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Innovative Genius: A Framework for Relating Individual and Organizational Intelligences toInnovation

Author(s): Mary Ann GlynnSource: The Academy of Management Review, Vol. 21, No. 4 (Oct., 1996), pp. 1081-1111Published by: Academy of ManagementStable URL: http://www.jstor.org/stable/259165 .

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g Academy of Management Review1996, Vol. 21, No. 4, 1081-1111.

INNOVATIVEGENIUS:A FRAMEWORKFOR RELATING NDIVIDUALAND ORGANIZATIONALNTELLIGENCESTO INNOVATIONMARY ANN GLYNNEmory University

In this article, organizational innovation is viewed as fundamentallycognitive, and the concept of organizational intelligence is developedand related to innovation. Individual and organizational intelligencesare conceptualized as being functionally similar (i.e., as purposefulinformation processing that enables adaptation to environmental de-mands). Organizational intelligence, however, is a social outcome andis related to individual intelligence by mechanisms of aggregation,cross-level transference, and distribution. A conceptual framework isproposed that relates types and levels of intelligence, moderated bycontextual factors, to the two stages of the organizational innovationprocess: initiation and implementation. Implications for research andmanagement are discussed.

In its essence, innovation involves intelligence; to put it simply, "Aninnovation is a new idea" (Van de Ven, 1986: 591). Absent the creativespark of innovative genius or the intelligence of organizational systemsthat recognize and support innovation, finding new and useful solutionsto problems becomes troublesome. Advancing the idea that "[a]t their core,most successful enterprises today can be considered intelligent enter-prises," Quinn (1992: 48) epitomized the growing realization that organiza-tions need to effectively manage their intellectual resources as well astheir physical assets. By so doing, organizations enhance their adaptivepotential to meet increasingly turbulent and uncertain environmental con-ditions.The role of intelligence in innovation becomes evident when intelli-gence fails innovation, as, for instance, when organizations make routine,noninnovative responses to novel and complex problems (Marcus, 1988),or, conversely, when firms make innovative responses when a routine onewould suffice (Walsh & Ungson, 1991). Authors have hinted at the role ofcognition in fostering innovation. Mezias and Glynn (1993) found that the

This article benefited greatly from constructive insights offered by Pamela Barr, RobertDrazin, AMR's five anonymous reviewers, and Susan Jackson; my thanks go to all of them.1081

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1082 Academy of Management Review Octoberamount and type of organizational innovation is related to learning pro-cesses, and Cohen and Levinthal (1990) demonstrated that organizationalinnovation is dependent upon the organization's knowledge base. Implicitin theories of organizational cognition, such as organizational learning(Senge, 1990), memory (Walsh & Ungson, 1991),and sense making (Weick,1990), is intelligence, for without it an entity cannot learn, remember, orprocess information effectively. Although cognitive perspectives on orga-nizations have flourished in recent years, researchers have not elaboratedon either the nature and function of intelligence in organizations or on itsrole in affecting innovation. That is the purpose of this article.In the realization that intelligence is "the ability to solve problems,or create products, that are valued within one or more cultural settings"(Gardner, 1993:x) lies its link to organizational innovation, which is definedas novelty that is useful (Amabile, 1988; Kanter, 1983). Figure 1 providesthe conceptual framework for this article. The objective is to begin tobuild a theory that explains the cognitive foundations of organizationalinnovation. The central idea is that intelligence is embedded in organiza-tions and operates both through individual agents and institutionalizedsystems to affect organizational innovation. Organizational innovation isbased on individual and organizational intelligences, which are moder-ated by contextual factors. Thus, the question of how to make firms moreinnovative involves the question of how to make firms more intelligent. Theframework of Figure 1 is used to organize this analysis of the intelligence-innovation relationship in organizations.

INTELLIGENCE N ORGANIZATIONS:INDIVIDUALAND ORGANIZATIONALAn organization is a body of thought thought by thinking think-ers. (Weick, 1990: 288)

Like other cognitive constructs applied to organizations, intelligencecan be considered at multiple levels of analysis. Adopting the multilevelframework outlined by Glynn, Lant, and Milliken (1994), I examine intelli-gence at both the individual level and the systemic level; I also considerthe interrelationship of these levels.Because I was interested in exploring the relationship between orga-nizational innovation and intelligence, I focus on how intelligence is mani-fested by individuals as members of organizations and by an organizationas a collective. Although it is feasible to examine intelligence at otherlevels of analysis, particularly at the intermediate, meso, or small-grouplevel (e.g., Williams & Sternberg, 1988), setting limits on this exploratorywork was necessary.Individual Intelligence

In the psychological literature, individual intelligence is conceptual-ized as information-processing capability that is used to solve problems

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1084 Academy of Management Review Octoberor meet task challenges (Sternberg &Salter, 1988).Importantly, intelligencerequires intentionality (of the actor), and it is flexibly adaptive, not rigidlystereotyped (Cantor &Kihlstrom, 1989).Earlier literature focused on intelli-gence as an individual trait (e.g., Spearman, 1927; Terman, 1916), whichconsisted of several basic cognitive processes, including perception,learning, encoding, memory, and reasoning. Fundamental to intelligenceis expertise, the repertoire of knowledge used to solve problems. Thisrepertoire consists of both declarative knowledge (i.e., factual information,causal beliefs, or perceptual orientations) and procedural knowledge (i.e.,the strategies, rules, and skills for acquiring, storing, retrieving, and ma-nipulating declarative knowledge) (Cantor & Kihlstrom, 1989).Although intelligence is generally viewed as purposeful information-processing capability (Barron &Harrington, 1981;Gregory, 1994),there is noconsensual definition of the construct for animals, humans, or machines. Atpresent, there are two major-but divergent-approaches to intelligencein the psychological literature: (a) a cognitive or psychometric perspective,which focuses on intelligence as an individual trait, and (b)a contextualistperspective, which focuses on intelligence as a social product, related tothe cultural, normative web in which individuals are embedded (Stern-berg, 1985a). These two perspectives differ in their theoretical orientation,levels of analysis, assumptions about the measurement of intellligence,and ways in which differences in intelligence can best be explained; theyare outlined in Table 1. Both perspectives are examined in this article,because, taken together, they offer a broader and more comprehensiveapproach to organizational intelligence.Cognitive or psychometric perspective. According to this perspective,intelligence is conceptualized as an individual's overarching capacity forthinking and problem solving; this "general cognitive ability" is calledthe g factor (Spearman, 1927). Thus, the main objective of the cognitiveperspective has been the development of standardized instruments withwhich to assess interindividual differences in intelligence; the intelligencequotient (IQ) test eventually became the dominant indicator.In empirical studies on the effects of individual intelligence in worksettings, researchers found that intelligence (or general cognitive ability)is an important predictor of task performance, particularly for complexjobs (Gottfredson, 1986; Hunter, 1986). Support for the classic tenet that"Performance = Motivation x Ability" (Campbell, 1976) was demonstratedin several studies. In a longitudinal survey of 105 MBAgraduates, O'Reillyand Chatman (1994) found that together intelligence and hard work af-fected job performance and career success. Similarly, Wright, Kacmar,McMahan, and Deleeuw (1995), in their study of 203 warehousers, demon-strated that cognitive ability had significant main and interaction effects(with personality) on the development of work-related knowledge andperformance. Ree, Carretta, and Teachout (1995)found that cognitive abil-ity directly affected the acquisition of job knowledge and indirectly af-fected work performance. Thus, there is considerable empirical validation

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1996 Glynn 1085

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1086 Academy of Management Review Octoberthat general cognitive ability is a significant predictor of job and careeroutcomes in organizational settings (Gottfredson, 1986; Hunter, 1986;Schmidt, Hunter, Outerbridge, & Goff, 1988).Despite this evidence, the cognitive or psychometric perspective hasbeen faulted for being too limited and not inclusive of the full range ofhuman activities that might be labeled intelligent. Also, it may be anoverly strict, individually centered measure of intelligence that does notaccount for how intelligence may be defined by, and related to, the socialor cultural context in which it develops and functions (Gardner, 1993;Sternberg, 1988).Contextual perspective. Contextualists view individual intelligenceas composed of a number of distinct abilities (Sternberg & Salter, 1988),not as an overarching trait common to all individuals. In contrast to thepsychometric perspective, in which individual intelligence is invariant tocontext, contextualists argue that intelligence will vary by specific do-mains; thus, because people are members of different societies and cul-tures, individuals can have different types of intelligence. Radical for-mulists argue for cultural relativism (e.g., Vygotsky, 1978), contending thatdifferences in intelligence reflect differences among cultures and prac-tices, rather than differences among individuals. A theme common to thisperspective is that intelligent behavior occurs in a social context thatincludes expectations, demands, and a history of prior experience.Contextualists argue that intelligence is multifaceted and that thereare multiple intelligences, if not within a single individual, then certainlyacross a spectrum of individuals. Gardner (1993: xi) introduced seven can-didate intelligences: "the linguistic and logical-mathematical intelli-gences that are at such premium in schools today; musical intelligence;spatial intelligence; bodily-kinesthetic intelligence; and two forms of per-sonal intelligence, one directed toward other persons, one directed towardoneself." Naive, popular, or implicit theories of intelligence (Sternberg,1985a) have been focused on individual performance in everyday workand life contexts, and they have been used to classify intelligence intothree categories: practical problem-solving ability, verbal ability, and so-cial competence. Because intelligence is defined relative to a particularcontext, researchers have been concerned with the characteristics thatdifferentiate contexts, and organizations have been considered a majorcontextual determinant (Veroff, 1983). Thus, "intelligence in the popularsense of the word is inextricably linked to a specific sociocultural environ-ment" (Cantor & Kihlstrom, 1989: 9).Critics of the contextual perspective contend that even though individ-uals may manifest different "types" of intelligence, this may not refutethe existence of a g factor; that is, individuals may simply demonstratedifferential weightings of their intellectual abilities in response to situa-tional demands. Supporting this idea are studies that demonstrate thatthere is not a large variance in individuals' intellectual performanceacross different contexts (Sternberg & Salter, 1988).

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1996 Glynn 1087Defining individual intelligence. Although there is no one best wayto study intelligence (Sternberg, 1985b), the following definition is culled

from this review of the literature:Individual intelligence is defined as a person's capabil-ity to process, interpret, encode, manipulate, and accessinformation so as to acquire, retain, and apply knowl-edge quickly and successfully to meet external chal-lenges or solve problems in a particular domain orcontext.Stated simply, individual intelligence is a person's purposeful informationprocessing that aids adaptation to task or environmental challenges. Itinvolves both task-relevant domain intelligence (i.e., declarative knowl-edge) as well as flexible rules (i.e., procedural knowledge) for acquiringinformation and combining existing declarative knowledge to developnew knowledge.Organizational Intelligence

Although intelligence has been associated primarily with individuals,some authors have begun to conceptualize and measure it at a collectivelevel (e.g., Williams &Sternberg, 1988).From the outset, it must be acknowl-edged that extending a microlevel construct to the macrolevel organizationinvites opportunities for ambiguity and threats of anthropomorphism. Ad-ditional confusion stems from the various uses of organizational intelli-gence, including a description of the intelligence of individual organiza-tion members as well as a description of the system (e.g., March & Olsen,1986; Pinchot & Pinchot, 1993; Quinn, 1992); a description of informationprocessing capabilities as well a description of the outcome or product ofthese processes (e.g., intelligence about new technologies or one's compet-itors); a real property of systems (Huber, 1990; Leidner & Elam, 1995);anda metaphor for organizational systems (Garud &Kotha, 1994;Morgan, 1986).

In this article, the conceptual boundaries of organizational intelli-gence are established according to the three working assumptions thatWalsh and Ungson (1991) used to develop the construct of organizationalmemory: (a) organizations functionally resemble information-processingsystems that process information from the environment; as such, organiza-tions exhibit intelligence that is similar in function to that of individuals;(b)modeling organizations as information-processing systems implies thatthey also are interpretative systems that scan, interpret, and diagnoseenvironmental events for their uncertainty and complexity, which supportsthe basic idea that adaptive capability underlies intelligent action; and(c) conceptualizing an organization as "a network of intersubjectivelyshared meanings that are sustained through the development and use ofa common language and everyday social interactions" (Walsh & Ungson,1991: 61) delineates intelligence as a concept that is invoked to explain asystem but is itself not easily observed.

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1088 Academy of Management Review OctoberThe first assumption, that of functional similarity between human andorganizational intelligence, leads to the following definition of organiza-

tional intelligence:Organizational intelligence is an organization's capabil-ity to process, interpret, encode, manipulate, and accessinformation in a purposeful, goal-directed manner, so itcan increase its adaptive potential in the environmentin which it operates.This definition embodies the second boundary condition (i.e., that organi-zational intelligence is adaptive); like individual intelligence, organiza-tional intelligence is related to solving problems, meeting objectives, andmaking effective responses to environmental challenges. Regarding thethird boundary condition, organizational intelligence offers an explana-tion for experiential learning processes that underscore organizationalsuccesses and failures (Glynn et al., 1994). Learning intelligently impliesthat an organization has learned correctly, accurately, and appropriatelyfrom experience; armed with good and valid information, the organizationhas the potential to perform more effectively.Although organizational intelligence may bear a functional resem-blance to individual intelligence, it is clearly not commensurate withindividual intelligence. As a property of the collective, organizationalintelligence is a social outcome. Organizational intelligence can resultfrom the accumulated wisdom of its members as well as from interactionsamong its members, who can be characterized as having varying levelsof intelligence (according to psychometric measurements) and varyingtypes of intelligence that are tied to specific domains or contexts (e.g.,practical, linguistic, or social intelligence). That the interchange amongintelligent members affects the intelligence of a collective is evident inthe concept of "group intelligence," defined as

a concept distinct from the more familiar concept of individualintelligence-for in the interdependent context of group func-tioning, group members may be involved in the collaborationdifferentially with regard to their abilities and desires, yield-ing a system with characteristics and capacities unlike thoseone group member could display alone. Groupintelligence isthe functional intelligence of a group of people working as aunit. (Williams &Sternberg, 1988:356)Given that organizational intelligence is not identical with, but relatedto, the intelligence of its membership, mechanisms that relate individualand organizational intelligence are considered.Mechanisms Relating Individual and Organizational Intelligences

By drawing from other multilevel models that were used to examinethe link between microlevel and macrolevel processes (DiMaggio, 1991;Glynn et al., 1994; Rousseau, 1985), I identify the following set of mecha-

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1996 Glynn 1089nisms: (a) aggregation effects, whereby individual members' intelligenceaccumulates to become organizational intelligence; (b) cross-level effects,whereby individuals' intelligence is transformed and codified as organiza-tional intelligence; and (c) distributed effects, whereby organizational in-telligence is embedded in the structured patterns of thought and actionin which organizational members interact and engage. Each of thesemechanisms is built on a different set of theoretical assumptions and hasimplications for the way in which organizational intelligence is measured;the premises and implications of these three models are summarized inTable 2.Aggregation model. Through an aggregation model, organizationalintelligence is modeled as consisting of the accumulated intelligence of itsmembership. This model is based on well-defined measures of individualintelligence, such as IQ tests. Organizational intelligence can be mea-sured, then, as the sum, the mean, or the maximum value of members'scores on measures of general cognitive ability (Williams & Sternberg,1988).This measure thus affords an overall index of the level of organiza-tional intelligence, but it does not capture the multiplicity of intelligencetypes within an organization.An aggregation model represents a simple, straightforward, easilycalculated rendering of organizational intelligence, which is consistentwith the way in which individual intelligence has long been measured.However, the usefulness of an aggregation model of organizational intelli-gence is severely limited. It is most applicable to organizations that havea very small membership, which is fairly homogeneous with respect tolevel and type of intelligence, and that have a structure with little special-ization. Single-product (or single-service) organizations operated by a soleentrepreneur or very few partners may describe a case in which organiza-tional intelligence and individual intelligence are virtually one and thesame (i.e., typically that of the chief executive). There is dubious validityin applying an aggregation model to very large conglomerates that havehighly divisionalized structures and a diverse, heterogeneously intelli-gent, geographically dispersed, and loosely coordinated workforce, inwhich intraorganizational processes are likely to affect the relationshipbetween the intelligence of individuals and the intelligence of the system.The assumptions of an aggregation model imply that organizationscan be smarter (or less intelligent) than their membership, if the organiza-tional IQ is significantly higher (or lower) than that of the majority of itsmembers; members with a very high (or very low) IQ score may skew thedistribution and inflate (or deflate) the mean organizational intelligencescore. Thus, although the simplicity of an aggregation model is attractive,its ability to capture veridically organizational intelligence is quite re-stricted.Cross-level model. A cross-level model directs attention to the trans-ference of intelligence. Accordingly, diffusion and institutionalization pro-cesses convert and encode individual intelligence in the organization's

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1090 Academy of Management Review Octoberfn -0I.. > >4

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1092 Academy of Management Review Octobermemory, routines, rituals, standard operating procedures, and symbolsand thus become organizational intelligence; socialization processestransmit intelligence from embedded systems to individual members.Three types of transference mechanisms are considered here: structuredorganizational roles, technology, and social or political influences.One structural mechanism instituted by GE, Coca-Cola, Cigna, Hew-lett-Packard, Monsanto, and Young & Rubican is the new organizationalrole known as the chief learning officer (CLO). These executives are "incharge of directing knowledge to the right places" and extending the flowof individual knowledge, information, and intelligence throughout theorganization (Ward, 1996: 12). In the following example, GE's CLO bringsdisparate information together to solve a problem intelligently:

The General Electric manager was dismayed. As he spoke toa recent gathering of company workers, he displayed a chartshowing that sales of appliances had slowed substantially.The appliance division, he and others surmised, appeared tobe in serious marketing trouble.But the attendees soon learned that the problem had nothingto do with pricing, advertising or other basic marketing tasks."Up speaks a GE Capital guy and puts up his chart showingconsumer debt reaching saturation levels,". . . "Suddenly,ev-eryone had a whole new angle on the problem." That newperspective led the employees to trysolutions not frommarket-ing but rather from finance, such as new ways to help debt-laden customers pay forbig-ticket appliances. (Ward,1996:12)

Just as organizational roles (e.g., CLOs) can diffuse intelligence, so toocan technologies. Because intelligence involves information processing,those MIS and expert system technologies that facilitate organizationallearning (e.g., Argyris, 1992; Elofson & Konsynski, 1993) similarly enablethe development of organizational intelligence. Huber (1990:63)contendedthat the "[u]se of computer-assisted information storage and acquisitiontechnologies leads to organizational intelligence that is more accurate,comprehensive, timely, and available." Similarly, Quinn (1992: 311) ac-knowledged that much organizational wisdom and managerial knowl-edge is captured and stored by information technologies (IT)in databases;the result is that "[w]ell developed IT systems help eliminate errors [and]leverage intellect." In spite of the advantages such computerized systemsoffer, however, they are constrained to operate within a particular contextand use the algorithms, decision rules, and assumptions that define thatparticular context. Thus, even though MIS, expert systems, and computertechnologies may hasten the development of organizational intelligence,they also limit it to a particular context that is delineated by the initialconditions under which the computer algorithms were developed.Social and political influences also affect diffusion and transferencemechanisms. There is ample evidence that "groups have the potential toenhance individual processes-as well as the potential to degrade them"

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1996 Glynn 1093(Sniezek, 1992: 131). The effects of such interpersonal factors are evidentin the group intelligence that emerges from interpersonal interactions andprocesses (Williams & Sternberg, 1988). In a series of studies that exam-ined the influences of majority and minority views on task performance,Nemeth (1986) demonstrated that the positions expressed by a majorityof individuals tended to foster convergent thinking, limit the number ofalternatives, and enforce conformity to the prevailing views. Conversely,minority viewpoints tended to stimulate divergent thinking and led tomore effective solutions: "Persons exposed to opposing minority viewsexert more cognitive effort . . . attend to more aspects of the situation. . .and . . . are more likely to detect novel solutions or come to new decisions"(Nemeth, 1986:25). Thus, underrepresenting or suppressing minority view-points can affect the processing of information and, in turn, both intelli-gence and creativity.More generally, intelligence is fostered in social climates in whichdiversity of viewpoints is permitted. Laughlin (1988: 258) pointed out thatconformity to a unanimous but erroneous majority can be reduced whena dissenting minority viewpoint is introduced. Numerous studies of grouppolarization have demonstrated that an initial tendency of groups towarda particular direction is enhanced following group discussion. In his re-view of this literature, Isenberg (1986: 1143) noted that there is evidencethat such polarization can result in group norms of risk or caution andthat "group members associate ability and skill with riskiness (or cau-tion) and thus become more risky (or more cautious) in order to appearmore able and skillful." In one study, for instance, the authors (Baron &Roper, 1976)found that, in order to appear more intelligent, individuals po-larized their estimates to align with that of the norms. Thus, these social-psychological influences explain why the intelligence that characterizesa collective may not be simply an aggregation of members' intelligence.Distributed model. In contrast to the cross-level model, a distributedmodel is focused not on how intelligence is transferred within an organiza-tion but, rather, on how organizational intelligence emerges from the pat-terned interactions that constitute the organization (Brown &Dugoid, 1991;Lave &Wenger, 1991).Two key insights of a distributed model follow fromthe contextual perspective: (a) intelligence must be understood in termsof, and in relation to, the social and cultural context in which it developsand (b) intelligence may exist beyond individuals and be distributedwithin the structural and symbolic systems of the collective. Therefore,

intelligence inheres as much in the artifacts and individualsthat surroundone as in one's own skull. My intelligence doesnot stop at my skin; rather, it encompasses my tools (paper,pencil, computer), and my networkof associates (officemates,professional colleagues, others whom I can phone or to whomI can dispatch electronic messages). (Gardner,1993:xiii)Central to the distributed model is Walsh and Ungson's (1991:60) thirdassumption, that an organization is a system of "intersubjectively shared

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1094 Academy of Management Review Octobermeanings" sustained through social interaction. March and Olsen (1986:26) allowed for the possibility of intelligent action within loosely coupledorganizations, and they argued that some "central mechanisms of organi-zational intelligence" are not limited to only coordination, control, andevaluation systems in organized anarchies, but that "ambiguous goals,loose coupling and garbage can processes are . . . frequently . . . formsof intelligence." Thus, organizational symbols, patterns of interaction, cul-ture, and socialization processes distribute and encapsulate organiza-tional intelligence because "patterns of behavior in organizations codeideas" (Sandelands & Stablein, 1987: 143).A distributed model of organizational intelligence is informed by orga-nizational theories that center on the creation of meaning, the social con-struction of reality, and the development of organizational culture andsymbolism (e.g., Daft & Weick, 1984; Walsh & Ungson, 1991; Weick, 1979).The idea that organizational intelligence arises from embedded interac-tions is consistent with the view that organizations consist of interlockedand institutionalized behaviors (Berger & Luckmann, 1966;Sandelands &Stablein, 1987; Weick, 1979). In this case, the focus is primarily on thepatterning and dynamism of these organizational behaviors rather thanthe intellectual capacity of individual organizational members (e.g.,Weick & Roberts, 1993). This view is echoed in theories of learning thatcontextualize learning in the social, cultural, and communal environmentin which it takes place (Brown & Dugoid, 1991). Intelligence, according toWeick and Roberts (1993), is the hallmark of those organizational systemsdesigned for reliability over efficiency. Sandelands and Stablein (1987:138), in their construction of "organizational mind," described intelligenceas "the ability to maintain a working similarity between mind and nature.. More generally, this ability is concerned with achieving and maintain-ing congruence or 'isomorphism' between what is mind (i.e., ideas, feel-ings) and what is external."An organization may be smarter than its individual members.Whereas individuals are limited in their capacity to process information(March & Simon, 1958),this limitation is easily overcome by the collective.Routine processes and organizational symbols that are rich in informationthat is accurate, relevant, and externally isomorphic can lead to smartorganizations. Conversely, however, individual members may be smarterthan the organization; this is particularly true when organizational sys-tems fail to institutionalize intelligent ideas or recognize the intelligentcontributions of members.INFLUENCES OF INTELLIGENCEON ORGANIZATIONALINNOVATION

The process of innovation is parallel for individuals and orga-nizations. Foreach the game is one of intelligent capitalizationon chance. (Staw, 1990:305)Organizational Innovation

Organizational innovation is the process of bringing new, problem-solving ideas into use (Amabile, 1988; Kanter, 1983).An innovation is novel

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1996 Glynn 1095to the adopting organization, but it may imitate something that existselsewhere (Aiken & Hage, 1971;Damanpour, 1991;Kimberly, 1981;Marcus,1988;Rogers &Shoemaker, 1971;Van de Ven, 1986).Innovation is intendedlyadaptive, and it is undertaken typically in response to unfamiliar, unex-pected, or nonroutine problems.More formally, innovation is defined as "nonroutine, significant, anddiscontinuous organizational change" (Mezias & Glynn, 1993:78) that em-bodies a new idea that is not consistent with the current concept of theorganization's business (Galbraith, 1982). Innovation, particularly radi-cal, frame-breaking innovation (Dewar & Dutton, 1986; Ettlie, Bridges, &O'Keefe, 1984; Nord & Tucker, 1987), involves organizational intelligencebecause it involves changes in existing organizational competencies(Mezias & Glynn, 1993) and cognitive paradigms (Anderson & Tushman,1990; Tushman & Anderson, 1986;Tushman, Newman, & Romanelli, 1986),mental models (Senge, 1990), and theories in use (Argyris & Schon, 1978).Innovation is a subset of the broader category of organizational change;innovation encompasses creativity as a subset (Woodman, Sawyer, & Grif-fin, 1993).In conceptualizing the process of organizational innovation, most re-searchers use a stage approach. However, "there is no one universal andsmooth sequence of steps from initial vision through idea generationthrough development and final implementation" (Amabile, 1988:151).Manyresearchers (e.g., Marcus, 1988; Rogers, 1983;Staw, 1990;Zaltman, Duncan,& Holbeck, 1973;Van de Ven, 1986)support the following two-stage model:(a) an initiation stage, which consists of "all activities pertaining to prob-lem perception, information gathering, attitude formation and evaluation,and resource attainment leading to the decision to adopt," and (b) animplementation stage, which consists of "all events and actions pertainingto modifications in both an innovation and an organization, initial utiliza-tion, and continued use of the innovation when it becomes a routine featureof the organization" (Damanpour, 1991:562). By using this two-stage model(depicted in Figure 1),I do not mean to suggest that organizational innova-tion is necessarily simple, linear, or fully preprogrammed. The processwas realistically described by Quinn (1985:83) as "opportunistic, customerresponsive, tumultuous, nonlinear and interactive in its development."The inherent simplicity of this model is useful, however, for the theory-development objectives of this article.Several researchers have elaborated on this basic model to expandthe number of innovation stages. For instance, Cooper and Zmud (1990)proposed a six-stage model for information technology innovation: initia-tion, adoption, adaptation, acceptance, routinization, and infusion. Witha similar focus on technology-based innovative projects, Roberts and Fus-feld (1981)viewed implementation as involving six stages: preproject, proj-ect possibilities, project initiation, project execution, project outcome eval-uation, and project transfer. Although these fine-grained approaches offera detailed examination of the innovation process, which is useful fortracking and managing innovative projects in a firm, this level of specifi-

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1096 Academy of Management Review Octobercation is beyond the scope of this conceptual framework. Because creatorsof most stage models acknowledge the dual components of initiation andimplementation/adoption as being vital, this article focuses on these twokey stages. The two-stage model is useful because it breaks down theinnovation process into a series of tasks, each associated with a particularset of skills or roles, which, it is proposed, relates to a particular set ofintellectual demands.Dominant intelligences and organizational innovation. Several re-searchers have found that different individuals, or different types of individ-uals, are associated with different stages of the innovation process. Innova-tors (Kirton, 1976) are the idea generators who initiate idea generation instage 1; hey to be nonconformers and will disregard or violate existing orga-nizational rules and norms as the need arise. By contrast, stage 2 adaptors(Kirton, 1976), or innovation champions (Howell & Higgins, 1990; Pinchot,1985), have more bureaucratic savvy, which they use to navigate ideasthrough the organization's formal and informal "corporate immune" sys-tems (Pinchot, 1985), where resistance is often encountered. Roberts andFusfeld (1981)' found support for these distinctions in their analysis ofthousands of staff profiles in R&D and engineering firms: Idea generatorshave expertise in a limited number of fields, enjoy conceptualizing ab-stract ideas, see new and different ways of doing things, and tend to workalone. In contrast, innovation champions have a wider range of interests,are more applied, and interact with others to sell ideas. Beath (1991) alsofound that, similar to other innovation champions, IT champions also re-lied on the technical resources and political support of the organization.Implicit in the distinction between innovators and adaptors (Kirton,1976) is that different types of expertise or intelligence are involved ateach stage. In the initial, inventive stage, intelligence concerning task-specific domains is vital. Technical knowledge of the task domain (whetherit be, for instance, verbal, mathematical, mechanical, spatial, musical,aesthetic, or practical) is important to solving problems within that do-main. In the second stage, however, it is knowledge about the organiza-tion's web of formal and informal influence systems (e.g., social, political,or interpersonal intelligence) that can influence the acceptance of newideas and innovative change. Thus, the dominant intelligence that suc-cessfully underlies the generation of new ideas is proposed to be differentfrom the dominant intelligence that underlies successful implementationof those ideas. Although the intelligence behind idea generation maycapitalize on domain-relevant and creativity skills (Amabile, 1988), theintelligence behind implementation requires knowledge about the organi-

'In their complete model, Roberts and Fusfeld (1981) proposed five critical functions,corresponding to their five-stage model of innovation. The first two functions (idea generation,championing) are discussed, but the remaining three, all relating to project managementonce an innovation is adopted (project leading, gatekeeping, sponsoring or coaching), are not.

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1996 Glynn 1097zational context and interpersonal skills. For both stages, the cognitiveagility to combine and recombine existing knowledge in new and differentways is critical, as it is to any process of creativity, innovation, and change(Amabile, 1988); thus, procedural knowledge must be fluid.

Proposition 1:Different dominant intelligences are asso-ciated with different stages of the innovation process.The dominant intelligence of innovation initiation (stage1) is technical knowledge that is relevant to the taskdomain orproblem. The dominant intelligence of innova-tion implementation and adoption (stage 2) is social, po-litical, and/or interpersonal, which is specific to the orga-nizational context. Both stages are characterized byprocedural flexibility in the combining and recombiningof factual (declarative) knowledge.Levels of intelligence and organizational innovation. Figure 1 depictsthe first stage of innovation as being based on (a) domain-specific intelli-gence at the individual level and (b) context-specific intelligence at theorganizational level. Domain-specific technical intelligence generally re-flects an individual's education, training, expertise, and knowledge withina particular context (Gardner, 1993); thus it is usually described at theindividual level of analysis. Organizational intelligence can be domain

specific also; certainly, organizations develop distinctive competencieswithin their industries or environmental niches that may reflect domainintelligence. However, for organizations, context-specific knowledge at theinitiation stage primarily relates to problem perception and informationgathering (Damanpour, 1991);it makes unfamiliar events understandablein terms of how they relate specifically to the organization. In other words,organizations tend to understand novel or uncertain environmental eventsnot in an abstract manner, but in a self-referential one (Milliken, 1990).Proposition 2: There are different dominant intelligencesat different levels of analysis that affect the initiationstage of organizational innovation. The dominant indi-vidual intelligence is domain relevant, whereas the dom-inant organizational intelligence is context specific.

Antecedents of Innovation Initiation at the Individual LevelIndividual creativity. Although individual intelligence may affect in-novation initiation directly (Proposition 2), it also works through individualcreativity to generate ideas or perceive problems. Even though groups ororganizations may be creative (Amabile, 1988; Woodman et al., 1993), the

individual level is examined here for two reasons. First, although onecan describe the creativity of a collective, it always involves individuals.Amabile (1988:126)defined creativity as "the production of novel and usefulideas by an individual or small group of individuals working together," andWoodman and colleagues (1993: 293) defined organizational creativity as

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1098 Academy of Management Review October"the creation of a valuable, useful new product, service, idea, procedure,or process by individuals working together in a complex social system"(emphases added to both quotations). Second, because this work is explor-atory and directed toward theory building, a simple, parsimonious ap-proach was adopted.

Proposition 3: Individual creativity is an antecedent ofthe initiation of organizational innovation.Even though creativity is an antecedent of innovation, it is not a sufficientcondition. Enabling conditions that facilitate the development of organiza-tional innovation are also involved (see Figure 1).Enabling conditions. The availability of opportunities and the absenceof internal and external constraints affect the unfolding of the innovationprocess. At the individual level, internal constraints result from individu-als' "transient emotional and motivational states, such as depression orelation, learned helplessness or feelings of control, inability to concentrateor particular ability to concentrate," whereas external constraints stemfrom environmental conditions, "such as loud noises, frequent interrup-tions, insufficient illumination, inadequate resources for accomplishingthe task at hand, and so on" (Sternberg & Powell, 1988: 998).For organizations, Amabile and Gryskiewicz (1987) found, from theirinterviews with R&Dscientists, that lack of operational autonomy or lackof freedom over one's work or ideas inhibited creativity. Amabile (1988)also noted that truly creative performance is enhanced when extrinsicconstraints are not overwhelming. At the organizational level, any innova-tive change must overcome the constraints of organizational inertia andresistance. In general, situations in which constraints are absent andindividuals have autonomy and control seem to favor the expression ofintelligence and the generation of innovative ideas.Adequate resources, support, and appropriate incentives are also nec-essary for innovation. Reviewing educational and industrial studies, Mum-ford and Gustafson (1988: 37) concluded that "environments providing re-wards for or explicitly stating the need for creativity engender high levelsof creative activity." Amabile and Gryskiewicz (1987) found that sufficientresources, such as facilities, equipment, information, and funds, contrib-uted to the creativity of R&D scientists. Although these environmentalfactors encourage creativity, it is reasonable to expect that they wouldencourage the expression of intelligence as well; having adequate timeand information resources to understand the task environment as well asthe support to address problems would enable intelligent action. More-over, having the requisite power within social, cultural, or organizationalsettings to act on one's understanding would also be a vital condition ofintelligent action.

Proposition 4: The initiation, idea generation of organiza-tional innovation is dependent upon individual creativ-ity; creativity results in innovation under the following

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1996 Glynn 1099enabling conditions: when there is opportunity for cre-ative expression and an absence of constraints, whenthere are adequate resources and support to developideas, and when there are strong intrinsic incentives.

Antecedents of individual creativity. Individual creativity is drivenby individual intelligence, which is moderated by individual characteris-tics and the situational context (as shown in Figure 1). The rationale forpositing these interactive effects can be found in the conclusion Mumfordand Gustafson (1988: 28) reached from their extensive review of historical,experimental, and field research on creativity: "Creative behavior is likelyto be determined by a complex interaction between the attributes of theindividual and the attributes of the environment."Individual intelligence and creativity. Individual creativity has longbeen associated with intelligence, both conceptually (e.g., Gardner, 1993;Sternberg, 1985a) and empirically: "Studies of creative adult artists, scien-tists, mathematicians, and writers find them scoring very high on tests ofgeneral intelligence" (Barron & Harrington, 1981: 445). Based on his caseanalyses of seven creative individuals-Freud, Einstein, Picasso, Stravin-sky, Elliot, Graham, and Gandhi-Gardner (1993:363) concluded that "cre-ators differ from one another not only in terms of their dominant intelli-gence but also in terms of breadth and the combination of intelligences."Individuals of higher intelligence tend to outscore those of lower intel-ligence on measures of originality, preference for complexity, and concep-tual fluency and flexibility (Steiner, 1965). Amabile (1988: 140) noted thatcreativity is not necessarily related to the amount of task-domain (or de-clarative) knowledge that an individual possesses, but rather to the wayin which it is stored and accessed: For increased creativity, "It is notpossible to have too much knowledge; it is possible to have too manyalgorithms." Thus, in addition to relevant knowledge and expertise, acreative individual also will have flexible procedural knowledge.

Although research attests to a link between intelligence and creativ-ity, high levels of intelligence do not guarantee creativity. Nowhere is thismore evident than in Feldman's (1982) book, Whatever Happened to theQuiz Kids? For these children with very high IQs, "their creative perfor-mances in their later lives have nowhere near matched their intelligentperformances in their earlier lives" (Sternberg, 1988: 125).What, then, ac-counts for the strength (or weakness) in the intelligence-creativity link?In their analysis of published correlations between creativity andtraditional measures of intelligence (i.e., tests of general intelligence, gfactor, or IQ), Barron and Harrington (1981) found that overall correlationvalues ranged from nonsignificant to moderately positive; however, whenintelligence was measured by raters' judgments or respondents' percep-tions (instead of IQ-type measures), correlations were significant. Eventhough psychometric measures of general intelligence (IQ or g factor)failed to predict creativity (Barron & Harrington, 1981), they do predict

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1100 Academy of Management Review Octoberjob performance and career success in more established contexts (e.g.,Gottfredson, 1986;Hunter, 1986;O'Reilly & Chatman, 1994;Ree et al., 1995).Thus, it may not only be the measure of intelligence that is of concern,but it may be also the type of intelligence. Assessments of g factor or IQtend to tap primarily verbal and mathematical intelligence, rather thanother types of intelligence (Gardner, 1993). For intelligence to be relatedto creativity, the dominant intelligence (and its assessment) must relateto the task domain in which creativity occurs.

Proposition 5:Individual intelligence results in creativitywhen the dominant intelligence relates to the particulartask domain (declarative knowledge) and when there isflexibility in combining rules for accessing and storinginformation (procedural knowledge).Individual and situational context of creativity. Summarizing findingsfrom extant research, Amabile (1988: 142)formulated "TheIntrinsic Motiva-tion Principle of Creativity: People will be most creative when they feelmotivated primarily by the interest, enjoyment, satisfaction, and challengeof the work itself -and not by external pressures." Subsequent studies sheconducted with her colleagues using undergraduate and adult samples,measuring creativity both with pen-and-pencil assessments and expertratings, attested to the validity of this principle (Amabile, Hill, Hennes-

sey, & Tighe, 1994). Further support of the role of intrinsic motivation inlinking intelligence and creativity was provided by Glynn and Webster(1993), who found significant relationships among intrinsic motivation,cognitive playfulness, and innovation intentions for a sample of highlyintelligent adults.Woodman and colleagues (1993: 298) advocated a focus on creativitythat goes beyond an individually centered perspective but acknowledged"an appreciation for the creative person as a partial explanation for cre-ativity." Although researchers have debated whether creative individualshave an enduring constellation of attributes (e.g., openness to experience,intellectual curiosity, assertiveness, independence of judgment, spontane-ity), a longitudinal study of women's adult development supports the no-tion that individuals do have creative personalities and that these person-alities tend to endure over time. Helson, Roberts, and Agronick (1995)foundthat intelligence (measured as SAT verbal score), aspirations, and scoreson a creative temperament scale all contributed to the prediction of occu-pational creativity.Proposition 6:Individual intelligence results in creativitywhen individuals have high intrinsic motivation and apersonal orientation toward creativity.Noting that "situational variables have been all but totally ignoredin theories and testing of intelligence," Sternberg and Powell (1988: 997)suggested several variables that operate to affect the expression of intelli-gence, including absence of constraints, adequate resources and support,

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1996 Glynn 1101novelty (or unusualness) of circumstances, and expectations of intelligentaction. The first two (constraints and resources) are treated in this frame-work (see Figure 1) as enabling conditions that affect both creativity andinnovation; the remaining two situational variables are discussed in termsof their effects on the individual intelligence-creativity relationship.Individuals tend to perform better in familiar settings: "Recall of stimu-lus material tends to be best when it occurs in the same setting as thatin which the material was learned" (Sternberg & Powell, 1988:999). Simi-larly, in their review of the research, Alba and Hutchinson (1987:427) foundthat a person's ability to solve problems creatively was affected by thenovelty of the problem: "In situations in which a problem is familiar, priorexperience may lead to the direct retrieval of a prior solution-as in thecase of routinized problem solving. . . In situations in which the problemis new, expertise allows an individual to generate and evaluate potentialsolutions." When tasks are heuristic (as opposed to algorithmic, wheretask behavior is governed by fixed and specific rules), creativity is favored(Amabile, 1983). Thus, when circumstances are unfamiliar, unusual, ornovel, individuals may rely less on already learned behaviors and, in-stead, attempt to acquire new information or reprocess existing informa-tion in new ways that enable creativity.Consistent with the well-documented effects of self-fulfilling prophe-cies, it seems plausible that when intelligence is expected, valued, ordemanded, intelligent actions are more likely. Intelligence testing is al-most always done under maximal-performance demands: "One is encour-aged to put forth one's best effort, and the pressure to do so is clear andpresent" (Sternberg & Powell, 1988: 999). Amabile and Gryskiewicz (1987)found that organizational climate promoted creativity if innovation is val-ued, failures are tolerated, and a spirit of cooperation and collaborationexists.

Proposition 7:Individual intelligence results in creativitywhen the task, problem, or circumstances are novel, un-familiar, or heuristic and when an intelligent approachto problem solving is expected and valued.

Organizational Antecedents of Innovation Initiationand ImplementationPrevious discussion focused on the relationship of organizational in-novation to the stages of innovation (Propositions 1 and 2). In this section,the focus is on how organizational intelligence interacts with organiza-

tional and situational characteristics to affect innovation. The rationalefor this approach is found in the work of Mumford and Gustafson (1988:38). These authors stated that innovation is facilitated "by an environmentthat provides a cognitive basis for creative efforts through structures en-couraging the creation of systematic understandings and ongoing explora-tion of alternative points of view."

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1102 Academy of Management Review OctoberOrganizational and situational context. In her model of organizationalinnovation, Amabile (1988: 153) argued that organizations have a basic

orientation that motivates them to innovate (or not). Amabile (1988: 154)summarized the most important aspects of the informal arrangements: "avalue placed on innovation in general, an orientation toward risk (versusan orientation maintaining the status quo), a sense of pride in the organiza-tion's members and what they are capable of doing, and an offensivestrategy of taking the lead toward the future (versus a defensive strategy ofsimply wanting to protect the organization's past position)." Organizationsthat value diversity in perspectives, tolerate ambiguity, value innovation,and accept risk taking will tend to have a stronger orientation toward inno-vation.Organizations with a greater capacity for innovation tend to be or-ganic rather than mechanistic in structure (Burns &Stalker, 1995),integra-tive rather than segmentalist (Kanter, 1983),and they have lower formaliza-tion, more role ambiguity, multidisciplinary teams, and job rotation (Staw,1990). Organizational size, complexity, and formalization are consideredobstacles to innovation (Aiken &Hage, 1971;Burns & Stalker, 1995;Kanter,1983; Nadler & Tushman, 1989;Rogers, 1983). Several studies have demon-strated that flexible environments, broad job definitions, and job autonomyfor workers facilitate innovation (Amabile, 1988; Amabile & Gryskiewicz,1987; Andrews & Farris, 1967;Delbecq & Mills, 1985;Pelz &Andrews, 1966).After reviewing a number of studies on organizational climate, Mumfordand Gustafson (1988: 37) concluded that "innovative research-and-designsystems are characterized by the recognition and reward of superior per-formance, particularly with respect to the initial exploratory stages ofcreative endeavors." Leidner and Elam (1995)surveyed senior and middle-level managers who use expert information systems and found that the useof decision support technologies increased organizational intelligence.In general, then, organizations characterized by less bureaucracy; lessfunctional specialization; more fluid, flexible, and integrative structures;

increased worker autonomy; and good communication and informationflows are thought to be more innovative.Traditionally, the belief has been that organizational factors that favorthe initiation of innovation tend to inhibit their implementation and adop-tion; characteristics of the "innovating organization" are aligned withthose of the first stage but not the second stage. Marcus (1988: 235) ex-plained the reasoning:Rule-bound approaches, which involve central direction andhighly programmedtasks, are supposed to promoteimplemen-tation; that is, the number of routine tasks prescribed fromabove should increase as an organization moves toward imple-mentation. . . Conception, proposal generation, and initia-tion, on the otherhand, require fewer controls and moreauton-omy, because diversity, openness, informality,and the abilityto bring a variety of bases of information to bear on a problemneed to be encouraged.

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1996 Glynn 1103Work in the 1980s and 1990s suggests that those organizational struc-tures and characteristics that enable initiation also enable implementa-

tion; greater autonomy and managerial discretion generally facilitate im-plementation. In his study of how nuclear power plants implementedexternally induced safety review innovations, Marcus (1988) found thatpoor safety records were associated with a rule-bound approach to imple-mentation, whereas better safety records were associated with an ap-proach that allowed managers greater autonomy. One reason for thisrelationship between degree of implementation autonomy and innovationsuccess is related to intelligence: "Implementators are likely to havegreater knowledge at the point of delivery, where there are multiple andcontradictory demands . . . [Efforts to centralize authority] may encouragelow system comprehension. . . . Autonomy is needed to encourage highlevels of commitment and knowledge" (Marcus, 1988: 251).Finally, organizational capacities for learning influence organiza-tional innovation. According to conceptual (e.g., Stata, 1989; Tushman &Nadler, 1986), empirical (e.g., Cohen &Levinthal, 1990;Henderson & Clark,1990), and simulation research (e.g., Mezias & Glynn, 1993), an organiza-tion's ability to learn from its own history and experiences affected itscapabilities for renewal and change. By extension, then, intelligence canunderlie effective learning to enhance organizational innovation. Takinginto account this set of organizational and situational factors leads tothe following:

Proposition 8: Organizational intelligence results in in-novation under conditions of high organizational orien-tation to innovation and when situational factors favorthe expression of organizational intelligence, that is,when constraints are absent; the circumstances, prob-lems, or tasks are novel, unfamiliar, or heuristic; ade-quate support and resources are available; an intelligentapproach is expected and valued; and an organizationhas a high capacity for effective learning.

IMPLICATIONS FOR THEORY, RESEARCH,AND MANAGERIALPRACTICEImplications for Theory and Research

In this article, I developed the construct of organizational intelligenceas a social outcome that related to individuals' intelligence by means ofaggregation, cross-level, or distributed effects. Thus, understanding andassessing individual intelligence is important to understanding organ-izational intelligence. I discussed how individuals' intelligence can becharacterized according to interindividual differences in level or type ofintelligence. An extension of this idea is to characterize organizationalintelligence according to the homogeneity or heterogeneity of its members'

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1104 Academy of Management Review Octoberintelligence with regard to these two dimensions of intelligence. Fieldresearch might be conducted to describe organizational intelligence interms of members' homogeneity of intelligence levels or types, examiningdifferences by members' functional division, hierarchical position, or orga-nizational tenure. More or less innovative business units or firms may becompared for their differences in members' intelligence, and for theirdegree of heterogeneity. An alternative research strategy is to use com-puter simulations to assess the effects that variance, heterogeneity, orcomposition of individual members' intelligence have on organizationalinnovation. The simulation methodology could model how organizationalinnovation unfolds over time and how heterogeneity in level or type ofindividual intelligences affects the process. Such a model might buildupon March's (1991) simulation of mutual learning between members ofan organization and an organizational code; such research holds promisefor researchers' examination of the relationships between microlevels andmacrolevels of intelligence.This article focused on intelligence as purposeful, adaptive informa-tion processing that was functionally similar but not equivalent for individ-uals and organizations. In the future, researchers might investigate theconditions under which organizational intelligence may differ more orless markedly from individuals' intelligence. Such an investigation wouldrequire a specification of the general laws that govern the developmentand expression of intelligence; this is a process of "microtranslation"(DiMaggio, 1991: 77). Although (perhaps) information-processing aspectsof intelligence are functionally similar across levels of analysis (Huber,1991: 89), other aspects of intelligence may not be so correspondinglysimilar. Two such aspects of intelligence that may differ across levelsof analysis are considered next: (a) differences in the way intelligencedevelops and (b) differences in the relationship between the social orcultural context and organizational intelligence.Organizational intelligence may develop at different rates in responseto different kinds of experiences (e.g., success versus failure or threatversus opportunity). If intelligence involves the development of rules thatare environmentally isomorphic (Sandelands & Stablein, 1987) or ecologi-cally valid (Siegler & Richards, 1988), these rules will change in responseto differences in context or experience. Further, one might expect that therate of rule development proceeds more rapidly for organizations thanfor individuals, given the greater information-processing capacity of acollective. Alternatively, one might hypothesize that an institutionalizedsystem would be more inert and reliant on previously learned rules be-cause of group pressures to conformity, particularly in the absence ofdissenting minority opinions (e.g., Laughlin, 1988; Nemeth, 1986). Addi-tional modification of this basic idea might include a consideration oforganizational size and its effects on the development of intelligence.Specifically, are there limits to intelligence as the size of a group increasesand problems of information communication, coordination, interpretation,

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1996 Glynn 1105and integration multiply? In this article, I focused on the intelligence ofindividuals and organizations; understanding how intelligence developsand unfolds in small groups or teams is an important agenda for future re-search.Differences in the relationship between intelligence and context mightbe different across levels of analysis. For organizations, this notion impliesthe consideration of different levels or types of intelligence across differenttypes of organizations. To map the existence and dominance of differenttypes of intelligence, Sternberg's (1985b) three-part framework on intelli-gence (consisting of analytical, creative, and contextual components)could be used in different organizational contexts, structures, and cultures.One might speculate that more organic types of organizational structures,because of their flexible and innovative capabilities (Burns & Stalker,1995), would be associated with more creative aspects of intelligence.Conversely, mechanistic organizations, with their emphasis on bureau-cratic, functional specialization might place a premium upon analytical(or IQ-type) intelligence. Further, the intelligence of executive leadershipalso could be analyzed for organizational and industry differences. Stern-berg (Trotter, 1986: 60) suggested that Lee Iacocca has a high level ofcontextual intelligence or "street smarts." An interesting question iswhether his type of intelligence extends to other executives at Fortune100 firms or auto manufacturing firms.The conceptual framework proposed herein focused on radical innova-tion because it made more cognitive demands; future researchers mightinvestigate the effects of intelligence on more incremental innovation.Mezias and Glynn (1993) demonstrated that different types of organiza-tional strategies often yield unintended consequences; strategies intendedto increase innovation often resulted in more incremental innovation thanradical innovation. In linking type of intelligence to type of innovation,one might postulate that analytical intelligence (typically assessed bystandardized psychometric instruments like IQ tests) may rely heavily onlearned and programmed information structures and rules that may beeasily accessed but not so easily manipulated in the service of innovationthat is radical or "frame breaking" (Tushman et al., 1986).Correspondingly,one might compare the role that intelligence plays in fostering technologi-cal versus nontechnological innovations.The proposed model relates intelligence to organizational innovation,which is broadly construed as a two-stage process: (a) initiation and ideageneration and (b) implementation and adoption. More fine-grained ap-proaches to the constructs of intelligence and innovation represent prom-ising areas for future conceptual and empirical research. For instance,researchers might investigate the relationship of intelligence to subcate-gories of initiation and implementation.Future work might be directed toward understanding intelligence interms of other cognitive organizational processes and placing it withinthe nomological web that constitutes organizational cognition. Related

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1106 Academy of Management Review Octoberconstructs include organizational learning and memory; processes relatedto the development and persistence of organizational routines, rituals,and symbols; and organizational adaptation and change. In many of theseconcepts, organizational intelligence seems to be an implied but under-specified variable. Many organizational learning theorists contend thatalthough learning may lead to change, it does not necessarily ensureorganizational adaptation (Glynn et al., 1994).Intelligence makes experi-ence understandable, which aids the development of domain knowledgeand the construction of ecologically valid rules that are effective in dealingwith environmental demands. Thus, intelligence is implicitly at the coreof the learning organization (Senge, 1990); it is what enables a firm tolearn from its own experience and the experience of other firms. Distributedviews of intelligence draw attention to the intelligence embedded in insti-tutionalized patterns of structure and symbols. An interesting researchagenda might develop from an examination of organizational routinesand artifacts to determine what they reveal about the intelligence of thatsystem. As in the oft-cited example of the large and varied Eskimo vocabu-lary for snow (e.g., Whorf, 1956), so too might the analysis of the structureand content of organizational acronyms, metaphor, or slang reveal theintelligence underlying the coded content and codification processes oflanguage.Implications for Managerial Practice

This article points to the vital role of an organization's intellectualresources and the importance of managing intellectual capital. Organiza-tional innovation is impossible in the absence of creative geniuses, whoinitiate innovative processes, and intelligent organizational systems thatrecognize and support viable innovation. Dominant intelligence needsto fit task demands; this notion suggests that the placement function isimportant in fitting individuals who have appropriate levels and typesof intelligence with jobs that require this intelligence. Even though anaccountant may have the mathematical intelligence to perform well infinancial matters, he or she may lack the social intelligence needed for asales position. Thus, managers should place employees in jobs that fittheir cognitive skills and abilities.In addition to individual characteristics, managers also must attendto situational factors that enable the expression of intelligence and moti-vate its application to creative solutions and innovative organizationalendeavors. Such environments are characterized by an absence of con-straints, novelty of tasks, adequate resources and support, and expecta-tions of intelligent action. Even though this article followed previous re-search (e.g., Amabile, 1988) in proposing that intrinsic motivation wasnecessary for creativity and innovation, it is also likely that extrinsicmotivation plays a role in the process. This seems plausible at the laterstage of innovation when individuals take creative, inventive ideas andapply them to organizational needs and problems. As innovation moves

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1996 Glynn 1107out of the idea stage into the implementation stage, extrinsic incentiveswill probably be more important. If managers are able to influence motiva-tional and situational factors, they will be better able to foster intelligentinnovation. Managers also need to adopt a strong business orientationtoward innovation and embed this orientation in their organization's op-erating systems and cultural values. Because much of an organization'sinnovation orientation lies within its visionary leadership (Amabile, 1988),managers are well poised to be exemplary role models and to personifythe innovative genius.

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Mary Ann Glynn is an associate professor at the Goizueta Business School, EmoryUniversity. She received her Ph.D. from Columbia University's Graduate School ofBusiness. Her research has focused on understanding cognition and cognitive pro-cesses in organizations and exploring their relationship to innovation and creativity,learning, organizational identity, and members' identification with organizations.