify intuition was not their only tool but it was an important management resource.

Agor  (1984a, 1984b) found the ability to use intuition and the frequency of its use varies by management level, type of organization, sex, occupational specialty, and ethnic background.  Top management scores higher than middle management in both use and frequency, and middle managers in turn score higher than lower level managers. His research also shows top managers display greater potential intuitive ability than middle or lower level managers.

These results are consistent with Salton’s Organization Engineering theory. In addition, the progression is geometric making it mathematically impossible for purely analytical methods to be applied in all facets of a senior executive’s area of responsibility.  Therefore, the ability to effectively use  partial information and to generate resolutions without full specification of the process will become increasingly valuable and the strategies of Reactive Stimulator and Relational Innovator work best within these environments.

Agor (1984a, 1984b) concluded from his research that subjects in his study were more likely to use intuition where the following conditions existed: a high level of uncertainty; little precedence exist; variables are not scientifically predictable; facts are limited or do not indicate a path to travel; use of analytical data is not appropriate at the time; multiple realistic alternative solutions exist; and/or time is of the essence.  These are exactly the conditions which favor the combined styles of the Relational Innovator and Reactive Stimulator strategy, in Salton’s Organizational Engineerin.

Agor also reiterates the importance of knowing the different personality types and brain dominance patterns with regards to staff positions with individuals whose strengths are aligned with the desired work results.  He also states where this is not done properly less than optimal, if not dismal outcomes may result.  Hermann (1981) states this same basic principle from a different perspective, suggesting people tend to become employees where they can do work which best fits their preferences.

Both Agor’s and Hermann’s position on these issues are fully compatible with those parts of Salton’s theory, people will tend to seek environments favorable to their elected strategy and will therefore be aligned with the demands of the position.  However, unlike Agor and Hermann, Salton allows for shifts in the preferred strategic profile, permitting alignment to be realized over time.  Both Agor and Hermann suggest the alignment is more static and individuals can only be aligned if their position is changed in character.

Goldberg (1983) describes the use of intuition in a range of human functions, from how the mind works to developing one’s intuitive abilities, to using it in decision-making and problem-solving.  He suggests intuition is often defined in terms of what it is not, rather than what it is.   For example, Goldberg distinguishes the difference between intuition and ESP as precognition (intuition) and an extension of our five senses already present (ESP).   Goldberg like some of the other experts links closer the relationship between rationality and intuition as being complementary rather than separate and distinct.  In fact, he even goes so far as to say intuition is a part of rational thinking (1983).    Agor (1984b) points out a limitation of Goldberg’s book in that it was not based on actual field testing nor did it contain detailed descriptions on specific management situations in which to use intuition.  And uniquely. Sprecher (1983) prefers to think of intuition as merely a subset of logical thinking. 

Salton’s theory incorporates all of the above observations; i.e., intuition is just a position on the method and mode continuums.  Although sometimes distinct other times complementary, all types can be accommodated within Salton’s Organizational Engineering theory. 

Isenberg (1984) studied a dozen executives by conducting interviews, work observations, talking to colleagues/subordinates, reading logs/diaries, and engaging them in various exercises over a two-year period.   The managers ranged from entrepreneurs to division-level managers within Fortune 100 companies.   While Isenberg was not able to clearly identify a linear rational process,  there was a tendency to combine rational with intuitive processes. This integrative approach is also identified in later studies and articles on the subject.   What he (1984) did find is two-thirds of those studied are preoccupied with a very limited number of quite general issues:

In making their day-to-day and minute-to-minute tactical maneuvers, senior executives tend to rely on several general thought processes such as using intuition; managing a network of interrelated problems dealing with ambiguity, inconsistency, novelty, and surprise; and integrating action into the process of thinking. (p. 84)

He suggests there are five circumstances in which intuition is used:

First, they intuitively sense when a problem exists.

Second…to perform well-learned behavior patterns rapidly.

A third function of intuition is to synthesize isolated bits of data and experience into an integrated picture

Fourth…as a check…on the results of more rational analysis. And,

Fifth…to bypass in-depth analysis and move rapidly to come up with a plausible solution. (p. 85)

The most important of these five circumstances he identifies is of the inner knowing sense versus the rational or data analysis. Isenberg (1984) states intuition comes from extensive experience with analysis, problem-solving, implementation, and to the extent the lessons of experience are well founded, then so is intuition.    The importance of intuition occurs at the problem-solving/decision-making time as well as at the time a problem is sensed to be happening, prior to identification.    Isenberg describes the phenomenon as everything finally coming together in either an experience or seeing a big picture, which he termed the “AHA!”.

Herbert Simon (1987) discusses the role of intuition and emotion in management decision-making.   He refers to Barnard’s logical and non-logical processes, and to split-brain research to explain his view of analytic (rational) and judgmental (intuitive) decisions.   He best sums up his research position by saying:

It is fallacy to contrast analytic and intuitive styles of management...the effective manager does not have the luxury of choosing between…approaches to problems.   Behaving like a manager means having command of the whole range of management skills and applying them as they become appropriate. (p. 63)

Again, the thinking of both Isenberg and Simon are reflected in Salton’s theory.  The selection of the method and mode continuums does not address the degree of expertise which those positions can be manifested.  Salton’s (2000) general rule of practice makes perfect especially supports Isenberg’s concepts.

Naisbitt and Aburdene (1985) take a futurist approach to the subject of intuition in management and relate it to western civilization, which they contend is more analytical than intuitive its decision-making and problem-solving processes. These researchers contend chief executives use intuition or more holistic thought processes regularly in circumstances where planning, decision-making, and complex problem-solving are too complex for rational models, or when information is limited.  Again, this thinking is entirely consistent with Salton’s theory.

Eisenhardt (1989), tracking the decision-making processes in twelve microcomputer firms, conducted extensive interviews with members of top management teams, used questionnaires, observed group meetings, and examined various secondary data. The study showed rapid decision-making is linked to such characteristics as being decisive, operations-focused, hands-on in work style, and being instinctive by nature.   This rapid decision-making is then measured against effective performance.   As an example of behavior linked to rapid decision-making, Eisenhardt finds executives gather real time information on firm operations and on the competition’s environment.   This suggests the presence of a deep, intuitive grasp of the business operations.

Salton’s Organizational Engineering research is consistent with Eisenhardt’s finding of rapid decision-making, which, she reports, is effective.  However, Salton’s theory qualifies this by noting it is effective in the particular industry she studied.  Microcomputers were rapidly evolving during the period of her research and there was minimal reliable structure available for extensive lengths of time, a condition favoring unpatterned strategies.   For example, it is unlikely Eisenhardt would recommend her theory be applied to a brain surgery situation in a hospital.   Salton’s Organizational Engineering theory does accommodate Eisenhardt’s theory given when it is applied to real limitations.

Cappon (1993, 1994), a medical doctor and psychotherapist, is convinced based on his practice that everyone has some capacity for intuition, even though not everyone uses it: those who do use it, do not always apply its use equally.   He suggests intuition can be trained and this is based on his use of “IQ2” (instrument designed to measure for actual capacity). This is a predecessor to his Cappon Intuition Profile, used to test for the likelihood of intuitiveness that was developed in 1989.   Cappon believes the reason people either do not use it or do not admit to using it is because intuition is not necessarily processed consciously, and is therefore suspect.

Cappon (1993) began his studies of intuition with the hypothesis it is the secret to success in most endeavors, even in business environment. He tested more than 3,000 clients and found women do not have more intuition than men do.  He attributes this false belief that women use more intuition to Western societies being dominated by males, and scientific thinking, of which both distrust intuition.   Cappon also suggests intuition has been viewed negatively because the process itself is almost unconscious.  These negative views because scientific research bias that further forced it underground. The intuitive process thus becomes masked and its relative importance greatly obscured.

Cappon (1993) extended his research to measure 20 specific skills:

• Perceptual closure on insufficient time;
• Perceptual closure on insufficient definition;
• Perceptual recognition;
• Positive perceptual discrimination;
• Negative perceptual discrimination;
• Synthesis or Gestalt insight;
• Time flow estimation;
• Retrieving memory or quick memory;
• Passive imagination;
• Psycho-osmosis or knowing the unknown;
• Stimulated imagination;
• Active imagination;
• Anticipation or foresight;
• Optimal timing of intervention;
• The hunch or seeing the solution before you have it;
• The choice or best method;
• The choice of best application; 
• The hindsight (uses empathy and identification in order to divine the cause of things); 
• Associative and disassociative matching;  and
• Seeing the meaning of things.  

Cappon’s request to administer his research instrument was not well received among some intuition-sensitive companies which feared the public would lose faith in them if they were thought to be operating on gut feeling.   Interestingly however, companies in the manufacturing industries willingly agreed to use Cappon’s instrument.

Cappon’s research contribution points out how informal judgments on the use or study of intuition can generate some heavy skepticism.  The same is not true of Salton’s Organizational Engineering theory, because its instrument does not require summary judgments based on classification of observed behavior.  Rather, these observations confirm the validity of the instrument’s findings.

Parikh (1994) conducted intuition research on 1312 managers from large non-governmental industrial and service organizations located in nine countries: Austria, France, Japan, the Netherlands, Sweden, the United Kingdom, the United States, Brazil, and India.         Parikh’s findings suggest many managers use intuition; intuition contributes to business success; and intuition contributes to harmonious interpersonal relationships.   Specifically, respondents perceived the following areas as important for the use of intuition: corporate strategy and planning; marketing; public relations; human resource development; and research and development. 

Parikh’s research is entirely in line with Salton’s Organizational Engineering theory.  The applications Parikh cites are inherently unstructured in nature and would favor the unpatterned strategies of the Relational Innovator and Reactive Stimulator.

Spitzer and Evans (1997) discuss a meta-study done by Kepner and Tregoe using content experts to: (1) examine the state of problem-solving and decision-making in business today; (2) conduct a detailed examination of their client base to determine whether their problem-solving and decision-making are effectiveness as that of the best in the world; and (3) interview management experts and researchers, such as Ken Blanchard, Henry Mintzberg, Tom Peters, Peter Senge, Noel Tichy, and Stuart Varney.   Kepner and Tregoe had three hypotheses when they  began their inquiry:

1. Consistently good decision-makers use a consistent process that differs from mediocre or poor decision-makers.
2. Good decision-makers can describe the process they use.
3. The decision-making process can be codified and taught to others.Results found the first and third hypotheses were significantly supported, while the second hypothesis was not supported.   

As a theorist, Salton is concerned with how human decisions are made both by individuals and groups.  Judgmental terms, such as good decision-makers can be seen as inappropriate because the term good depends upon a pre-defined measure. 

Joel Kurtzman, former editor of The New York Times business section and The Harvard Business Review, (Ray and Myers, 1986) suggests:

The rational process is linear.   It’s when you are putting your facts in order and looking at them, weighing them, and making a decision based on the importance you assign each fact.   Intuition is looking at the same facts and trying to see a pattern.   The patterns aren’t always evident because they are not linear.   That’s where intuition is very valuable.   You look at a set of variables, and suddenly it snaps into your mind that there’s a pattern.   The ability to recognize patterns is intuitive.   Rational and intuitive thinking is not mutually exclusive. (p. 177)     

The existence of two different types of information processing, one analytical and rational, the other more intuitive and non-rational, have been verified by scientific studies investigating the two hemispheres of the human brain (Ornstein, 1972).   Over the past twenty years, this research has made a distinction between the hemispheres of the brain.   People are described as either left-brain thinkers, who rely on logic and rationality, or right-brain thinkers, who tend to use intuition and creativity in making decisions--the premise being that each person prefers one style of thinking more than the other, but is not limited to a single style. A position suggests that a balance between the two opposites is the more desirable, either from an individual applications perspective or one using two or more people in a group decision-making process.

Salton’s Organizational Engineering theory does not take a position on the biological determinants of human behavior including brain dominance research.   However, Salton objects to the position a balance between the two is some kind of ideal or optimal.  Salton’s Organizational Engineering theory looks at the desirability of a particular kind of decision-making as being determined by the context being addressed.  For example, if a decision is required during an operation involving extraction of a brain tumor, it can be argued linear thinking based on tested science is the best strategy.  A decision involving the purchase of a forward contract on the commodity exchange may be better served with an intuitive strategy.  The idea that there is some kind of common decision-making process integrating both preferences is summarily rejected by the engineering orientation of Salton’s Organizational Engineering theory.

Other researchers do agree intuition is not only a personality trait, but also agree the right cerebral hemisphere functions for intuitive choice, while the left hemisphere is analytical (Agor, 1984a, 1984b; Lynch, 1980; Hermann, 1981; and Zdenek, 1983).   Ned Hermann ‘s research on creativity in the mid-1970s at General Electric confirmed that different areas of the brain are used for various types of cognitive processing (Talbot, 1989/90).   This research was further verified with Hermann Brain Dominance Instrument research (Hermann, 1989).

Thornton (1971) suggests intuition can be differentiated from other forms of cognitive abilities and, in particular, from reasoning. Intuition is also an active mental process found as front-end principles in mathematics and science.   Thornton also concludes intuition can be used to learn more about oneself, about others, and about the world.  Therefore, Thorton sees intuition as a means of self-awareness, rather than as an approach to explaining organizational functions.

Riggs (1987) studied the use of intuition in management and compares intuitive abilities, management styles, and management types (executive, middle, and lower level managers), the were managers of major corporations in Washington state.   Riggs used an early version of Agor’s Test Your Management Style questionnaire as well as follow-up telephone interviews with those who scored in the top ten percent on the intuitive scale.  Contrary to Agor’s previous research, Riggs’ results indicate, there are no significant differences for intuitive ability, management style, or management type between various levels of management.   However, consistent with Agor’s research, additional information obtained as a result of her telephone interviews reveals (1) managers who scored the highest on the intuitive scale used intuition when making major business decisions, (2) knew they were using intuition, (3) often disguised their intuitive decisions, but (4) considered themselves intuitive decisions-makers.

Riggs offers a weak design protocol, but does serve to reinforce the previously cited view of Cappon’s studies attempting to directly address intuition through questionnaires, which are challenged to overcome a reporting bias.  Such a data collection challenge may suggest the relative importance of intuition is probably understated as a managerial tool.  The other important finding of Riggs concerning the variance of intuition by hierarchical level, is an important aspect of this study’s design.

Blackwell (1987) studied a small sample of a higher education population with a questionnaire using measures from Agor’s Intuitive Management survey and Goldberg’s Are You Intuitive? test, along with questions asking about the frequency of intuitive experiences.   Blackwell concludes managers scored higher than non-managers and women score higher than men do.   Blackwell also indicates brain organization tentatively suggests a linking to intuition. Furthermore; a balanced style of intuition and reasoning may suggest some relationship to a visionary leadership style.

Catford (1987) tested fifty-seven business professionals using problem-solving models on a survey with a demographic assessment instrument and the Myers-Briggs Type Indicator (MBTI).   Catford concludes the MBTI would not be a good indicator for determining what actual problem-solving strategy business professionals will use. Catford’s research finds middle and senior management experience intuition in their decision-making processes.   Catford finds those comparison scores between senior and middle managers do not appear to factor in the participant’s experience with the use of intuition in decision-making situations.  Furthermore, she concludes the comparisons of senior and middle managers’ high and low degrees of intuitive experiences are proportionate to the sample size studied.

Blackwell’s findings reinforce Agor, while challenging Rigg’s position on the variance of intuition by hierarchical level position.  However, Rigg’s position is supported by the findings of Catford who concluded the senior and middle manager results were in proportion to the sample size versus correlated to their hierarchical position. 

Taylor (1988) researched the intuitive decision-making experiences of ten managers using a case analyses and questionnaire.   Taylor’s research supports the view that  middle and senior managers experience intuition in their decision-making processes.   Other factors which influence their decision-making are: the quality of their managerial experiences; relationships within their organizations; their rational tendencies and the rational forces in the environment; their intuitive predisposition; and their individual degree of intuitive development.  Furthermore, Taylor finds intuition occurs around certain kinds of management decisions involving people judgments, decision-making in a situation where no problem-solving precedent has been established, or around incomplete problem scenarios. 

Taylor’s findings are consistent with Salton’s theory; the strategy being used will tend to be aligned with the issue in question.  However, this contradicts Ornstein’s (1972) expectation that some kind of overall optimal is to be sought between intuitive and rational methods.

Brown (1990) studied fifty-two school superintendents using the MBTI, as well as on-site observations of four of the superintendents. Of those responding (17 of 52); five were very clearly intuitive, five were clearly intuitive; five were moderately intuitive, and two measured minimally intuitive. 

Brown (1993) also researched intuition among advertising agency employees.   This study measures intuitive responses to advertisements, both in terms of their private judgment and as a predictor of consumer response.   Brown’s research reveals 43 percent of the subjects would have made more accurate predictions of consumer response had they merely reported their own intuitive judgments only, rather than attempting to rely on their intuitive judgments and the available research data combined.  In fact, another factor which was discussed and brings up another dimension is even being able to tell good from bad [research] data.   Brown’s (1993) findings are in line with Salton’s Organizational Engineering theory expectations.  The weakly defined variables and structure of advertising make it an ideal venue for the exercise of the unpatterned strategies of Relational Innovator and Reactive Stimulator.  This suggests the desirability of an implied balance between intuitive and rational methods is not supported. 

These findings reinforce the position intuition can be expected to vary by hierarchical level, which argues against some kind of ideal balance as proposed by Ornstein.  It also tends to reinforce the findings of Agor, Blackwell, and Salton; while contradicting Riggs and Catford. 

Instrumentation

Different instruments are found for measuring intuition as indicated in Table 1.

Table 1

Instruments Measuring Intuition

The commonality among most of the instruments cited is they are based on psychological theory.  The contribution of the Salton’s instrument is it is based on information processing theory, an added dimension to the research previously reviewed, none of which is considered in any of the reported research.

The training aspects of Intuition in business have appeared in several forms. Agor (1983b) supports the value of management training programs, which included intuition as well as analytical skills for decision-making that have become an integral part of management education in the 1990s.   Universities such as Stanford (Ray and Myers, 1986) and Florida International (Taggart and Taggart-Hausladen, 1993) have incorporated intuition and creativity based courses into their curricula for business students.   In fact, Creativity in Business (Ray and Myers, 1986) was based on the Stanford University course of the same name by Ray and Myers (Agor, 1989c).  MIT, through a training company called Innovation Associates, founded by Peter Senge, has been training managers on the use of intuition in management (Agor, 1989c).   Senge (1990a) also introduced the use of intuition by managers as part of his mental models in his book The Fifth Discipline.    Senge’s personal mastery mental model relates to the work of Agor (1984a), Mintzberg (1976), and Isenberg (1984) with regard to integrating reason and intuition.   Senge (1990a) states:

People with high levels of personal mastery do not set out to integrate reason and intuition. Rather, they achieve it naturally as a by–product of their commitment to use all resources at their disposal.  They cannot afford to choose between reason and intuition, or head and heart, any more than they do would choose to walk on one leg or see with one eye. (p. 168)

Senge (1990a) goes on to state that integrating reason and intuition is not a linear process, cause and effect are not close in time and space…obvious solutions will produce more harm than good…and short-term fixes produce long-term problems.   He believes rationality and intuition are not diametrically opposed, but they can be used in conjunction with each other, such as being able to convert intuitive thought into rationally testable ideas.   

Summary

The literature presented in this chapter focuses on intuition and being used in managerial decision-making processes.   Two approaches to the viability of intuition are discussed: one is based on the concept that intuition is potentially available to everyone and can be developed (Vaughan, 1979), and the other that an individual’s type is either intuitive or non-intuitive (Jung, 1971).

The literature shows many managers report using intuition, in spite of the deeply rooted practice against non-rational methods (Agor, 1984a, 1984b; Dean, Mihalasky, Ostrander, and Schroeder, 1974; Isaack, 1978; Mintzberg, 1976; and Rowan, 1986).    It also suggests the influence of intuition or non-rational thought processes is one which has been neglected as a form of legitimate management understanding.   The rational or logical thinking mode characteristic of the scientific management era has been the dominant accepted style in practice. 

Research which has been done to indicate and illustrate managers’ use of intuition ranges from inferential processes performed with a pre-existing database (Agor, 1986) to acceptance and use of predictive abilities (ESP) (Dean, Mihalasky, Ostrander, and Schroeder, 1974).   Even though there has been documentation which indicates the value of the use of intuition (Agor, 1984b, 1986; Dean, Mihalasky, Ostrander, and Schroeder, 1974; Isaack, 1978; Mintzberg, 1976; and Rowan, 1986) in business, there is still a reluctance to readily acknowledge or report its use due to perceived negative reaction (Agor, 1986a, 1986c, and 1986d).   Some researchers report, and I believe, successful decision-makers are found to have greater ESP abilities (Cosier and Aplin, 1982; Dean, 1974).

This study, through a comparative analysis of the review of the literature to demonstrates Salton’s Organizational Engineering theory can accommodate many divergent positions (e.g., Vaughan, 1979 and Jung, 1971).  Salton’s research also confirms the position that only a certain portion of the population is expected to be endowed with high levels of intuitive skills (e.g., MacKinnon, 1962; Parikh, 1994; Peavy, 1963; and Thornton, 1971).  Salton’s Organizational Engineering theory also supports differences in gender and intuition research which can help to resolve issues on whether there is a difference.   Finally, the role of intuition in the area of organizational development is addressed by Salton to resolve the issue of whether intuitive abilities vary by hierarchical levels (e.g., Barnard, 1968; Dean, Mihalasky, Ostrander, and Schroeder 1974; and Riggs, 1987) The purpose of this research is to resolve these opposing positions reported in the literature.

In addition, the survey instrument adds a dimension not heretofore available because of previous reliance on psychological theory and measures.  Salton’s Organizational Engineering theory relies on information processing and can be seen as adding a dimensionality to the field.   In today’s ever-changing business environment, application of organizational theorists’ views on rational versus non-rational aspects of decision-making becomes even more relevant.   Current organizations are characterized by ambiguity, diversity, emerging technologies, and cultural mixes, and are ideal environments for testing the use of intuition.  Intuition is important in understanding complex organizations which allow individuals to deal with the inherent uncertainty and complexity (Senge, 1990a).   Future decision-making using intuition will have a greater role for individuals in leadership positions (Agor, 1984a).   Furthermore, inclusion of intuition in leadership models and development activities is repeatedly recommended by several individuals mentioned in this chapter (Agor, 1984a, 1984b; Dean et al, 1984; Senge, 1990a).

Chapter 3, describes the research design, data collection instrument, and data analysis to be used in this study.  The population and related sample for measuring the use of intuition in decision-making are described.

CHAPTER 3

Methodology

The focus of this study is the use of unsystematic strategies by human beings in organized environments. Dr. Salton’s Organizational Engineering concepts of unpatterned method and action mode, which produce observable behaviors consistent with the concept of intuition are also used by other researchers in intuition research. The research question driving this study is: 

Do various combinations of method and mode produce results that are consistent with the findings other researchers have attributed to intuition?

This chapter describes the methodology used to examine the research question by constructing hypotheses that can be refuted by data collected in the environments within which intuitive behavior is proposed to operate.

Variables

In Chapter 1, the general theory of Organizational Engineering is outlined.  The relevance of Organizational Engineering to intuition research is focused as the use of unpatterned method and the level of action mode.

In Chapter 2, the theorists and researchers who have identified and codified variables associated with intuition are described.  This review identified multiple findings which can also be tested using Salton’s Organizational Engineering theory.  The findings of these earlier theorists can be recast in terms of the large-scale method and mode factors which underlie Salton’s theory.  Positive findings on these hypotheses will answer the research question and support the use of Salton’s Organizational Engineering theory as a foundation for future research and theoretical development.

Relational Innovator Dimension

Hypothesis H1o

Relational Innovator style is not positively correlated with hierarchical position.

Hypothesis H1a

Relational Innovator style is positively correlated with hierarchical position.

The Relational Innovator style is based on the thought mode and will not necessarily display external behavior typically associated with intuition.  However, when the unpatterned method is used, this style is given access to the insights, which may arise from the discovery of unexpected relationships. Researchers (Agor, 1986a, 1986b, 1986c, 1986d; Brown, 1990; and Cappon, 1994) find a relationship of intuition to hierarchical position, thus it is hypothesized a positive correlation shall be found between the strength of the Relational Innovator component and organizational level.

The independent variable in Hypothesis 1 is scores on the Relational Innovator scale of the I-OptTM instrument.  The dependent variable is the hierarchical ranking of the respondent.  The data are drawn from the hierarchical database of the Organizational Engineering Institute.

Kendall’s tau-b test is used to test data about hierarchical position, since it uses an ordinal scale not testable using parametric statistics, which requires normalcy conditions apply to the data. Kendall’s tau is a rank-based, non-parametric method, and hence, does not require the use of the normal curve.

Reactive Stimulator Dimension

Hypothesis H2o

The Reactive Stimulator style is not correlated to hierarchical position.

Hypothesis H2a

The Reactive Stimulator style positively correlates to hierarchical position.

The independent variable in Hypothesis 2 is the Reactive Stimulator scale of the I-OptTM instrument.  The dependent variable is the hierarchical ranking of the respondent.  The data are drawn from the hierarchical database of the Organizational Engineering Institute.

This hypothesis states the unpatterned method is combined with the action mode.  This contrasts with the thought mode of the Relational Innovator in Hypothesis H10 and H1a.  A positive finding on this hypothesis confirms the importance of the unpatterned method and its associated intuitive behaviors as a component of executive decision-making.  In addition, if positive results are obtained for both Hypothesis 1 and Hypothesis 2, then documented results support the correlation-based argument that the unpatterned method, rather than the mode, is driving the phenomenon.

The same statistical treatment employed for Hypothesis 1 is used to test Hypothesis 2.  The finding of a significant difference between organizational levels supports the position the unpatterned method is a component of effective decision-making at higher organizational levels.

Organizational Level

Hypothesis H3o

The Conservator pattern is not negatively correlated with hierarchical position.

Hypothesis H3a

The Conservator pattern is negatively correlated with higher hierarchical positions.

If intuitive behaviors are favored at higher organizational levels because the issues confronted are more general and vague, then it should also be true that the lower organizational levels will confront issues of more specificity.  In these circumstances, structured methods will be supported as applied to action-based processes at lower organizational levels.

The independent variable for Hypothesis 3 is the Conservator pattern measured by the I-OptTM instrument and illustrated in Figure 4.  This pattern employs a structured method and action mode. The dependent variable is the hierarchical ranking of the respondent.  The data are drawn from the hierarchical database of the Organizational Engineering Institute.

This hypothesis examines whether there is a systematic difference within leadership ranks.  In other words, first-level management is expected to have greater levels of the Conservator pattern than higher hierarchical levels.  This association will be explored using Kendall’s tau.

The association is also expected to be visible between managers and non-managers along all of the dimensions of the Conservator pattern as measured by the I-OptTM instrument.   Comparing one group tests this, leaders to another group, non-leaders. Therefore, this test does not involve the rank ordering of position mandated for the use of Kendall’s tau.   Here, the non-parametric Mann-Whitney test is used to test whether the overall strategic profiles of managers and non-managers differ significantly.

A positive finding both within leadership ranks and between leadership and non-leadership ranks on the Conservator pattern will test whether or not structured methods are conducive to the generation of insight and whether this varied systematically by hierarchical level. In short, the information processing requirements of hierarchical level are likely to permit or preclude the exhibition of insightful behavior.

Relational Innovator/Reactive Stimulator

Hypothesis H4o

Research & Development professionals will not have higher Changer pattern scores than will Information Technology professionals.

Hypothesis H4a

Research & Development professionals will have higher Changer pattern scores than will Information Technology professionals.

The basis of these hypotheses is information technology demands rigorous adherence to the structures mandated by the computer.  Research and development on the other hand benefits from spontaneously connecting unrelated variables. Therefore, research and development is systematically more intuitive.

The independent variable for Hypothesis 4 is the results of the Changer pattern, illustrated in Figure 4, which is a combination of the Relational Innovator and Reactive Stimulator, as measured by the I-OptTM instrument for people occupying positions in Research and Development groups.  The dependent variable is the patterned strategies (Logical Processor and Hypothetical Analyzer), as measured by the I-OptTM instrument for people occupying positions in other than Research and Development groups.  The data are drawn from the general database of the Organizational Engineering Institute.

The literature review suggested there is an observable difference in intuition based on the functions being performed.  By its nature, the Research and Development function favors intuition, because developing new products, processes, and methods involves abandoning, at least to a degree, established structures.  If intuitive behavior is being captured by Organizational Engineering’s unpatterned method, it is expected the styles using this unpatterned method are more in evidence in the Research and Development function than in the general population.

A positive finding on this hypothesis supports the thesis that the information-processing model, which underlies Organizational Engineering, is an adequate or at least viable explanation of intuitive behaviors.

Hypothetical Analyzer/Logical Processor

Hypothesis H5o

Customer Service professionals will not have higher Conservator pattern scores than will the general employee population of organizations.

Hypothesis H5a

Customer Service professionals will have higher Conservator pattern scores than will the general employee population of organizations.

Hypothesis 5 tests whether the Customer Service function is more prone to use structured methods than are members of the general population.  The Customer Service function is typically confined to following strict guidelines in satisfying customer claims and demands.  This hypothesis tests whether people who systematically rely less on unpatterned methods are attracted more to Customer Service functions than are those in the general employee population.

The independent variable for Hypothesis 5 is the structured methods of the Conservator pattern, Hypothetical Analyzer and Logical Processor, (Figure 4) as measured by the I-OptTM instrument for people occupying positions in Customer Service groups.  The dependent variables are the scores on structured styles for people occupying positions in occupational areas other than Customer Service.  The data are drawn from the general database of the Organizational Engineering Institute.

Hypotheses H5o/H5a use the non-parametric Mann-Whitney test to establish whether there is a statistically significant difference between Customer Service groups and the general population.

A positive finding for Hypothesis H5a supports the proposition that information-processing styles are a determinant of success within a function.  If Hypothesis H4a on Research and Development is also positive, the issue will be triangulated on both sides of the spectrum and, therefore, the inference will be greatly strengthened.

I-OPT^TM Instrument

The data collection instrument is the I-OptTM Survey and is presented in Appendix A. The I-Opt SurveyTM, also marketed under the name DecideXTM, are trademarks of Professional Communications Incorporated. The instrument has been in use since 1991.

Soltysik (2000) tested the validity of the instrumentation, as it is applied to Organizational Engineering along all major dimensions of formal validity theory.  The instrument has met all tests of significance in face validity, construct validity, content validity, convergent validity, discriminant validity, concurrent validity, predictive validity, conclusion validity, and reliability.  The instrument is found to meet or exceed the generally accepted criteria for significance of p<.05.  See Appendix B for Summary of Reliability and Validity Findings (Soltysik, 2000).

Of particular interest in this research is content validity.  Content validity concerns the degree to which “judgments made on the basis of the instrument are truly appropriate to the underlying theory or concept” (Soltysik, 2000).  In other words, high content validity provides assurance the proposed relationship between unpatterned method and action mode and intuitive behavioral displays are captured by this instrumentation.

Using a Nomological Net methodology (Trochim, 1999) Soltysik finds between 84 percent and 92 percent of the statements used in the I-OptTM Survey can be directly traced back to the underlying theoretical concepts of method and mode.  This finding, along with Soltysik’s finding that respondent misunderstanding is improbable, supports this study’s research design and the tests conducted in this study correctly test the relationship between the method and mode as well as the dimensions of intuitive behavior being tested.

Database

This researcher has obtained unrestricted access to primary and archival, unfiltered data, using the I-OptTM Survey instrument from the Organizational Engineering Institute of Ann Arbor, Michigan.  These data exist in a formatted database maintained by the Organizational Engineering Institute in Ann Arbor, Michigan for research purposes by qualified scholars and practitioners in the field.  This researcher is permitted (Appendix C) to use this database and is certified as a Level III Certified Organizational Engineer by the Organizational Engineering Institute.

The data used in this research are primary, unfiltered, unprocessed, and have not been screened or summarized for any other purpose.  The data consists of raw scores on each of the four dimensions captured by Salton’s Organizational Engineering effort, through instrument administration sessions by trained personnel using human subjects completing the I-OptTM Survey.   In addition, the data on group leaders are referenced to specific organizational positions and, as groups, by organization function.  While not initially collected for the purposes of this study, the data provide an unbiased look at an extensive body of human subjects with whom to test the hypotheses derived from the research question and literature review.

The Organizational Engineering Institute provided the source data for this dissertation as well as the analysis of groups and teams in actual field situations.  The typical procedure involved:

1. An internal Organizational Development/Human Resource professional or an external consultant acted as an agent for the group and contacted the Institute to request an analysis of an individual or a group.
2. The agent distributed and collected the Survey instruments and forwarded them to the Institute either electronically or by physical courier (i.e., mail, FedEx, UPS, etc.).
3. If the agent had access to the software-scoring program, the agent scored the instruments locally and forwarded the results to the Institute.
4. The information provided would normally include the requesting organization’s name so it could be incorporated into the final report.
5. The Institute then conducted the analysis and returned the results to the agent for distribution to the individual participants.
6. In the development of TeamAnalysis™ and LeaderAnalysis™ software, the Institute called back the agent representative to determine the accuracy and effectiveness of the group reports.  In this conversation PCI would often (but not always) discover the name of the client company and mission of the group analyzed.
7. The Institute then entered the information from the Survey and the group reports into a Microsoft Excel database for future reference.

The resultant information was divided into two distinct databases: The TeamAnalysis™ database includes the calculated survey results for all individuals included in the various TeamAnalysisTM surveys the Institute has conducted.  The individual survey results are identified by the group within which they participated.  The LeaderAnalysis™ database includes the calculated survey results for all individuals included in the various TeamAnalysisTM surveys PCI conducted. Because a TeamAnalysisTM is a precondition for a LeaderAnalysisTM, all of the individuals identified in the LeaderAnalysisTM database are also included in the TeamAnalysisTM database. Team AnalysisTM and Leader AnalysisTM are both trademarks of Professional Communication Incorporated.

TeamAnalysisTM does not require the identification of the leader, but rather treats all participants as equally influential. The LeaderAnalysisTM requires the identification of a group leader, and the LeaderAnalysisTM  database includes the hierarchical positioning of the participants.  PCI  attempts to collect the title of the group leader for inclusion in the database.  This effort was successful in most, but not all cases.  The title collected for each leader is the usual title used in the firm or organization.

The unedited information in the database has been systematically collected from November 1994 to January 2001 and contains information on 9034 individuals who used the I-OptTM instrument and whose scores are contained in the TeamAnalysisTM database.  This researcher obtained access to the database on January 30, 2001.  The data are collected in conjunction with performing various group-based analyses and are organized by the individual groups for which studies and analyses were performed.  The groups represent a broad range of activities illustrated by the sampling of group names in Table 2 (Soltysik, 2000)

Table 2

Examples of Work Groups in the Database

In addition to the group-based data, the Organizational Engineering Institute began collecting hierarchically based data in 1996.  The LeaderAnalysisTM database consists of the raw I-OptTM Survey scores for groups organized with defined hierarchical structures. The LeaderAnalysisTM (hierarchical) database is drawn from the same population as the TeamAnalysisTM database, and therefore has the same industries as represented above within it. This database also contains information on groups with the leader and subordinates identified, where applicable.  In many cases, the rank of the leader is identified because of requested analysis.  A sampling of the titles in the database include President, Managing Partner, Senior Vice President, Chief Operating Officer, Vice President, Owner, General Manager, Director, Manager, and Supervisor.    Appendix D contains the classifications along with coding, definitions, and number of individuals included in the hierarchical levels used by this study.

Leadership of a group does not necessarily imply high position within a firm’s hierarchy.  For example, some groups are led by secretaries and administrative assistants and others by the CEO of the firms.  There are also situations in which people on a team have higher rank within the firm than does the leader.  For example, one New Product Committee is headed by the VP of R&D and the President of the firm is a committee member.  However, in most cases, the leader of a group has higher or at least equal rank within the firm as the participants.

The primary data, made available to this researcher, are collected across a wide variety of industries primarily located in the United States.  A sampling of the industries included is given in Table 3 (Soltysik, 2000).

Table 3

Types of Industries/Areas Included in Database

Technically, the data in the database are considered a purposive rather than a truly random sample.  However, the size of the sample, the wide range of functions represented, and the variety of industries involved indicate the findings of this study are reasonably considered representative of the use of intuition, as defined herein within organized environments in the United States (Soltysik, 2000). In summary, the databases used in this analysis are unique to scholarly research in that they are:

• Large in absolute size

• Sourced from a wide variety of different organizations

• Drawn from groups which are actually functioning in the “real world”

• Collected independently by a wide variety of agents

• Catalogued and collected from an independent source

• Freed of much unintentional bias due to independent researcher and data source.

Subjects

The subject companies in this study include firms of all sizes.  Participants include the most senior levels of Fortune 100 firms as well as those from entrepreneurial startups.  The names of the firms were disclosed to this researcher; however, strict confidentiality provisions in the data access agreement require the protection of privacy to the contributing participant organizations.  Similarly, the names of the individuals participating were made available to this researcher, but are covered under the same confidentiality agreement as their organizations.  The individuals represent a sampling of various nationalities and ethnic groups, as well as both genders, which information is coded to protect all participants.

On the basis of a personal examination of the data, this researcher, along with Organizational Engineering Institute staff, is able to assert the data are of high integrity.  The unedited, primary nature of the data provides assurance the data are not biased by unstated assumptions or unintended obfuscation.

Population

As indicated in the database section of this chapter, the population being tested is reasonably inferred to be a representative sample of the people participating in organized environments within the United State of America.

A majority of the sample is drawn from profit-making firms.  However, the sample also includes representatives of non-profit associations, institutions such as universities, and governmental entities at local, state and federal levels.  Therefore, the findings of this study may be reasonably considered representative of the use of intuition as used by those in a wide variety of venues.

It is also worth noting the groups represented in this research are real entities functioning in the real world, and directed at the satisfaction of real needs as perceived by the organizations for which they are employed.  They are not simulated entities and, therefore, the findings can be considered representative of the actual functioning of intuition as it occurs in the day-to-day operation of the organizational entities which are representative of the population of the United States.

Instrument Design

The study includes quantitative information gathered by the I-OptTM Survey instrument.  An identical instrument is also available under the tradename DecideXTM and is distributed by HRD Press of Amherst, MA.  A copy of the instrument is included in Appendix A. I-OptTM and DecideXTM are both trademarks of Professional Communications Incorporated.

The instrument uses a proprietary algorithm to produce measurements of the dimensions identified in Chapter 1.  The structure of the Survey questionnaire is transparent.  There are 24 sets of responses, organized as forced choice selections.  Each set of responses contains four options from which the respondent must select a single response otherwise known as a forced choice.

Each of the four options represents a different position on the underlying method and mode scale.  By making this choice, the respondent is expressing his or her preferred position on these underlying scales.  The methodology is fully described by Salton (1996, 2000).

The I-Opt™ instrument, which underlies the database used in this study is of a forced choice nature.  Many psychometricians have argued ipsative questionnaires cannot be used for interpersonal comparison.  This, of course, does not mean they are right, it only means  they hold a different opinion.  A basis for the ipsative argument is a forced choice does not tell how much a person favors one response over another; just that one is favored.  For example, people might be offered a choice between ice cream and candy.  One person may choose candy, but really favors it only a little more than ice cream.  Another person might choose ice cream and favors it massively over candy. 

Consolidating many such responses, the psychometricians argue, can (but not necessarily will) lead to distorted results.

Recent research (Saville and Willson, 1991) has called into question the practical value of the psychometricians’ arguments.  There now seems to be good evidence people do show behavioral consistency across situations.  These consistencies are not just illusory by-products of the language system.  There are very good reasons for using ipsative scaling. Saville and Willson assert ipsative scaling is used for two main reasons: better control of response sets and to reflect the position life, is about choices.

Using theoretical arguments based on the laws of large numbers, as well as empirical tests and simulations based on various forms of the Master Personal Profile test, Karpatschof and Elkjaer (2000) have shown:

The present analysis does not just state that there is correspondence but that the choices made in the magnitude and ipsative version of the test are as close to one another as can be expected according to the psychometric model.

And they continue:

We have thus demonstrated two things in our study:

1. Choice behavior in normative and ipsative tasks is the same (defined by identical preference).
2. Assessments made in the normative and ipsative versions are the same. (p.36).

The Karpatschof and Elkjaer study lends some confidence the results of this research will not be jeopardized by ipsative considerations.  Another, perhaps more compelling reason, lies in the validity study of the I-OptTM instrumentation by Soltysik (2000).  This study tested the instrumentation against all eight recognized tests of validity including predictive validity (Soltysik, 2000).  If ipsative considerations were a contaminant it is unlikely the strengths reported in all of the remaining validity tests could have been achieved at the high values reported.  Furthermore, Soltysik’s validity study addressed group effects with similar positive results. Difficulties arising from ipsative consolidation effects, if they existed, would have been revealed there, but in fact, were not.

The conduct of an ipsative analysis relies on the availability of the individual responses to each of the questions in the instrument used; in this case, I-OptTM.  The Institute of Organizational Engineering has files of the individual questionnaires in paper form.  However, access to these data do not fall within the scope of the agreements between the author of this dissertation and the Institute.  Rather, access is only provided to scores generated by these instruments.  Therefore, an explicit test of the exact ipsative characteristics of the I-OptTM instrumentation will not be conducted as part of this research.  However, the above citations provide confidence the results of this research can be relied upon and the ipsative threat is not present.

In summary, the instrument is reasonably straightforward and has been widely tested in actual operating situations.  It has been consistently applied over long periods of time and can be considered a stable, well-recognized instrument.

Validity and Reliability of the Instrument

As noted in the database section of this chapter, the I-OptTM instrument has been validated along all recognized dimensions of validity.  An extensive study using the Organizational Engineering Institute database was conducted in 1999 and published by Soltysik (2000).  Soltysik’s study considers validation of both the I-OptTM instrument and the methodology used to consolidate individuals to obtain representation of entire groups.  For purposes of this work, only the validation of the instrument itself at the individual level is of concern.  Soltysik covered all academically recognized forms of validation in his study.  Because the scope of the effort is extensive, Soltysik drew on various data elements.  For tests of validity involving direct comparisons of scorings along various dimensions, Soltysik draws on the unedited database of the Organizational Engineering Institute. For all tests of this character, the results meet or exceed the academically accepted standards of p<. 05 significance or better.

This study, using established, well-recognized statistical procedures examines each of the hypothesis statements.  However, in his validation research, Soltysik (2000) finds certain data elements do not meet the normality assumptions required by parametric tests, such as the t-test and analysis of variance (ANOVA).   Where this occurs, non-parametric statistics are employed to test the hypothesis.

Certain tests, such as face validity, do not lend themselves to inferences which could be drawn from the numerical database.  For these, Soltysik relies upon an expert panel of 50 people who had experience using the instrument.  This very large panel had members with high educational qualifications, many of whom had operational responsibilities in the area of organizational development.  A summary of the qualifications of panel members is presented in Tables 4 through 6 (Soltysik, 2000).

Table 4

Organizational Distribution of Experts

Table 5

Occupational Positions of Experts

Table 6

Educational Achievements of Expert

In cases involving the individual instrument (the matter of interest in this research), the members of the expert panel validated the element being tested with 99% agreement among themselves (Soltysik, 2000).

Soltysik (2000) also tested the reliability of the I-OptTM instrument by applying a variation of the parallel form methodology to data from the years 1994 through 1999.  The test offered 15 independent opportunities to reject the null hypothesis and thereby call into question the validity of the instrument.  The instrument passed all 15 tests as well as the overall test.  Soltysik (2000) states this provides strong evidence of the reliability of the survey instrument.

Data Analysis Environment

The data currently exist in electronically retrievable form.  This researcher will input these data to a Hewlett Packard Kayak workstation computer for processing.   Statistical procedures will be processed using SPSS – version 8.0 for Windows.

Summary

Chapter 3 describes the methodology used in this study.  It outlines the survey process, the database, the subjects, the instrument, the hypotheses tested, and the analysis procedures.   Reliability and validity studies concerning the selected instrument are also presented both in this chapter and in Chapter 2.   Chapter 4 discusses the results of this study and examines procedure.

CHAPTER 4

Analysis and Presentation of Findings

The research question is tested by five interrelated hypotheses. Three hypotheses are designed to examine both the Reactive Stimulator and Relational Innovator style components of the proposed relationship to hierarchy, separately and then together.  In addition, two separate hypotheses are designed as crosschecks of the proposed underlying relationship.  These two hypotheses test functional areas--Research & Development, Information Technology and Customer Service--for the relative level of intuition required to discharge the functional responsibilities effectively.  The specific hypotheses and the results are:

Hypothesis One

This study proposes the strategic style of Relational Innovator (unpatterned method, thought mode) is associated with hierarchical position, otherwise known as organizational rank.  Specifically, the hypothesis is stated as:

H1o:        Relational Innovator style is not positively correlated with hierarchical position.

H1a:        Relational Innovator style is positively correlated with hierarchical position.

Kendall’s tau-b is applied to an extract LeaderAnalysisTM database consisting of leaders identified by their organizational position.  Tau-b (rather than “a”) is used as the relevant statistic because it accommodates tied scores which may be present in the data.  The 1-tail option is chosen because the hypothesis proposes a specific direction for the relationship. The results of the application of the test statistic are presented in Table 7.  The null hypothesis is rejected at a significance level of p <. 001, clearly superior to the p < .05 level typically accepted as a standard in the field.  The “.000” level is an artifact of the SPSS system, only reporting to three decimal places.

Table 7

Statistical Results of Hypothesis 1

Relation of Hierarchical and Relational Innovator Level

Table 7 reports a negative correlation, rather than the positive one proposed in the hypothesis.  This is a result of the method used to code the organizational rank.  A “0” is assigned to the CEO and Presidents, “1” to Vice-Presidents, “2” to managers and a “3” to the Supervisors.  Therefore the direction of correlation is reversed in the report.  In other words, the correlation coefficient is saying the lower the code (i.e., the higher the rank), the higher the Relational Innovator score.  This is as hypothesized.  Examining the graphics, produced by the statistical analysis presented in Figures 6A and 6B, illustrates the phenomenon. The “stair step” nature of the graphics lends visual evidence to the correspondence of the Relational Innovator strategic style to hierarchical position.

In summary, Hypothesis H1o is rejected, and the alternative H1a is accepted.  The evidence strongly suggests a positive and significant correlation between organizational rank and the presence of a Relational Innovator strategic style.

Figure 6A

Hypothesis 1: Median Scores by Hierarchical Rank

Figure 6B

Hypothesis 1: Mean Scores by Hierarchical Rank

Hypothesis Two

This hypothesis proposes the strategic style of Reactive Stimulator (unpatterned method, action mode) is associated with hierarchical position, otherwise known as organizational rank.  Specifically, the hypothesis is stated as:

Hypothesis H2o:   The Reactive Stimulator style is not correlated to hierarchical position.

Hypothesis H2a:   The Reactive Stimulator style positively correlates to hierarchical position.

Kendall’s tau-b is again applied to the LeaderAnalysisTM database, which has leaders identified by their organizational position. The results of the application of the test statistic are presented in Table 8.  The null hypothesis is not rejected, because the significance level of p = .305 exceeds the traditional standard of p < .05.

Table 8

Statistical Results of Hypothesis 2

Relation of Hierarchical and Reactive Stimulator Levels

This finding is unexpected and is clearly demonstrated by the graphics generated by SPSS as presented in Figures 7A and 7B.  Figures 7A and 7B indicate the possibility of the expected association, but not clearly enough to validate a significant statistical judgment.

This analysis explores the relationship between Reactive Stimulator and organizational rank through a supplemental evaluation.  Within leadership positions, Reactive Stimulator scores are not significantly correlated with rank.  However, participation in leadership is itself a rank relative to the remainder of the organizational population.  In other words, being designated a leader is of a higher rank than not carrying such a designation.

To test this form of organizational ranking, the various levels of leadership are consolidated, and this aggregate is compared to the overall population in the TeamAnalysisTM database.  The null hypothesis in this comparison is the exact equivalent of H2o, except the nature of “hierarchical position” is redefined as all hierarchical ranks combined versus the remainder of the population in the database.

Figure 7A

Hypothesis 2: Median Scores by Hierarchical Rank

Figure 7B

Hypothesis 2: Mean Scores by Hierarchical Rank

The non-parametric Mann-Whitney test is applied to the two populations. “The Mann-Whitney test is the most popular of the two-independent sample tests. It is equivalent to the Wilcoxon rank sum test and the Kruskal Wallis test for two groups.  Mann-Whitney tests that two sampled populations are equivalent in location.” (SPSS, Help Index).  Table 9 displays the results of this analysis.

The 2-tail test is automatically provided by SPSS as a part of the Mann-Whitney test. The results indicate the null hypothesis is rejected at a significance level of p < .001,clearly superior to the p < .05 level typically accepted as a standard in the field.  Because the hypothesis indicates direction, the 1-tail test would be more appropriate; however, the 1-tailed significance level for a test is always less than or equal to the 2-tailed level.  In other words, the 2-tailed test is at best equal to and most likely more stringent than the 1-tail. 

Table 9

Mann-Whitney Test Results of Hypothesis 2a

Leaders versus the Population in Reactive Stimulator Score

Kirk (1982) states “an experimenter is less likely to reject a false null hypothesis with a two-tailed test than with a one-tailed test”.   The direction and magnitude of the association between rank and leader/non-leader organizational status can be inferred from an examination of the descriptive statistics, as presented in Tables 10A and 10B.   The Reactive Stimulator scores of people in leadership positions far exceed those of people in non-leadership roles in both median and mean.

Table 10A

Hypothesis 2: Leader Median and Mean Reactive Stimulator Results

Table 10B

Hypothesis 2: Population Median and Mean Reactive Stimulator Results

These results suggest there is a threshold condition prevailing.  In other words, leaders demonstrate more Reactive Stimulator style than the non-leader population.  However, once the threshold is reached, there is not a need to forever increase levels of Reactive Stimulator, as one rises in the leadership hierarchy.  This condition is probably due to the fact that, in order to be selected for leadership, an individual must somehow stand out within the general employee population.  The Reactive Stimulator strategy is ideal for this purpose, because fast responses are characteristically displayed by this style in confronting unusual situations (Salton, 2000; Salton and Fields, 1999). 

This style calls attention to an individual and increases the probability they will demonstrate leader behaviors, and therefore of their being considered and/or selected for possible leadership roles/positions.

In summary, hypothesis H2o is rejected, and the alternative H2a is accepted with the proviso that organizational rank is defined only as leadership versus non-leadership position.  The evidence suggests there is a positive and significant correlation between organizational rank and the presence of a Reactive Stimulator strategic style.

Hypothesis Three

This hypothesis proposes the Conservator strategic pattern is negatively associated with organizational rank.  Specifically, the hypothesis is stated as:

Hypothesis H3o:  The Conservator pattern is not negatively correlated with hierarchical position.

Hypothesis H3a:  The Conservator pattern is negatively correlated with higher hierarchical position.

Kendall’s tau-b is applied to an extract of the LeaderAnalysisTM database, which displays leaders identified by their organizational position.  The results of the application using this test statistic are presented in Table 11.  The null hypothesis is rejected at a significance level of p < .001, again clearly superior to the p < .05 level typically accepted as a standard in the field.

Table 11

Non-Parametric Statistical Results of Hypothesis 3

Relation of Hierarchical Position to Conservator Pattern Levels

Table 11 reports a positive correlation, rather than the negative one proposed in H3o. This is an artifact of the method used to code the organizational rank. A “0” is assigned to the CEO and Presidents, “1” to Vice-Presidents, “2” to managers and “3” to Supervisors. Therefore the direction of correlation is reversed in the report.  In other words, the correlation coefficient is saying the higher the code (i.e., the lower the rank), the higher the Conservator pattern score.  This is as hypothesized.  Examining the graphics produced by the SPSS system, as displayed in Figure 8A and 8B, one readily recognizes this phenomenon. The “stair step” nature of the graphics clearly demonstrates the correlation of the Conservator pattern to lower organizational position.

Figure 8A

Hypothesis 3: Median Scores by Hierarchical Rank

Figure 8B

Hypothesis 3: Mean Scores by Hierarchical Rank

Hypothesis 3 also suggests the Conservator pattern scores of leaders should be significantly lower than the Conservator pattern scores of non-leaders. To test this form of organizational ranking, the various levels of leadership are consolidated and compared to the overall population in the TeamAnalysisTM database using the Mann-Whitney test, the results are presented in Table 12.

Table 12

Mann-Whitney Statistical Results of Hypothesis 3

Leaders versus Population in Conservator Pattern Levels

The Mann-Whitney test requires identified dispersions of the two populations being compared.  In the validity study associated with the I-OptTM instrumentation (Soltysik, 2000), the Ansari-Bradley test is used to confirm this condition.  SPSS, however, does not contain the Ansari-Bradley test and, therefore, this condition could not be explicitly tested.   However the Median test, while weaker than the Mann-Whitney test, does not require an equal dispersion of the two groups.  Therefore, the Median test was applied to the data to indirectly eliminate this consideration.  The results are presented in Table 13.

Table 13

Median Test Statistical Results of Hypothesis 3

Leaders versus Population in Conservator Pattern Levels

Again, the results of the application of the test statistic suggest the null hypothesis is rejected at a significance level of p < .001.  Given this confirmation, it is reasonable to assume the condition of equal dispersion within population groups does not threaten the findings.

The direction and magnitude of the association between leadership and non-leadership ranks is inferred from an examination of the descriptive statistics presented in Tables 14A and 14B. The scores of people in a non-leadership position far exceed those of people in leadership roles in median values.

Table 14A

Hypothesis 3: Population Conservator Pattern

Descriptive Statistics

Table 14B

Hypothesis 3: Leader Conservator Pattern

Descriptive Statistics

This correlation is perhaps more vividly demonstrated in the graphics provided within the SPSS program, presented in Figures 9A and 9B.

Figure 9A

Hypothesis 3: Median Scores by Population and Leader

Figure 9B

Hypothesis 3: Percent of Cases above Median by Population and Leader

In summary, Hypothesis H3o is rejected, while H3a is accepted.  The evidence suggests Conservator patterns are negatively correlated with hierarchical position within leadership ranks. Also, the evidence indicates there is a negative correlation between leaders and non-leaders along the Conservator pattern.  All of these results are obtained at very high levels of statistical significance, namely p < .001.

Hypothesis Four

This hypothesis proposes the Changer strategic pattern is positively associated with organizational roles, which demand insightful processes.  Specifically, the hypothesis is stated as:

Hypothesis H4o:  Research & Development professionals will not have higher Changer pattern scores than will Information Technology professionals.

Hypothesis H4a:  Research & Development professionals will have higher Changer pattern scores than will Information Technology professionals.

To test this hypothesis, organizational units clearly identifiable as Research and Development (R & D) related are extracted from the TeamAnalysisTM database.  A similar process is performed for groups with an Information Technology (IT) orientation.  The two groups are then compared using a Mann-Whitney test.  The results are presented in Table 15.

Table 15

Mann-Whitney Statistical Results of Hypothesis 4

Changer Comparison of Research & Development and Information Technology

The results of the application of the test statistic suggest the null hypothesis is rejected at a significance level of p < .001, again superior to the p < .05 level typically accepted as a standard in the field.  It should be noted the Mann-Whitney test (as well as the Median test) automatically reports out as a 2-tail test in SPSS.  The hypothesis indicates a direction, therefore making a 1-tail test more appropriate even though, the 2-tail is more rigorous than the 1-tail. Therefore, application of the 2-tail test represents no threat to the conclusions.

The Mann-Whitney test requires the dispersions of the two populations being compared be identical.  In the validity study associated with the I-OptTM instrumentation, the Ansari-Bradley test was used to confirm this condition (Soltysik, 2000).  SPSS, however, does not contain the Ansari-Bradley statistic, and therefore, this condition could not be explicitly tested.  However the Median test, while weaker than the Mann-Whitney test, does not require equal dispersion.  Therefore, the Median test was applied to the data to indirectly eliminate this consideration.  The results are presented in Table 16.

Table 16

Median Test Statistical Results of Hypothesis 4

Changer Pattern Comparison of Information Technology and Research & Development Functions

Again, the results of the application of the test statistic suggest the null hypothesis is rejected at a significance level of p < .001.  Given this confirmation, it is reasonable to presume the assumption of equal dispersion within population groups does not threaten the findings.

The direction and magnitude of the association between Changer pattern scores concerning Research & Development (R&D) and Information Technology (IT) status can be inferred from an examination of the descriptive statistics as presented in Tables 17A and 17B. The scores of subjects holding an R&D position far exceed people in IT roles in mean values.

Table 17A

Hypothesis 4: Mean Research & Development Changer Pattern Results

Descriptive Statistics

Table 17B

Hypothesis 4: Mean Information Technology Changer Pattern Results

Descriptive Statistics

This correlation is perhaps more vividly demonstrated in the graphics provided within the SPSS program, as presented in Figures 10A through 10C.

Figure 10A

Hypothesis 4: Changer Pattern Median Scores by Information Technology and Research & Development

Figure 10B

Hypothesis 4: Changer Pattern Percent of Cases above Median by Information Technology and Research & Development

Figure 10C

Hypothesis 4: Changer Pattern Mean Scores by Information Technology and Research & Development

In summary, Hypothesis H4o is rejected, and H4a is accepted.  The evidence suggests people in the Research & Development group have significantly higher levels of the Changer Pattern than do people in the inherently more structured Information Technology group.

Hypothesis Five

This hypothesis proposes the Conservator strategic pattern is positively associated with organizational roles which demand disciplined processes.  Specifically, the hypothesis is stated as:

Hypothesis H5o:  Customer Service professionals will not have higher Conservator pattern scores, than will the general employee population of organizations.

Hypothesis H5a:  Customer Service professionals will have higher Conservator pattern scores than will the general employee population of organizations.

To test this hypothesis, organizational units clearly identifiable as having a Customer Service function were extracted from the TeamAnalysisTM database.  The balance of the database with all Customer Service personnel data removed represents the comparison group.  The two groups are then compared using a Mann-Whitney test.  Twenty-three people scored a zero in the Conservator pattern and, therefore, were excluded from the calculations.  The results are presented in Table 18.

The results of the application of the test statistic suggest the null hypothesis is rejected at a significance level of p < .001.  Again, the Median test was used to offset any risk from the potential violation of any assumption of equal dispersion required by the Mann-Whitney test.  The results are presented in Table 19.

Again, the results of the application of the test statistic suggest the null hypothesis is rejected at a significance level of p < .001.  Given this confirmation, it is reasonable to presume the assumption of equal dispersion within population groups does not threaten the findings.

Table 18

Mann-Whitney Test Statistical Results of Hypothesis 5

Conservator Comparison of Population and Customer Service

The direction and magnitude of the association between Conservator scores for Customer Service and the remainder of the population of the database can be inferred from an examination of the descriptive statistics, as presented in Tables 20A and 20B. The scores of people in a Customer Service function far exceed those in the remainder of the population of the database in mean values.

This correlation is perhaps more vividly demonstrated in the graphics provided within the SPSS program, as presented in Figures 11A through 11C.

In summary, Hypothesis H5o is rejected, and H5a is accepted.  The findings suggest people in the Customer Service function have significantly higher levels of the Conservator pattern as represented by their scores than do people in the remainder of the population database.

Table 19

Median Test Statistical Results of Hypothesis 5

Conservator Pattern Comparison of Customer Service and Population

Table 20A

Hypothesis 5: Mean Customer Service Conservator Pattern Results

Descriptive Statistics

Table 20B

Hypothesis 5: Mean Population Conservator Pattern Results

Descriptive Statistics

Figure 11A

Hypothesis 5: Median Scores by Population and Customer Service

Figure 11B

Hypothesis 5: Percent of Cases Above Median by Population and Customer Service

Figure 11C

Hypothesis 5: Mean Scores by Population and Customer Service

Summary

All of the hypotheses postulated in this study have performed as anticipated at a very high level of significance.  The single exception is encountered with Hypothesis 2, where the level of Reactive Stimulator was not found to systematically vary within leadership ranks.  However, supplemental analyses show the levels did systematically and significantly vary between the categories of leaders and non-leaders.  This is a hierarchical relation and would seem to satisfy the intent of the originally proposed hypothesis.

In general, the theory of intuition as discussed in the earlier chapters of this dissertation is supported by the results of the statistical analyses.  In other words, actual results in the field support Organizational Engineering theory as an explanation of the phenomenon of intuition.  However, the implications of these findings go far beyond the restricted area of intuition.  Chapter 5 presents the Summary and Conclusions, along with implications of this research and possible areas for future research.

Chapter 5

Summary and Conclusions

The definition of the concept of intuition varies within the literature.  However, it can generally be considered to be a non-rational decision-making process within which the decision-maker cannot easily or readily explain to another person how decisions are derived.  Because the basis of the decision cannot be easily explained, it is attributed to mental capacity defined as intuition.

Overview of Significant Findings

The literature review examined the various psychologically based approaches which address the issue of intuition.  In this research, it is shown Organizational Engineering can be used to explain the common process addressed by numerous other theorists and researchers. These theorists offer different specific definitions of intuition in their research, and Organizational Engineering is sufficiently robust to integrate all of them.

This study contends the phenomenon of intuition could best be observed in individuals who favor and apply the unpatterned thought and action modes.  This analysis is based on the fact the action mode can be observed by others.  In combination with an unpatterned method, the action mode is likely to reflect images and/or behaviors for the user of the Changer strategy (unpatterned method, thought and action modes) whom coworkers and colleagues perceive as an insightful person.

The review of literature disclosed people who tend to be promoted in organizations typically displayed more intuitive abilities than do others in this same organizational population.  Therefore, if the Organizational Engineering theory of intuition is correct, observers should be able to witness an increase in the use of unpatterned methods, as well as thought and action modes, by individuals at ever higher organizational levels.

The same phenomenological relationship is also analyzed according to functional groups within organizations.  If the theory of Organizational Engineering is correct as applied to intuition, others can witness a higher level of unpatterned method and action mode in Research and Development personnel than in Information Technology areas of a firm. Research & Development works in advance of current technology and, hence, has a strong need for less obvious relationships to create new products and processes, i.e. intuitive behaviors.  Information Technology, on the other hand, works within the boundaries of a well-defined, logical system.  Almost by its nature, processes are more readily explained within the Information Technology field.  Readily explained processes are typically not attributed to intuition.  Therefore, Research & Development functions are perceived to be more intuitive than Information Technology operations.

Another measure of Organizational Engineering theory is examined by comparing results collected from a Customer Service population those of the general organizational population.  Customer Service is a very confined area, tightly bound by rules, well-defined processes, and explicit procedures.  There is less allowance for intuitive processing of any kind; those scores when compared with the general population of the database in this area should reflect this in their low levels of Organizational Engineering correlates to intuitive behavior. 

Chapter Four of this research displays charted results of the findings in the statistical analyses of the five research hypotheses tested by this study.  In all cases, the findings were significant at the .001 level, beyond the defined level established by the SPSS statistical program.  Therefore, the findings are, at minimum, 50 times more powerful than the standard acceptable level of .05.

The single unexpected finding encountered in Hypothesis 2 suggests the degree of unpatterned method and action mode identified as Reactive Stimulator style does not increase as individuals are promoted into leadership roles.  A supplemental test, however, demonstrates the absolute level of this strategic style preference systematically differs between leaders and non-leaders at the .001 level.  This suggests a threshold-level of this capacity requires some degree of recognition for promotion into leadership rank.  However, leadership levels beyond this point provide less advantage for continued promotions within the various leadership hierarchies. 

Overall, the findings of this research create a compelling case for using Organizational Engineering theory over the older psychological theories as an explanation of intuitive behavior.  The Organizational Engineering theory appears to be more succinct and has greater theoretical rigor, while producing quantifiable results which far exceed the standards typically employed in organizational development research. 

Limitations of the Study

This study uses a system of testable hypotheses which, when examined individually and as a group, create a compelling argument for the value of Organizational Engineering as an explanatory paradigm in the area of intuition.  These hypotheses were predicated and correlationally analyzed using the I-OptTM instrumentation and Organizational Engineering Institute database, which share common variables used by other theorists in their research and studies.  To the degree the conceptual design of these instruments differ, and an underlying presumption that only one can be most effective, some intuition researchers will question the results.

The extensive database used in this research study clearly addresses challenges concerning the overall generalizability of these findings.  True, specific industries may be under-represented in the database used, which is a common criticism in most research of this type.  Researchers whose interest focuses on investigating a single organizational sample may find the results less than compelling.

Implications for Human Resource Management Professionals

The findings concerning threshold levels of Reactive Stimulator strategies to be a factor for admission into the managerial ranks may offer the most immediate value for the field of organizational development.  An argument can be made that the sudden and unusual action typical of the Reactive Stimulator strategy calls attention to the individual.  Because the individuals at higher organizational levels can notice and observe such employees, the probability for promotion into the managerial ranks improves.  If future research also finds this to be true, there are substantial implications for career development, as well as for leadership training.  This suggests people with lower levels of Reactive Stimulator skills can be taught to emulate Reactive Stimulator behavior patterns and; therefore, increase their probability of advancement. In addition, other considerations would relate to the value of intuition to increase the effectiveness of decision-making, productivity, and competitive advantage.

Organization Development consultants can use the results of this research to design or re-design systems, processes, and structures to either encourage or restrict non-rational thinking for the promotion of learning, problem-solving and decision-making. More specifically, items like idea generation; problem-solving, decision-making and strategy development might be considered; in light of the information processing patterns which support the desired outcomes.  Training and learning strategies can be implemented to develop these abilities in individuals. In other words, in what specific processes and at what stages can each of the styles preferences be integrated into the application repertoire of all employees to add strength to decisions or processes which could then result in enhanced productivity and competitive advantage?  Project management, for example, might be considered as a staged process. The Relational Innovator may have more value at the early stages where ideas and options can be admitted without penalty. The next stage of narrowing the field is more suited to the Hypothetical Analyzer’s skills of assessment and criteria analysis.  The implementation phase favors the disciplined strategies of the Logical Processor, supported by the quick reaction strength of the Reactive Stimulator.  The proof of these different well-defined patterns, existing in different measurable strengths in different people, might allow the overall optimization of project management in all types of organizational settings.

Another implication concerns the amount of structure, which can be optimally designed to support an employee using an intuitive strategy.  This support might include items such as infrastructure to detail level work of correspondence, record keeping, calendaring and work scheduling.  Identifying and quantifying such an optimal support strategy might allow an improvement in productivity at individual and organizational levels.  In other words, the gain in productivity from the individual using an intuitive strategy might be sufficient to offset the cost of the structured support systems and resources, while generating a profitable return on investment.  The one-size-fits-all, leaner-and-meaner strategy might be replaced with an intelligent allocation of information processing assets, guided by a defined theory and accurate measurement.

In the area of training, this research can be leveraged and extended to support the selection process of who goes to what type of training, as well as designing the types of training used at various hierarchical levels of an organization. In addition, this information can be further used as part of the training needs assessment for virtual and self-directed work teams to include telecommuter employees. Further training programs, which train people on how to better utilize their intuitive behaviors to gain greater degrees of speed, efficiency, effectiveness, and capacity environment, might be identified and specified.  In essence, what this creates is the ultimate version of customized training for each individual’s information processing and learning styles.  Organizational Engineering provides both the theoretical base and measurement tools to address these and other training issues.

Other implications for Human Resource and Organizational Development professionals include how they select, design, and utilize teams in our team-based workplace environments.  This can support staffing decisions and subsequent performance for designing workflow structures.  Teams, departments, workgroups, committees, and other forms of organized entities can benefit from varying mixes of information processing styles.  This research demonstrates systematic differences in strategic processing styles by hierarchical level and function.  The mix of styles within a group will enhance overall goal achievement, support designing ideal solutions for complex problems, as well as making the best decisions in a minimal amount of time.

Implications for Senior Executives include methods for improving policymaking, staffing, strategy, consensus building, and organizational culture.  Different mixes of strategic styles among the organizational populations could produce outcomes more easily predicted and controlled. In general, the findings of this research suggest there are multiple opportunities available to recruit, select, train, develop, and promote future leaders.  The systematic differences in strategic styles identified by this study do point the way to many possibilities for mixing and matching these styles in order to consciously structure more efficient and effective organizations.

Other areas rich with implications such as designing new work environments, global and virtual teaming, telecommuting, knowledge management, competency modeling and building, and fast cycle decision-making, just to name of few.  Essentially, the demonstrated existence of defined information processing strategies and styles can be applied to any area in which human beings must work in concert with each other to achieve a common purpose. 

Recommendations for Future Research

Research questions and supported results of this research carry significant implications across a wide range of subjects, from the philosophical to the practical.

On the philosophical side, the same processes which give rise to intuitive behavior in human beings are available to any information-processing organism.  Theoretically, since animals are information processors, they might display degrees of intuition.  If this proves true in future research, it means humans have lost yet another claim to being unique in the universe.  This would be a finding of significant dimension in philosophical circles.

Some other future considerations for research may include:

• Determine career patterns for individuals with high Relational Innovator scores and Changer patterns.   For example, perhaps the population for this research represents a residual of a much larger group.  Many people with these strategic preferences may have gotten lost in the climb to the top.  The relative risk of the strategy probably merits research.
• Research the information processing preferences among people in large Fortune 500-type organizations versus the less structured entrepreneurial organizations, which are growing more numerous. The possibility of different environments favoring different strategic styles suggests a separate stream of hypothesis worthy of investigation.
• Determine correlation between Goleman’s work on Emotional Intelligence and Relational Innovator scores and Changer patterns. Like intuition, emotional intelligence is a learned ability.
• Investigate economic performance relative to the varying styles and patterns at the CEO level merit serious investigation.  In other words, could certain styles correlate with better performance on a consistent basis at the highest leadership role?
• Examine or investigate the longevity of individuals at varying organizational levels.  Do certain styles lend themselves to staying in positions for shorter or longer periods of time? How could functions such as succession planning, recruitment strategies, and retention processes benefit from knowledge gained in this type of research?
• Conduct longitudinal studies to determine whether scores for the styles and patterns systematically change in relation to movement in the organization.  Organizational Engineering theory specifically allows for change in strategic styles and patterns, but does not focus on specific direction relative to hierarchical level.  Knowledge of systematic tendencies could support designs for more effective training and development programs for all employees within organizations.
• Implement uniquely designed benchmarking studies centered on the amount of time people with varying levels of various styles spend working in office versus out in the field, on the shop floor versus out with customers, and so on.  The existence of systematic differences in these behaviors could help guide strategic planning and more productive management practice and expectations.
• Determine if certain style and pattern strengths are correlated within professions such as medicine, law, accounting, and engineering could determine whether certain styles and pattern strengths are correlated with roles or jobs within each profession.  Findings in this area may provide insights about generalizations and stereotypes which individual professions are forced to address. These distinctions and verified discriminations could help facilitate social harmony, and public policy, as well as improving quality of work life issues for professionals.

In the final analysis, Organizational Engineering theory holds promise for all aspects of organizational design and development.  Any collective of individuals must be able to communicate in order to be a successful organization.  The existence of defined patterns of decision-making and communication postulated by Organizational Engineering and demonstrated in this research can impact any and all of these areas of professional concern across all disciplines.

Conclusions

The Organizational Engineering-based theory of intuition differs from other studies and theories by looking at intuition as a phenomenon arising naturally from information and decision-making processes.  Individuals using an unpatterned method (the organization of data being input) combined with thought and action modes (the character of the intended output) arrive at decision options not necessarily following any of the standard, logical, and/or existing processes.  When this happens, an outside observer could tend to attribute the unexpected idea as arising from some sort of insight process based on an intuition capability.

Organizational Engineering can assist in understanding how a process such as intuition influences how information is processed and decisions are made. It is this natural outcome of an information-processing pattern used to navigate life.  Organizational Engineering explains the same phenomenon as do the psychologically oriented theorists and researchers; and do so with more clarity of thought and practical application of the concepts. 

In conclusion, the findings of this research support the proposition that insight is a normal, probability-based phenomenon grounded in the information processing style of the individual.  The numerous implications of this study’s findings go beyond the scope of this dissertation and can extend to many other areas of human and organizational behavior.

APPENDIX A

I-OPT^TM SURVEY INSTRUMENT

http://www.iopt.com/IOpt%20Survey.htm

APPENDIX B

THE VALIDITY AND RELIABILITY OF ORGANIZATIONAL

ENGINEERING INSTRUMENTATION AND METHODOLOGY

• Face Validity

A expert panel of 50 professionals administered 14,655 surveys and found disagreement with the survey report in less than 1% of the cases (n=128, 0.87%).  The group based TeamAnalysis™ was tested by 44 experts in 921 administrations and was found to be inaccurate in less than 1% of the cases (n=1, 0.1%).  The face validity of both the instrument and the consolidation methodology as represented by TeamAnalysis™ is judged to be very high.

• Construct Validity

Statistical evidence in the context of the differential population methodology was applied to 3 occupational categories involving 75 distinct groups and 887 people were compared to a database population (N~8,700).  The findings are statistically significant at the .05 standard adopted in this study (p= .0152).  In addition, the theory’s use of only a single assumption minimizes exposures from undefined assumptions inherent in any theory.  Overall, Organizational Engineering appears to meet or exceed the standards of construct validity within the discipline.

• Content Validity

Content validity is more a matter of logic than of statistics.  However, a nomological net demonstrates that between 84% and 92% of the survey responses can be directly traced to specific dimensions of the underlying theory.  In addition, 100% of the 50 members of the expert panel agree that the response structure incorporated in the survey is not contaminated by respondent misunderstanding.  These findings suggest that the content validity is at least equal and perhaps superior to other theories within the discipline.

• Discriminant Validity

Discriminant validity was tested using an unsupervised learning method of cluster analysis.  The PAM algorithm run with k=3,887 was able to discriminate between three groups that should be different at a p < 10^-29 significance level, a level substantially in excess of the generally accepted p < . 05 standard of significance.

• Concurrent Validity

This dimension of validity relied upon the judgment of the expert panel of 50 professionals.  Between 32 and 48 experts responded to the various instruments and methodologies tested under Concurrent validity.  The experts reported that in their administrations, the number of inaccurate reports was zero (0%).  The concurrent validity of the instrumentation and methodologies is judged to be high.

• Predictive Validity

The large number of individuals (N = 8,721) and groups (1,003) encompassed by the study provide assurance of generalizability.  The statistical tests performed were shown to fully satisfy the proper criteria (e.g., identical dispersion, equality of variances, etc.) minimizing exposures based on statistical power.  In addition, the cross-validation across multiple dimensions of validity amplifies the assurance of the validity of the underlying theory and its expression in instrumentation and methodology.   In the author’s judgment, the theory and methodology fully meet the standards of validity as applied within the discipline of organizational development.

• Conclusion Validity

The large number of individuals (N = 8,721) and groups (1,003) encompassed by the study provide assurance of generalizability.  The statistical tests performed were shown to fully satisfy the proper criteria (e.g., identical dispersion, equality of variances, etc.) minimizing exposures based on statistical power.  In addition, the cross-validation across multiple dimensions of validity amplifies the assurance of the validity of the underlying theory and its expression in instrumentation and methodology.   In the author’s judgment, the theory and methodology fully meet the standards of validity as applied within the discipline of organizational development.

• Reliability

Reliability is technically not a form of validity. The reliability of the instrument was tested for all pair wise combinations of the years 1994 through 1999 (15 individual contrasts) using the Kruskal-Wallis test.  In all cases, the findings confirmed reliability by showing that differences in the data between years could not be established.  The survey instrument is judged reliable by the accepted standards of the discipline.

Source:  Robert Soltysik.  Validation of Organizational Engineering Instrumentation and Methodology.  Amherst:  HRD Press, 2000.

APPENDIX C

PERMISSION LETTER

APPENDIX D

CLASSIFICATION OF HIERARCHICAL LEVELS

The LeaderAnalysis™ database consists of entries by group reflecting the leader and his or her subordinates.  The data is collected using the I-OptTM instrument, which is used to collect self, described information on any organized collection of people by teams, departments, committees, workgroups and leadership role.  Therefore, it is possible to have multiple entries for a single leader. 

The database also contains the title of the leader as reported by the person requesting the analysis.  Title information is not available in some cases due to oversight, refusal to provide the information, or lack of knowledge on the part of the person requesting the analysis.

The original database provided by the Organizational Engineering Institute for this study contains information for 470 groups.  Eliminating duplicate entries for the same name and entries without titles reduced the available data to 438 groups headed by designated leaders.

The titles used can vary by organization.  For example, one manufacturer of heavy equipment uses the title “Division Head” to designate a person who heads a distinct functional area such as Training and Development.  In other firms a person with the title of Director could hold this same responsibility.  A similar ambiguity exists between the titles of Director and Manager.  Often the title Director is awarded as an acknowledgement of longevity or contribution rather than identifying a scope of responsibility.  To standardize the varied designations, individuals in leadership positions are divided into four categories.  They  are:

President and CEO: These are people who head an organization and either own it or report to a board of directors.  People in this category include the heads of Fortune 50 firms, startup DotComs, service firms and nonprofit organizations.  The size of the firms ranges from 6 employees to over 30,000. Coding for statistical purposes was “0”.

Vice Presidents: These are people who have been designated as a vice president or above by their firms.  Presidents of subsidiary companies are included in this category.  These people carry the legal assumption of apparent authority and can be reasonably assumed to represent the senior management of a firm.  Coding for statistical purposes was “1”.

Managers and Directors: These are people who head a functional area (e.g., Accounting, Federal taxes, Organizational Development, Sales, Human Resources, Information Technology, Customer, Service, Research & Development, etc.) or who have multiple managers reporting to them.  These people are judged to be middle management. Coding for statistical purposes was “2”.

Supervisors: These are people who head an area under a manager (e.g., a reporting section in Accounting) or who are designated Team Leader within the database.  People in this position are judged to represent the lower organizational rankings. Coding for Statistical purposes was “3”.

Applying the above to TeamAnalysis^TM database yielded the numerical counts in

Table 21

HIERARCHICAL DISTRIBUTION OF LEADER ANALYSIS^TM DATABASE