Learning Agility: In Search of Conceptual Clarity and ... · the recognition of when new skills or ... Review and Constructive Critique ... deﬁned as ‘‘the willingness and ability

Industrial and Organizational Psychology, 5 (2012), 258–279.Copyright © 2012 Society for Industrial and Organizational Psychology. 1754-9426/12

FOCAL ARTICLE

Learning Agility: In Searchof Conceptual Clarity and TheoreticalGrounding

D. SCOTT DERUE, SUSAN J. ASHFORD, AND CHRISTOPHER G. MYERSUniversity of Michigan

AbstractAs organizations become more complex and dynamic, individuals’ ability to learn from experience becomesmore important. Recently, the concept of learning agility has attracted considerable attention from humanresource professionals and consultants interested in selecting on and developing employees’ ability to learn fromexperience. However, the academic community has been largely absent from this discussion of learning agility,and the concept remains ill defined and poorly measured. This article presents a constructive critique of theexisting literature on learning agility, seeks to clarify the definition and conceptualization of the construct, andsituates learning agility within a broader nomological network of related constructs. We conclude by discussingseveral important directions for future research on learning agility.

Experience can be a masterful teacher. Evenancient scholars such as Aristotle noted howvirtue, morality, and courage are learnedthrough habit and practice (Ostwald, 1962).Education theories portray young childrenand adults as active learners who developthrough lived experience (Dewey, 1916;Lewin, 1951; Piaget, 1952). In organi-zational studies, the lessons of experi-ence are emphasized in domains suchas employee training (Noe, 2002), lead-ership development (McCall, Lombardo, &Morrison, 1988), team learning and adapta-tion (Edmondson, Bohmer, & Pisano, 2001),and organizational learning (March, 1991).Certainly, the lessons of experience are acentral component of individual, group, andorganization learning, growth, and devel-opment. Yet, experience is a funny thing.In any given experience, some people learn

Correspondence concerning this article should beaddressed to D. Scott DeRue.E-mail: [email protected]

Address: Stephen M. Ross School of Business,University of Michigan, 701 Tappan Street, Ann Arbor,MI 48109

valuable lessons. Other people, in that sameexperience, learn nothing or even the wronglessons. It is the ability to learn from experi-ence that enables some people but not oth-ers to excel in contemporary organizationswhere change and dynamism are the newnormal and learning is an emerging sourceof competitive advantage (Garvin, Edmond-son, & Gino, 2008; Spreitzer, McCall, &Mahoney, 1997).

The ability to learn from experiencereflects a person’s ability to master thechanging demands of his or her job (Kolb,1976) and involves a broad array ofindividual differences and characteristics(Spreitzer et al., 1997; Van Velsor, Mox-ley, & Bunker, 2004). In particular, anindividual’s ability to learn comprises adiverse set of attributes and competen-cies, including but not limited to individ-uals’ intelligence (Hunter, 1986; Hunter& Schmidt, 1996), personality attributessuch as Openness to Experience (LePine,Colquitt, & Erez, 2000), motivation to learnand seek out developmental opportunities(Birdi, Allan, & Warr, 1997; Colquitt &

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Learning agility 259

Simmering, 1998; Spreitzer et al., 1997),the recognition of when new skills orbehaviors are required (Van Velsor et al.,2004), and resilience in the face of adversityor unexpected events (Weick & Sutcliffe,2007). In this sense, ‘‘ability to learn’’ isa metaconcept reflecting a constellation ofindividual characteristics and attributes thatenable people to develop or refine their job-related knowledge and skills in response tochanging job demands and in service ofimproving their performance over time.

Seeking to extend our understanding ofindividuals’ ability to learn from experience,scholars and practitioners recently intro-duced a concept called learning agility,which to date has referred to a person’sability and willingness to learn from expe-rience and apply the lessons of experi-ence to improve future performance (DeMeuse, Guangrong, & Hallenbeck, 2010;Eichinger & Lombardo, 2004; Lombardo &Eichinger, 2000). Although learning agilitygoes beyond ability by emphasizing theimportance of individuals’ willingness tolearn and ability to implement the lessonsof experience, the concept has largely beentreated as synonymous with the abilityto learn. This conceptual overlap raisestwo important concerns. First, it is unclearwhether learning agility is a unique con-cept or simply a repackaging of old wine ina new bottle. Existing research on learningagility does not carefully differentiate, eithertheoretically or empirically, the agility con-cept from a general ability to learn. As aresult, learning agility is becoming a ‘‘catch-all’’ phrase referring to most everythingrelated to learning from experience, andto the extent that we allow learning agilityto become everything, it becomes noth-ing. Second, by equating learning agilitywith a person’s general ability to learn, wepotentially overlook the value in consider-ing agility as a unique component of theexperiential learning process. In this article,we develop a narrower conceptualizationof learning agility that is more faithful to thetraditional meaning of agility, focusing onthe speed with which people learn and theflexibility people exhibit in learning both

within and across situations. By refocusinglearning agility on speed and flexibility, weaddress an important theoretical gap in ourunderstanding of the experiential learningprocess—that is, explaining why some peo-ple learn faster and are more flexible in theirlearning than others. In this sense, learningagility is not equivalent to one’s ability tolearn but rather is one component of theability to learn. We expect that narrow-ing the conceptualization of learning agilitywill actually enhance the contribution thatlearning agility can make to our collectiveunderstanding of how people learn fromexperience.

With this in mind, our goals for the cur-rent article are threefold. First, we proposea narrower definition of learning agility anddevelop a conceptual framework for theconcept that situates it within the broaderdomain of research on learning from experi-ence. To accomplish this goal, we begin byreviewing the existing literature on learningagility and offering a constructive critiqueof prior research. We then leverage the lim-itations of existing research as a launchingpoint for developing a more precise andnarrower definition of learning agility. Sec-ond, we clarify the personal attributes thatwould be associated with learning agility,as well as the cognitive and behavioralprocesses that serve as manifestations oflearning agility and enhance the degreeto which people engage in agile learning.Third, we conclude by identifying oppor-tunities for future theory development andempirical research, measure the develop-ment related to learning agility, and explainhow this research on learning agility couldextend our collective understanding of howpeople learn from experience.

Learning Agility: A LiteratureReview and Constructive Critique

In Lombardo and Eichinger’s (2000) workon identifying high-potential talent inorganizations, they posited that managerialroles are becoming more complex, global,and marked by extreme paradox—and asa result, individuals moving into these roles

260 D.S. DeRue, S.J. Ashford, and C.G. Myers

need to be flexible, adaptable, and able tolearn from experience. Accordingly, theyargued that executive potential is a functionof one’s ability to learn from experience,and the selection of leadership talent shouldaccount for people’s ability to learn andadapt to the demands of new roles notsimply performance in a prior role. Tocapture this ability to learn from experience,Lombardo and Eichinger introduced theconcept of learning agility, which theydefined as ‘‘the willingness and abilityto learn new competencies in order toperform under first-time, tough, or differentconditions’’ (p. 323).

This seminal article spawned research onthe conceptual development and measure-ment of learning agility. We review herethe conceptual insights and return later toquestions of measurement precision andvalidity. Learning agility was conceptual-ized according to four dimensions (Lom-bardo & Eichinger, 2000, p. 324):

People agility: ‘‘people who knowthemselves well, learn from experience,treat others constructively, and are cooland resilient under the pressures ofchange.’’Results agility: ‘‘people who get resultsunder tough conditions, inspire othersto perform beyond normal, and exhibitthe sort of presence that builds confi-dence in others.’’Mental agility: ‘‘people who thinkthrough problems from a fresh pointof view and are comfortable withcomplexity, ambiguity, and explainingtheir thinking to others.’’Change agility: ‘‘people who are curi-ous, have a passion for ideas, like toexperiment with test cases, and engagein skill-building activities.’’

In their original study, based on a sampleof over 200 managers, Lombardo andEichinger (2000) concluded that learningagility predicted the degree to whichindividuals performed well in their currentrole and had the potential to be promotedto their next role. From these data, they

advocated using learning agility to selecttalent for key developmental assignments,to identify high-potential talent that mightnot be in visible roles, and to helppeople become more open to other pointsof view so they learn more from theirdevelopmental experiences.

Connolly and Viswesvaran (2002) andEichinger and Lombardo (2004) subse-quently investigated the discriminant valid-ity of learning agility relative to otherindividual differences such as personalityand intelligence, as well as the predictivevalidity of learning agility in explaining vari-ation in promotions and performance afterpromotion. With data collected from 313employees in three firms (two in insuranceand one in electronics), as well as 107law enforcement officers, they found evi-dence for discriminant validity in resultsshowing that learning agility is unrelated tointelligence, goal orientation, and person-ality (with one exception being a positiverelationship with Openness to Experience).In terms of predictive validity, learningagility was found to be unrelated to whethersomeone was promoted, which the authorsposited was because promotions are morea function of prior performance, politics,or poor choice as opposed to one’s abil-ity to learn from experience. In terms ofperformance after promotion, the evidencewas mixed. Learning agility related to per-formance after promotion when learningagility, and likely performance (the articlewas unclear about the source of the perfor-mance rating), were rated by one’s super-visor (r = .45). There was no relationshipbetween learning agility and performanceafter promotion when learning agility wasassessed via one’s peers.

Finally, similar to Eichinger, Lombardo,and colleagues, McKenna, Boyd, and Yost(2007) examined learning agility by explor-ing both the situational and personal factorsthat influence individuals’ learning fromexperiences. On the basis of 100 inter-views with pastors, the authors concludedthat one’s ability to learn from experi-ence—which they refer to as learningagility—is enhanced by situational factors


such as access to role models, exposure tonovel experiences that involve change andcomplexity, and opportunities for reflec-tion. In addition, an individuals’ ability tolearn from these challenging experienceswas a function of personal strategies suchas adopting a learning focus, being willingto admit one’s own mistakes, and relying onpersonal values and faith to get through dif-ficult and challenging times. These resultsgenerally reinforce prior findings relatedto what enables individuals to learn anddevelop from developmentally challengingexperiences (e.g., McCall et al., 1988).

Although we fully support the emphasison learning from experience and areencouraged by the results presented in thecurrent literature, we have several concernsabout how learning agility is being definedand conceptualized, as well as concernsabout the validity of the conclusions beingdrawn from prior research. First, learningagility has come to be used as a catch-all phrase referring to anything related tolearning from experience and individuals’ability to learn from experience. On thebasis of the current research, it is unclearwhy one would use the term learning‘‘agility’’ as opposed to learning ‘‘ability.’’What is the significance of ‘‘agility,’’ andhow does learning ‘‘agility’’ extend or addto our understanding of learning ability,which has been the topic of decadesof scientific research (Cronbach & Snow,1969; Derry & Murphy, 1986; Kolb, 1984)?Our fear is that the concept began with anambiguous definition, and as the literaturehas evolved, the definition has becomeeven more ambiguous and unclear.

Second, the current literature presentslearning agility as a multidimensional con-struct. Yet, it is unclear how these dimen-sions relate. In addition, some of thesedimensions go beyond one’s agility in learn-ing and even beyond one’s ability to learnfrom experience, and they frequently con-found learning with performance and suc-cess. For example, De Meuse et al. (2010)define learning agility as the ‘‘willingnessand ability to learn from experience, andsubsequently apply that learning to perform

successfully under new or first-time condi-tions’’ (p. 120). Embedded in this definitionis an assumption of successful performance,thus defining the concept of learning agilityin part by its outcome. The potential con-tribution of a learning agility concept is tofurther our understanding of how peoplelearn from experience in ways that enablemore effective performance. To realize thispotential, we need to keep the concept oflearning agility distinct from performanceitself. The four dimensions of learning agilityposited by Lombardo and Eichinger (2000)also seem to differ in terms of how relatedthey are to learning from experience. Forexample, the people agility dimension refersspecifically to the process of learning fromexperience, and the change agility dimen-sion refers to learning behaviors such asexperimentation and skill building. In con-trast, the results agility dimension refersto aspects of performance such as gettingresults and inspiring others.

Finally, researchers tout the predictivevalidity of learning agility, a questionableclaim given the lack of rigorous empiri-cal testing of the concept and underlyingtheory. For example, Eichinger and Lom-bardo (2004) concluded that learning agilityis related to performance after promotion,but this relationship only holds for boss-rated learning agility (not peer-rated learn-ing agility). Although it is not reported in thearticle, it is likely that this finding is at leastin part a product of common source bias(Podsakoff, MacKenzie, Lee, & Podsakoff,2003), where an individual’s boss providedassessments of both learning agility andperformance after promotion. Moreover,although learning agility is expected to pre-dict learning from experiences over time, allthe prior research has provided only cross-sectional reports of the relationship betweenlearning agility and performance. Thus, it isnot clear that learning agility is actuallythe causal mechanism driving improvedperformance or that any learning fromexperience is even occurring. The exist-ing literature is plagued by research designsthat produce inconclusive and ambiguousresults.


In summary, the learning agility conceptlacks conceptual clarity, and the exist-ing empirical research offers ambiguousinsights related to its construct and predic-tive validity. This is particularly problematicas selecting individuals based on their abil-ity to learn—as well as being able todevelop a learning ability in people—isparticularly important in the dynamic andcomplex world that we live in today. AsJohn R. Ryan (2009), the president andCEO of The Center for Creative Leader-ship, noted, ‘‘To succeed in a world whereour work is always changing, where chal-lenges are unpredictable and competitionabounds, we need to be agile learners’’(p. 7). To the extent that learning agility isone part of a person’s ability to learn, it is animportant concept worthy of investigation.Herein, we develop a more precise and nar-rower conceptualization of learning agilityand develop a framework for understandinghow learning agility relates to but is distinctfrom other constructs associated with learn-ing from experience. On the basis of thisrevised definition and conceptualization,we then go on to identify opportunities forfuture research and measure developmentrelated to learning agility.

Defining and ConceptualizingLearning Agility

Learning is the process of improvingactions through better knowledge andunderstanding (Fiol & Lyles, 1985), anddespite a wealth of research on thetypes of experiences that promote learning(McCall et al., 1988; McCauley, Ruderman,Ohlott, & Morrow, 1994) and the personalattributes and organizational factors thatsupport learning (DeRue & Wellman, 2009;Dragoni, Tesluk, Russell, & Oh, 2009),several important gaps remain in ourunderstanding of the experiential learningprocess. In particular, the current literatureoffers little insight into the rate of learningor specifically why some people go throughthe experiential learning process faster thanothers. Likewise, prior research has yet toexplain why some people are more flexible

with their understanding of a particularsituation, are able to shift among ideasand points of view more fluidly, andare ultimately able to make connectionsacross ideas and situations more easily thanother people. We posit that the conceptof learning agility will be most applicableand have the most theoretical value whenthinking specifically about issues relatedto speed and flexibility in the experientiallearning process.

The term ‘‘agility’’ has traditionallyreferred to ‘‘the power of moving quicklyand easily; nimbleness’’ and ‘‘the abilityto think and draw conclusions quickly;intellectual acuity’’ (American HeritageDictionary of the English Language, 2000).Extending the traditional meaning of theterm to experiential learning, learningagility foregrounds both the speed oflearning (i.e., an ability to pick things upquickly) and the ease of movement acrossideas (i.e., moving among various ideas orpoints of view and across situations). Inthis sense, learning agility references theimportance of developing ‘‘different, moreappropriate and possibly counterintuitiveways of doing things’’ (LePine et al., 2000,p. 570). It also captures a person’s ability tolearn quickly within a particular experienceand to be flexible in moving across ideasand understandings such that the personis able to maximize the potential learningvalue of a given experience. Learningfrom experience requires identifying andcomprehending different patterns withinand across experiences (Matlin, 2002). Theterm ‘‘agility’’ implies that a person cansee patterns quickly and is able to easilymove between different interpretations ordescriptions of those patterns. Implicit inthis description of flexibility as movingeasily from one idea to another is theability to hold multiple, conflicting ideasin one’s head simultaneously, which F.Scott Fitzgerald (1936) long ago labeledthe ‘‘test of a first rate intelligence.’’ Takentogether, we define learning agility as theability to come up to speed quickly inone’s understanding of a situation and moveacross ideas flexibly in service of learning


both within and across experiences. Fromthis perspective, learning agility comprisesboth processing and perceptual speed(Kyllonen & Christal, 1990), as well asflexible cognition (Deak, 2004).

It is important to recognize that the pro-cess of learning from experience occursover time, such that people develop anunderstanding of a particular experienceand then draw connections between thelessons of that experience and future experi-ences. As such, the learning agility conceptapplies both within an experience (e.g.,coming up to speed quickly and think-ing flexibly about the current experience)and across experiences. For example, anagile learner not only quickly recognizesimportant patterns in a situation but is alsoable to quickly and flexibly see connectionsbetween experiences.

As just one example of cross-situationallearning agility, imagine the manager whocan both carry over appropriate lessonsfrom experience and not get overly investedin (and thus carry over) inappropriate orincorrect lessons. Examples might includethe expatriate from one country who ismoving to a different country, a managerwith experience in one population whonow must manage a different population,or a manager with experience in onefunctional area who is now moving to adifferent function. Less agile learners notonly get caught up in and defensive abouttheir point of view within a particularexperience but also rigidly carry overspecific conclusions and lessons to newexperiences. Those higher in learning agilityare not only able to get up to speed quicklyin a particular experience, but they are alsoable to drop inappropriate lessons learnedas they travel across experiences. Thus,agility is not only about picking up newknowledge quickly and flexibly moving onto different conclusions when warranted, italso involves not getting stuck in a particularpoint of view and being able to transferlessons appropriately to new situations andexperiences.

Leavitt and March (1988) capturedthe temporal aspect of learning within

organizations when they stated that learningis about encoding ‘‘inferences from historyinto routines that guide behavior’’ (p. 319).In this way, learning agility is as muchabout unlearning as it is learning. Yet,the unlearning aspect of learning agility isnot straightforward or simple (see Weick,1993, 1996). Classic work on commitmentby Kiesler (1971) and Salancik (1977)suggests that people become committed tocertain courses of action that then becomedifficult to abandon. As an example, themore public the action and the moreconcerned people are about what variouspublics think of their actions, the moreactors stay committed to the original courseof action. Such behavioral commitmentmakes it difficult to remain flexible withinand across situations. In addition, whatwe know about schematic informationprocessing suggests that the lessons onetakes from one setting to another canserve as an expectation that may colorinformation processing in the new setting(e.g., confirmation bias; Nickerson, 1998).People are more likely to see informationthat supports their expectation in the newsetting, thereby making change, unlearning,or relearning less likely.

Our conceptualization of learning agilityis both narrower and broader than thoseoffered in prior literature. As describedabove, learning agility has been definedpreviously as ‘‘the willingness and abilityto learn new competencies in order toperform under first time, tough, or differentconditions’’ (Lombardo & Eichinger, 2000,p. 323). De Meuse et al. (2010) add theword ‘‘successfully’’ following ‘‘perform’’in their definition. These definitions areproblematic in that they confound agilitywith either its antecedents or outcomes.For example, the Lombardo and Eichingerdefinition incorporates into the construct oflearning agility the motivation to engagein agile learning—specifically, it includesa ‘‘willingness’’ to be agile as part of thedefinition of learning agility. In accordancewith tenets of good construct development(Schwab, 1980), our proposed definitionexplicitly separates a person’s willingness


to do the things that represent agility fromthe definition of what it means to be an agilelearner. Agility is about an ability to learnfrom experiences through being flexibleand fast. One’s willingness to engage inagile learning is a different issue that mightbe predicted by a range of other personaland situational factors beyond those thatexplain one’s ability to be fast and flexiblein learning from experience. As mentionedearlier, the De Meuse et al. definition isproblematic as it brings a success dimensioninto the definition of learning agility itself,suggesting that agility is in part defined byits creation of successful performance. Bytheir definition, a person cannot be agileand fail under new or first-time conditions.As Schwab’s treatment of construct validitysuggests, there is value in keeping theability to be agile and its possible effectson subsequent performance separate in thedefinition of the construct itself.

In addition, the Lombardo and Eichinger(2000) definition delimits the applicationof what is learned from experience andthe contexts within which that learning isvaluable (i.e., learning agility is relevantfor performing in first-time, tough, ordifferent conditions). Although learningfrom experience is generally in service ofbuilding capabilities that can be appliedto future experiences, it is probably bestto stop the definition there and not limitthe relevant application to certain types ofsubsequent experiences. Although learningagility may be especially useful whena person faces subsequent experiencesthat are novel or tough, these are notthe only types of experiences whereagile learning could be valuable. Thus,defining learning agility independent ofany particular experience type allowsresearchers to explore a wide range ofexperience types that might accentuate (orattenuate) the value of learning agility.

There are two final definitional issuesworth mentioning. First, there is a tradeoffin the two dimensions of learning agility.Notably, being flexible in moving acrossideas and points of view and being able toembrace simultaneously conflicting points

of view will likely reduce the speed atwhich people can learn from experienceand incorporate new lessons into theirbehaviors and routines. It takes time to con-sider and reconcile differing ideas and todetermine the best course of action amongalternatives. Similarly, an intention or per-sonal style of moving quickly may makeone less willing or able to be flexible,as we have described it. This notion oflearning agility as containing a paradox fitswell with views of leadership as embodyingparadoxical elements that must be simul-taneously satisfied (Denison, Hooijberg, &Quinn, 1995). Second, learning agility isonly one component of the ability to learnfrom experience. It is not synonymous withthat ability. With this narrower conceptualfocus, learning agility has great promisein helping us identify those who can beagile in learning from experience as well astrain employees to engage in experiencesof various types to maximize their learningand development. For example, in the con-text of cross-cultural management, Caligiuriand Tarique (2009) note the importance ofdeveloping what they call ‘‘cultural agility,’’which similarly captures the ability to movequickly (in their case from one culture toanother).

Learning Agility: An OrganizingFramework

Figure 1 situates learning agility into abroader framework of constructs related tolearning from experience, with a particularemphasis on the cognitive and behavioralprocesses through which learning agility ismanifested and enhanced. Indeed, as DeMeuse et al. (2010) note in their review oflearning agility, there are several constructsthat are different but conceptually related tolearning agility, although they identify onlylearning goal orientation and leadershipagility as particularly relevant. In develop-ing the nomological network (Cronbach &Meehl, 1955) for learning agility, we extendthe work of De Meuse and colleaguesby examining a broader set of relatedconstructs, including individual differences


L

IndividualDifferences Relatedto Learning Agility

(exemplars)

Cognitive ProcessesCognitive simulations

Behavioral Processes• Feedback seeking

GoalOrientation

Cognitive Positive•

• Counterfactual thinking

• Pattern recognition

•

• Experimentation

• Reflection

Processes Underlying Learning AgilityOpenness toExperience

Learning In &Across Situations

PositivePerformance

Change Over Time

• Experience characteristics

− Developmental challenge

− Complexity

• Culture and climate for learning

− Psychological safety

− Focus on “being right”

L i A ilitearning Agility• Speed• Flexibility

Contextual & Environmental Factors(exemplars)

(Meta)Cognitive

Ability

Figure 1. A model of learning agility.

that promote learning agility, cognitiveand behavioral processes that underlie andenhance agile learning, and context factorsthat influence the emergence and effectsof learning agility. Figure 1 also depictsthe idea that learning agility will promotelearning within and across situations and,through that learning, positive performancechange over time. Although certainly notexhaustive, Figure 1 illustrates how learn-ing agility fits within a broader network ofresearch on how individuals learn quicklyand flexibly from their experiences.

Individual Differences Related to LearningAgility

Although learning agility is unique in itsfocus on speed and flexibility, the con-cept does have similarities and connectionswith other constructs related to experientiallearning. Identifying the conceptual con-nections among constructs provides insightinto the basic meaning of learning agilityand helps clarify its boundaries and valuein the broader literature (Messick, 1975). Inthe following sections, we describe howlearning agility is related to three indi-vidual differences that are fundamentalto understanding an individual’s ability tolearn from experience: an individual’s goal

orientation, cognitive ability, and Opennessto Experience.

Goal orientation. Goal orientation refer-ences individuals’ propensity to pursuegoals related to learning and mastery (learn-ing orientation) or performance and rewards(performance orientation; e.g., Dweck,1986; Kanfer, 1990). Goal orientation hasbeen shown to affect learning and adap-tation generally (e.g., Farr, Hofmann, &Ringenbach, 1993), and it also influencesindividuals’ feedback-seeking behavior(VandeWalle & Cummings, 1997; Vande-Walle, Ganesan, Challagalla, & Brown,2000), leadership development (DeRue &Wellman, 2009; Dragoni et al., 2009), andperformance adaptability (DeShon & Gille-spie, 2005; Kozlowski et al., 2001). Relatedwork on learning versus performance goals(Seijts & Latham, 2001, 2005) suggests thatthe assignment of a performance goal actu-ally detracts from learning by making somepeople so anxious about performing at ahigh level that they unsystematically scram-ble to discover appropriate task-relevantstrategies, and in doing so, ‘‘they fail tolearn in a timely fashion the most efficientways to accelerate their effectiveness’’ (Sei-jts & Latham, 2005, p. 126). The conclusionof this stream of research is that having


a learning goal orientation is associatedwith greater motivation to learn (Colquitt& Simmering, 1998), improved perfor-mance after receiving feedback (Vande-Walle, Cron, & Slocum, 2001), and a greatercapacity to learn from challenging devel-opmental experiences (DeRue & Wellman,2009; Dragoni et al., 2009), all suggestingan important relationship between learn-ing goal orientation and learning agility.Indeed, De Meuse et al. (2010) identifiedlearning goal orientation as a key constructrelated to learning agility, although theirempirical results showed no relationshipbetween the two constructs. It is unclearwhether these results are because learningorientation is unrelated to learning agilityor because the measures used to assesslearning agility were imprecise in assessingthe speed and flexibility dimensions that wehave emphasized here. We expect learning-orientated individuals will be less commit-ted to a single point of view, thus enhancingindividuals’ flexibility in the learning pro-cess. Also, because learning-oriented indi-viduals are particularly attentive to possiblelearning opportunities, it is possible thata learning orientation could be associatedwith greater speed in the learning processas well.

More recently, scholars also haveemphasized the possible positive impactof performance goal orientation in learn-ing contexts, with a particular emphasison the extent to which people seek toprove their performance capability to oth-ers (a performance-prove orientation) and toavoiding mistakes (a performance-avoid ori-entation; Button, Matheiu, & Zajac, 1996;DeShon & Gillespie, 2005; VandeWalleet al., 2001). Although a performance ori-entation is often assumed to have a negativeimpact on learning (Ford, Smith, Weissbein,Gully, & Salas, 1998; Payne, Youngcourt, &Beaubien, 2007), it is possible that a combi-nation of a strong learning goal orientationand a strong performance-prove goal ori-entation might best enable individuals tolearn from experience and then use thoselessons to improve their performance overtime (DeShon & Gillespie, 2005). Whereas

a learning orientation establishes an open-ness to new insights and lessons fromexperience, a performance-prove orienta-tion should encourage people to incorpo-rate those new lessons into their behaviorsand routines to improve their task perfor-mance. For example, VandeWalle et al.(2001) demonstrated that individuals witha performance-prove orientation are morelikely to implement the lessons extractedfrom performance feedback quickly andthus experience improvements in perfor-mance after receiving feedback. Thus, wesubmit that learning agility is maximizedwhen individuals hold a learning goal andperformance-prove goal orientation simul-taneously. This combination will enableindividuals to be both fast and more flexiblein learning from experience.

Cognitive and metacognitive abilities.General cognitive ability or g has beendefined as an individual difference in infor-mation processing capacity or the abilityto learn (Hunter, 1986; Kanfer & Ack-erman, 1989; Ree & Earles, 1991) andhas been shown to enhance job perfor-mance across a broad set of work and taskcontexts (Hunter & Hunter, 1984; LePineet al., 2000; Ree, Earles, & Teachout, 1994).Individuals who possess higher levels of gperform better because they are able toretain more information in their workingmemory and can thereby store knowledgeand skills more efficiently and learn morequickly from their experiences (Schmidt,Hunter, & Outerbridge, 1986). In addition,metacognitive ability is a specific form ofcognitive ability that reflects one’s abil-ity to ‘‘think about thinking’’ and monitorcognition (Flavell, 1979). Prior research sug-gests that metacognitive ability is positivelyrelated to knowledge and skill acquisition,monitoring of goal progress, adaptation andlearning, and task performance (Ford et al.,1998; Kanfer & Ackerman, 1989; Pintrich& De Groot, 1990; Pokay & Blumenfeld,1990).

We propose that general cognitive abil-ity and metacognitive ability will be relatedto learning agility by enabling individuals


to be faster and more flexible in learn-ing from experience. In terms of speed,prior research suggests that general cog-nitive ability enhances individuals’ work-ing memory, which in turn is associatedwith greater perceptual and processingspeed (Ackerman, Beier, & Boyle, 2002;Kyllonen & Christal, 1990). In this research,the authors argue that greater cognitive abil-ity increases three aspects of learning speed:(a) the encoding speed with which informa-tion makes its way from an initial precept toa representation in working memory, (b) theretrieval speed with which information fromlong-term memory is deposited in work-ing memory, and (c) the speed with whichinformation leads to a specific behavioralresponse. In terms of flexibility, a strongermetacognitive ability should be associatedwith an enhanced ability to see connec-tions and move across ideas more easily.As noted by Shore and Dover (1987),‘‘Metacognitive processes enable individ-uals to better control their thinking andthereby become more efficient and flexiblelearners’’ (p. 37). One reason for this asso-ciation is that metacognitive ability reducesthe likelihood that an individual myopi-cally focuses on a single element of thetask and instead has a greater apprecia-tion and understanding of the connectionsacross elements. Indeed, research suggeststhat metacognitive ability enhances individ-uals’ problem-solving abilities in complexsituations or tasks (Swanson, 1990).

Openness to Experience. Openness toExperience captures the extent to whichindividuals are broad minded, curious,imaginative, and original (Barrick & Mount,1991; Costa & McCrae, 1992; McCrae,1987). Open individuals have a strong intel-lectual curiosity, actively seek out new andvaried experiences and ideas, and are gen-erally more receptive to change (Costa &McCrae, 1992; King, Walker, & Broyles,1996; McCrae, 1987). They have beenshown to be more creative and better ableto adapt to change than those who are lessopen (Baer & Oldham, 2006; Feist, 1998;LePine et al., 2000). Likewise, individuals

high on Openness to Experience are ableto draw from a broader range of experi-ences and perspectives when in new situ-ations (McCrae & Costa, 1996) and havebeen shown to be more willing to engagein the self-monitoring and assessment thatis involved in learning from experience(Blickle, 1996; Busato, Prins, Elshout, &Hamaker, 1999).

Being open to new experiences and per-spectives allows an individual to take ina broader array of knowledge, and thisbreadth increases flexibility as the individ-ual is not limited to a single perspectiveand is able to draw on multiple, perhapseven conflicting, sources of information.Openness has also been described as akey determinant of a broader searchingfor information and a more thorough andflexible analysis of available information(Day & Lance, 2004; Hooijberg, Hunt, &Dodge, 1997). For example, Day and Lancediscussed the need to handle potentiallyconflicting ideas and balance the differen-tiation and integration of experience as animportant aspect of leader development. Assuch, the tendency to be open to new ideasand experiences, and in particular ones thatmight contradict prior knowledge and expe-rience, should be related to the degree towhich individuals are flexible and exhibitagile learning.

Cognitive and Behavioral ProcessesUnderlying Learning Agility

Critical to building a framework of learningagility is an understanding of what learning-agile individuals do differently from others.Figure 1 suggests two fundamental differ-ences: (a) internal, cognitive processes thatpeople with high learning agility engage into facilitate fast and flexible learning pro-cesses and (b) external, more visible behav-ioral processes that agile learners employto enhance their learning. In the follow-ing sections, we describe three cognitiveand three behavioral processes (a set thatis neither exhaustive nor exclusive) thatunderlie an individual’s learning agility.We suggest that these processes are both a


manifestation of learning agility (meaningthat individuals higher in learning agilityare more likely to engage in them) andalso support and promote learning agility(meaning that the more individuals engagein them over time, the more learning agilethey will become).

Cognitive processes. First, agile learnerslikely engage in more prospective cogni-tive simulations—a form of internal, mentalexperimentation about possible future situ-ations and experiences (Bandura & Adams,1977; Sanna, 2000; Taylor & Schnei-der, 1989). Cognitive simulations that areprospective, such as visualization, allowindividuals to imagine possible situationsthat they may encounter in the future anddraw connections with prior experience todevelop strategies that can be applied in thefuture. In this sense, individuals can thinkabout how they might act in a situation, andin thinking through alternatives, lessons canbe extracted before even having the expe-rience. Although cognitive simulations canonly represent a portion of a potential expe-rience (Barsalou, 1999), they have beenshown to aid implicit and explicit memory,as well as application of learned skills tofuture tasks (e.g., Schacter & Addis, 2007).

Thus, cognitive simulations enable indi-viduals to forecast and make predic-tions about potential future situations andthrough this forecasting come up with pos-sible solutions and behavioral intentionsfor what one might do in the situation.In this sense, prospective cognitive simula-tions enable individuals to take the learningthey have acquired from one experienceand quickly and flexibly apply it to futureexperiences. This preplanned understand-ing of how one might apply his or herknowledge to a future scenario enables indi-viduals to learn and adapt more quickly, asthey will already have a partially formedplan of action. In addition, prospective sim-ulations allow individuals to forecast fora range of experiences beyond those thatthey have actually encountered in the past,thereby reducing the reliance on actualexperience for learning purposes.

A second cognitive process that bothsupports and is a manifestation of an indi-vidual’s learning agility is the practice ofcounterfactual thinking, which is a retro-spective form of cognitive simulation (Man-del & Lehman, 1996; Markman, Gavanski,Sherman, & McMullen, 1993; Sanna, 2000).Counterfactual thinking is the process ofimagining what ‘‘might have been’’ in anygiven situation and identifying alternativeoutcomes that might have arisen if onehad acted differently or the situation hadbeen different (Baron, 1999). Counterfac-tual thinking has a strong effect on individ-ual cognition and enhances learning andapplication in a variety of ways (Roese,1997). For example, counterfactual thinkingenables individuals to clarify cause-and-effect relationships (Branscombe, Crosby, &Weir, 1993) and identify more effectivestrategies for performance (Johnson & Sher-man, 1990). By engaging in counterfactualthinking, individuals can more quickly iden-tify the possible ways in which a prior expe-rience could have unfolded and, throughconsideration of these alternative coursesof action, more quickly extract the lessonsof experience and apply these lessons tofuture experiences. Moreover, by examin-ing not only what happened but also whatmight have happened, a person engaging incounterfactual thinking can draw a broaderrange of lessons from experience than justthose that he or she encountered directly,which should in turn enhance individualflexibility in drawing connections acrossdifferent ideas and experiences. As such, anindividual who engages in counterfactualthinking is more agile as a learner.

Beyond prospective and retrospectivecognitive simulations, a third cognitive pro-cess enabling learning agility is that ofpattern recognition. Matlin (2002) definespattern recognition as the process throughwhich individuals perceive complex andseemingly unrelated events as constitutingidentifiable patterns. Work in cognitive psy-chology suggests that individuals recognizethese patterns through the use of prototypes(a theoretical amalgam of the most fre-quent or modal features of a given category)


or exemplars (specific examples of mem-bers of a given category) to categorizean experience into a relevant category,and it is this categorization process thatenables individuals to see patterns acrossseemingly disparate experiences (Ashby &Maddox, 2005).

Extending these notions of pattern recog-nition to learning from experience, we positthat pattern recognition enables more agilelearning. Just as entrepreneurs are able to‘‘connect the dots’’ between their past expe-riences and a future venture opportunity(Baron, 2006; Baron & Ensley, 2006), webelieve that the ability to better discernpatterns and linkages within and betweenexperiences will enable individuals to applytheir learning more quickly and more flex-ibly. Whereas individuals without strongpattern recognition abilities can apply thelessons of prior experience to very simi-lar future experiences, an individual withstrong pattern recognition abilities will beable to more quickly and flexibly see con-nections across a broader range of expe-rience types. These individuals can seesimilarities between experiences that, onthe surface, seem unrelated and, as a result,be more agile in their learning from andapplying the lessons of experience.

Behavioral processes. In addition to inter-nal, cognitive processes, there are severalmore visible, behavioral processes throughwhich learning agility is manifested and thatsupport learning agility in return. Thoughno single process is either necessary or suf-ficient for being an agile learner, engagingin these processes provides a structure andset of behaviors through which the learningagile can augment their speed and flexibilityin learning from experience.

One key behavior related to learningfrom experience is seeking feedback. Indi-viduals learn best from experience whenthey ‘‘check in’’ with others by activelyseeking and receiving feedback (Ashford &DeRue, 2012; Ashford & Tsui, 1991; DeRue& Ashford, 2010a), and feedback seekinghas been shown to be particularly relevant

when situations are more uncertain (Ash-ford, 1986; Brett, Feldman, & Weingart,1990; Morrison, 1993) and when learn-ing is the primary goal (Ashford, Blatt, &VandeWalle, 2003; Butler, 1993; Vande-Walle & Cummings, 1997). Moreover, indi-viduals who actively seek feedback fromothers, rather than just waiting to receiveit, are more likely to receive more accuratefeedback. People often do not like givingfeedback, especially negative feedback. Assuch, seeking feedback counteracts a preva-lent social norm of withholding negativefeedback, leading the individual to a morethorough and precise understanding of hisor her own behavior (Ashford & Tsui, 1991).

Correspondingly, active feedback seek-ing should, at minimum, enhance the flexi-bility with which people are able to see anddraw connections between their behaviorand outcomes, as well as patterns acrosswithin and across experiences. Obtainingfeedback from others provides additionalpoints of data that individuals can incorpo-rate into their understanding of a situationand their behavior within it, thereby broad-ening the points of view that are consideredin the experiential learning process. Theseadditional perspectives can be combinedwith the individual’s own perceptions ofthe experience to generate a more thor-ough and detailed understanding of thesituation, which in turn should enhancethat person’s ability to see how the lessonsof one experience could inform and applyto a separate situation—thereby enhanc-ing the flexibility dimension of learningagility. With respect to the speed dimen-sion of learning from experience, the effectof feedback seeking is less apparent. Onone hand, feedback seeking could helpidentify lessons of experience that wouldgo unrealized if the person was left to inter-pret and process experience on his or herown, thus enhancing the speed of learn-ing. On the other hand, feedback seekingcould slow down the learning process byintroducing points of view or alternativeperspectives that introduce unnecessary orunhelpful variation in the interpretationsof a particular experience. Thus, although


feedback should enhance how flexible peo-ple are in drawing connections within andacross experiences, the impact on speed ofperception, processing, and learning is lessclear.

Experimentation is a second behavioralprocess that is related to learning agility.According to Kolb (1984), individuals havethe ability to experiment with differentbehaviors, tactics, and strategies as they gothrough an experience. Within the bound-aries of any single experience, peoplewho engage in active experimentation—forexample, trying out new behaviors orapproaches to a particular action—havea much richer set of experiences to learnfrom compared with those who do notexperiment and thus engage in fewer dif-ferent behaviors. Prior literature identi-fies two forms of experimentation, guidedand enactive (i.e., self-guided; Debowski,Wood, & Bandura, 2001; Wood, Kake-beeke, Debowski, & Frese, 2000), thoughthe effect of each has been explored pri-marily with tasks that are removed fromany interpersonal or organizational context(e.g., electronic searches on the computer).They found that experimentation was effec-tive primarily after a person had somedegree of proficiency at the task. Our viewis that when individuals engage more com-plex and ambiguous tasks and go into moredynamic and uncertain situations, such asa leader taking on a novel job assignment,those who engage in mini-experiments asthey move through the assignment developmore accurate mental models of leadership,a stronger sense of self-efficacy and identityas a leader, and a broader range of leaderbehaviors (DeRue & Ashford, 2010b; Ng,Van Dyne, & Ang, 2009).

Engaging in active experimentationshould also enhance an individual’s learn-ing agility. It allows an individual to ‘‘tryout’’ different ways of being within oneexperience, thereby illuminating a moredetailed mental model of the experienceand a broader range of lessons that mightbe gleaned from the experience. Similar tofeedback seeking, active experimentationshould enhance the flexibility with which

people see and draw connections withinand across experiences. Interacting withan experience in different ways throughengaging in behavioral experiments shouldhighlight the ways in which the same expe-rience (and its associated knowledge) canbe applied in different contexts, therebyenhancing individuals’ flexibility in apply-ing the lessons of experience across differentsituations. With respect to speed of learning,active experimentation could slow downthe learning process, as experiments taketime. That said, in complex and dynamicenvironments, we expect the experimen-tation process will actually speed up thelearning process by illuminating lessons ofexperience that would otherwise not beapparent. For both feedback seeking andactive experimentation, there is likely akey boundary condition with respect to thespeed of learning: specifically, the morecomplex and dynamic the situation is, themore feedback seeking and active experi-mentation increase the speed of learning.

A third behavior enabling and promot-ing learning agility is an individual’s ten-dency to reflect on the lessons of expe-rience. Reflection has been identified asa powerful process that helps individu-als ‘‘digest’’ their experiences, identify keylessons, and incorporate those lessons intofuture experiences (Alinsky, 1971; Anseel,Lievens, & Schollaert, 2009; DeRue & Ash-ford, 2010a; Gosling & Mintzberg, 2003;Schon, 1983). Recognizing the value ofreflection in learning from experience,researchers have examined how reflectionpractices can be designed and structuredto enhance the learning value of expe-rience, with a particular focus on thevalue of structured reflection interventionssuch as after-event reviews (Baird, Hol-land, & Deacon, 1999). For example, Ellisand Davidi (2005) showed that after-eventreviews focusing on both successes and fail-ures improved learning and performancemore so than after-event reviews focus-ing only on failures. Extending this study,Ellis, Ganzach, Castle, and Sekely (2010)showed that both personal and filmed after-event reviews can be effective, and in


both cases, the after-event review leadsto performance improvements by increas-ing individuals’ self-efficacy. By providinga more structured process that addresseskey barriers to learning from experience(e.g., individual biases such as hindsightbias), structured reflection enables peopleto develop a more accurate understandingof cause and effect, a richer understandingof counterfactuals, and clear guidance onhow the lessons of experience can translateinto behavior change in the future. In turn,after-event reviews enable greater learningfrom experience in complex and dynamicenvironments (DeRue, Nahrgang, Hollen-beck, & Workman, in press).

Reflection practices such as after-eventreviews should enable individuals to morequickly and flexibly learn from experience,thus enabling greater learning agility. Interms of flexibility, reflection will be animportant process for identifying connec-tions across disparate ideas or divergentpoints of view, as well as across seriesof actions that seem disjointed or discon-nected. According to Alinsky (1971), with-out reflection, individuals can go throughan experience without ever really havingan experience. That is, in the ‘‘heat ofthe moment,’’ people can easily miss thelessons of experience. By dedicating timeand energy to structured reflection duringand after an experience, people can con-struct broader, more complex, and moredetailed knowledge and insights from anexperience. In particular, people should seemore connections among ideas and pointsof view and develop these insights fasterthan if they were not reflecting and just act-ing. Thus, reflection should foster greaterlearning agility.

Context Factors Related to Learning Agility

Past research has emphasized the conse-quences of learning agility and the personalattributes that predict learning agility (DeMeuse et al., 2010), but less attention hasbeen directed at understanding the envi-ronmental factors that might moderate theeffects of learning agility. Yet, anything in

the environment that affects the speed oflearning, or the degree to which people canbe flexible across different points of view orcompeting ideas, would affect the degree towhich people, even people high in our pro-posed individual difference predictors, candemonstrate agility in the learning process.Moreover, environmental factors might alsoinfluence the degree to which learningagility translates into greater within- andcross-situational learning and development.Thus, in developing the construct of learn-ing agility and specifying related constructs,we also need to consider how contextualand environmental factors might influenceindividuals’ ability to be agile learners andthe subsequent consequences of learningagility.

Some environmental factors will be localto the person’s experience. For example,drawing from trait activation theory (Tett &Burnett, 2003; Tett & Guterman, 2000),the nature of the experience itself couldhave a strong influence on whether peopledemonstrate learning agility. Some experi-ences more so than others should activateindividuals’ learning agility, which in turnwould promote quicker learning and moreflexibility across ideas within the experi-ential learning process. An example mightbe in Kohn and Schooler’s (1978) clas-sic work on intellectual flexibility. In theirstudies, they examined the reciprocal rela-tionship between intellectual flexibility andthe substantive complexity of work or thedegree to which work requires indepen-dent thought and judgment—for example,jobs that require making decisions thatinvolve ill-defined or conflicting contingen-cies. Their findings suggest that experienceshigh in substantive complexity can actuallyenhance the degree to which people exhibitintellectual flexibility. Likewise, research onexperience-based leadership developmentsuggests that experiences rich in devel-opmental challenge promote learning bybreaking routines and forcing people tothink about and process experiences in dif-ferent ways (McCall et al., 1988). In thisresearch, more complex and challengingexperiences create a context where the


demand for learning agility is greater andthus is likely to trigger the expression oflearning agility more so than less challeng-ing or less complex experiences.

Yet, there is an ironic tension betweenthe attributes of experience that make themdevelopmental and learning agility. On onehand, learning agility will most likely beactivated and needed in experiences thatare more complex and challenging—thusthe reason Lombardo and Eichinger (2000)include tough or first-time experiences intheir definition of the concept. On the otherhand, research suggests that experiencescan become overly challenging and com-plex, thereby impairing or hindering thelearning process (DeRue & Wellman, 2009).With respect to learning agility, it mightbe that experiences can become so com-plex that individuals cannot acquire newknowledge fast enough or there are sim-ply too many conflicting inputs or pointsof view so that individuals are less likelyto exhibit agile learning. In this sense, thesame qualities of experience that make anexperience developmental could ultimatelybe the qualities that reduce the likelihoodof individuals demonstrating agile learn-ing. For example, as experiences becomemore complex, the relative importance ofspeed versus flexibility in learning agilitymight differ, where flexibility becomesmore important than speed as experiencesincrease in complexity.

Moving beyond the experience itself,there are also aspects of the broader groupand organizational context that might mod-erate the likelihood of individuals engag-ing in agile learning or the effects ofagile learning on outcomes. Edmondson’s(1999) research on psychological safety sug-gests that a context that is considered safeallows people to take risks, explore differ-ent avenues of thought, raise questions, andseek feedback. As De Meuse et al. (2010)point out, learning from experience gener-ally requires one to be wrong sometimes,and a punitive culture inhibits individuals’motivation for learning (Day, Harrison, &Halpin, 2009). Learning agility specificallyrequires a certain freedom of thought or

playfulness when it comes to consideringvarious approaches and points of view. Oneof the major deterrents to that playfulnesswill likely be defensiveness or an overcon-cern with the self. Thus, anything in theenvironment that increases concerns aboutego and image would likely detract fromlearning agility.

For example, educational psycholo-gists have long recognized the relation-ship between openness and defensiveness(Brockett & Hiemstra, 1991; Fisher, King, &Tague, 2001; Oddi, 1986). If individuals areconcerned about ‘‘being right’’ or ‘‘beingseen as being right,’’ then they are morelikely to invest in their point of view anddefend it against perceived attacks (and aremore likely to perceive disagreement asan attack). Such defensiveness reduces anindividuals’ ability to move flexibly acrossideas while also distracting their thinking inways that could reduce the speed at whichthey acquire and apply new knowledge.It is also possible that this defensivenesscould reduce the degree to which peo-ple consider points of view that do notdirectly support their held beliefs, whichin turn might result in learning the wronglessons entirely or missing out on a learningopportunity. De Meuse et al. (2010) discusshow a punitive culture could have neg-ative implications for learning agility, butwe extend this idea even further. In par-ticular, any element of an organizationalculture (e.g., the reward system) that pro-motes individualism and narrowly measuresachievement will prompt a focus on ‘‘beingright’’ and ‘‘looking right.’’ In other words,there are dimensions of organizational cul-ture beyond its punitiveness that will affectlearning agility. For example, the extent towhich learning is well articulated as a normand modeled in the organization shouldhelp trigger individuals’ underlying abilityto learn fast and be flexible, thus promptinggreater demonstration of learning agility inthe organization.

The personal attributes, cognitive andbehavioral processes, and context factorsthat we have identified as being relatedto learning agility represent only a few of


the many potential constructs within thenomological network of learning agility. Byidentifying a few exemplar concepts thatare either closely tied to learning agilityor are a manifestation of learning agility,and elaborating how they relate to orcapture aspects of learning agility (speedand flexibility), we hope to have clarifiedhow learning agility is situated within thebroader conceptual space of learning fromexperience.

Assessing Learning Agility

To truly understand learning agility and itseffects, we need valid and reliable mea-sures of the construct. In this section, weaddress several concerns regarding the mea-surement of learning agility. The dominantmeasure in this research, called ChoicesArchitect®, was developed by Lombardoand Eichinger (2000; Eichinger & Lom-bardo, 2004). It consists of 81 items thatassess their original four dimensions oflearning agility; the measure has evolvedover time into a workbook and assessmentcalled FYI for Learning Agility™ (Eichinger,Lombardo, & Capretta, 2010). To helpestablish its psychometric properties, DeMeuse, Dai, Hallenbeck, and Tang (2008)used the Choices Architect® measure toassess learning agility in a sample of 1,000employees from a large firm headquarteredin South America. They found that theChoices Architect® measure was reliableacross four different world regions. In addi-tion, the data from this study establishedthat learning agility as measured by ChoicesArchitect® is normally distributed, with noobserved differences across gender or age.

Although Lombardo and Eichinger (2000)are to be commended for putting the learn-ing agility construct on the map and fordeveloping Choices Architect® to helpresearchers begin to measure it, thereare several prominent concerns with theChoices Architect® measure. First, with 81items—27 dimensions of 3 items each,clustered into 4 agility factors (people,change, mental, and results) that each con-tain between 4 and 11 dimensions—the

measure lacks parsimony and is likely morecomplex than it needs to be for measuringlearning agility.

Second, the measure is not well alignedwith the definition of learning agility thatLombardo and Eichinger originally pro-posed. Recall that the authors define learn-ing agility as ‘‘the willingness and abilityto learn new competencies in order toperform under first-time, tough, or differ-ent conditions’’ (Lombardo & Eichinger,2000, p. 323). Ignoring for the momentthe conceptual issues involved in including‘‘willingness’’ as a component of the defi-nition of an ability construct, the authorsstray even from their own definition oflearning agility. Instead of containing a‘‘willingness’’ factor and an ‘‘ability’’ fac-tor, as seems to be indicated in their originaldefinition, the Choices Architect® measureincludes four factors: people agility, resultsagility, change agility, and mental agility.These four factors are further divided into27 dimensions, and although some dimen-sions seem related to learning agility, suchas ‘‘complexity’’ or ‘‘inquisitive,’’ the vastmajority seem unrelated, such as the ‘‘deliv-ers results,’’ ‘‘cool transactor,’’ ‘‘taking theheat,’’ or ‘‘light touch’’ dimensions. Thesefactors and dimensions seem to lose touchwith the basic idea of learning agility andseem to be more a product of factor anal-ysis than careful theoretical consideration.As an example, the items, ‘‘Knows howto get things done outside of formal chan-nels as well as within them; is savvy aboutwho to go to, and when’’ and ‘‘Is politi-cally adept; knows how to work with keydecision makers and stakeholders’’ seemconceptually similar (although neither seemrelated to learning agility). However, in themeasure, these items correspond to twoentirely different factors (and correspond-ingly, different dimensions)—change agility(innovation manager) and people agility(cool transactor), respectively.

Not only does the Choices Architect®scale invite questions about content validitywith respect to Lombardo and Eichinger’s(2000) original definition, we also haveconcerns about whether it adequately taps


our more narrow definition of learningagility in terms of speed and flexibility.To assess content validity with respectto the refined definition, we and threemanagement PhD students who were blindto the purpose of the exercise coded the 81items of the Choices Architect® measure,as either (a) a manifestation of learningagility, (b) a concept that was somewhatrelated to learning agility, or (c) totallyunrelated to learning agility as defined inthis article. Thus, six raters coded eachitem according to three possible responses.Only 14 items were rated as manifestationsof learning agility by four or more raters,and 26 items were rated as unrelated tolearning agility by four or more raters.There was less agreement with respectto the remaining 41 items, suggestingsignificant conceptual confusion in theChoices Architect® measure. In summary,many of the items seem unrelated to theauthors’ original definition and, certainly, aswe have defined it here, thus drawing intoquestion the content validity of the measure.

A third issue with the Choices Architect®measure is that some of the items cap-ture performance dimensions that shouldbe measured separately as outcomes, suchas the degree to which people build high-performing teams, are effective at manag-ing diversity, and get things done with-out relying on authority. Examples includeitems such as ‘‘Performs well under first-time conditions; isn’t thrown by chang-ing circumstances’’ or ‘‘Has a significant,noticeable presence.’’ The content of theseitems is related to an individual’s per-formance more so than learning agility.This observation is particularly importantgiven the strong claims made about learn-ing agility predicting performance (e.g.,Lombardo and Eichinger, 2000). This rela-tionship would be true by definition giventhat the two are confounded in the ChoicesArchitect® measure.

Finally, of the 81 items, almost 40% aredouble barreled. One example is the item:‘‘Knows that change is unsettling; can takea lot of heat, even when it gets personal.’’In this example, a person might agree that

change is unsettling but not feel that heor she can take a lot of heat or only do sowhen the situation is impersonal. Responsesto such items are impossible to evaluate.

In summary, the Choices Architect®measure has been a valuable stimulusfor research on learning agility, but tosufficiently assess the construct in thefuture, a new measure is needed. Weneed a fresh start—a measure of learningagility that is theoretically grounded andpsychometrically sound.

Concluding Remarks

Our intent with this article is to offer aconstructive critique of research on learn-ing agility in service of providing a strongertheoretical foundation for future researchon this important concept. As a researchcommunity, we are at a choice point. Wecan keep going as we are, conceptualizinglearning agility as we have despite its con-ceptual ambiguity. The result, we believe,will be to blur the boundaries betweenlearning agility and learning ability so muchthat the two become nearly synonymous, tothe detriment of progress in this literature.The other option is to embrace a con-ceptually clearer and narrower definitionof learning agility. This path has attrac-tive properties regarding construct develop-ment. A more precise definition allows usto differentiate learning agility from learn-ing ability and, as a result, allows us toassess the contribution of learning agilityto performance over time in organizations.The practical benefit of this path is that,if organizations are indeed becoming morecomplex and facing more uncertainty anddynamism in the environment, there will bepayoff for firms that can better identify andemploy highly agile learners as well as pay-off for individuals within those firms whocan demonstrate agile learning.

In this article, we have taken thefirst step in this process by proposing aconceptualization of learning agility that ismore faithful to its everyday definition andsituating it within a nomological networkof related constructs. We then turned


to measurement, where we highlightedseveral concerns related to the dominantmeasure of learning agility (the ChoicesArchitect® scale). What we end up with is anarrower, more focused construct that tapsa person’s speed and flexibility in learningfrom experience in organizations, as befitsthe definition of agility. By refining andnarrowing the conceptualization of learningagility, we hope to provide a foundationfor future researchers to develop measuresof learning agility, explore its conceptualboundaries and causal relationships, andultimately draw more precise conclusionsabout learning agility and its effects onlearning from experience.

An attractive future research agendawould include several following steps.First, the development and validation ofa learning agility measure is essential toprogress in this area. The goal is to createa parsimonious and targeted measure oflearning agility that allows differentiationbetween the speed at which people canlearn from experience and the flexibilitywith which people are able to work acrossideas both within and across experiences.Spreitzer et al.’s (1997) research on abilityto learn and the flexibility dimension wouldbe one role model in this regard. Thegoal is to construct a measure of learningagility that is reliable, valid, and empiricallydifferentiates between speed and flexibility.Such a measure will allow researchersto assess the unique variance explainedby learning agility beyond other relatedconstructs. Likewise, researchers would beable to determine what types of situationsrequire agility for learning to occur, as wellas identify the types of situations whereagility is not particularly necessary. With amore focused concept and measure, theterrain can be assessed more precisely,allowing our knowledge to accumulateand our field to advance an understandingof how individuals and organizations canlearn faster and more flexibly.

Second, speed and flexibility are bothpart of learning agility, but the two dimens-ions are not the same and introduce someinteresting tensions in the experiential

learning process. We have pointed out thatthey can be in tension (e.g., moving quicklycan hurt one’s flexibility) and also relatedconstructs that may help in one area canhurt in another (e.g., feedback seeking mayhelp individuals be more flexible in thelearning process and also slow them downin the process). In addition, learning occursover time, and to the extent that a personis particularly strong at learning quickly, itmay also be true that this person developsa point of view quickly and then cannotadapt that point of view over time. Weexpect that differential predictions aboutspeed and flexibility will be an interestingand important focus for future research onlearning agility.

A third emphasis for future researchshould be on the role of context. Argu-ments for the importance of learningagility are inherently contextualized, asthey invoke the dynamic and complexnature of organizations and their environ-ments—for example, that agility is moreimportant in substantively complex envi-ronments. Future research that examinesthe role of context in shaping the payoffof learning agility, or the ability of indi-viduals to engage in agile learning, wouldbe particularly noteworthy. This researchwould shed light on the conditions underwhich organizations should pay particularattention to learning agility, as well as offerinsight into how organizations can fosterlearning agility in their employees.

Finally, future research needs to employmethods that allow for stronger conclu-sions about learning agility. These methodsinclude using multiple sources to assessindividuals’ learning agility and the out-comes associated with learning agility. Inaddition, to assess the impact of learn-ing agility on learning, researchers needto employ longitudinal research designs tounderstand whether learning agility pro-duces a faster rate of learning or differenttrajectories and patterns of learning. Toillustrate, organizational newcomers withhigher learning agility might exhibit steeperlearning or performance curves, rising tohigher levels of learning or performance


much more quickly, than do peers withlower learning agility. However, if placedin jobs with low complexity, their learningcurve may plateau or be similar to the curvefor individuals who are lower in learningagility. Thus, the relative advantage of beinglearning agile will likely be affected by theenvironment within which one is operat-ing. Such dynamic modeling of the effectsof learning agility over time and across con-texts would be a noteworthy extension ofour work and be a valuable contribution toour understanding of learning from experi-ence in organizations.

We have great confidence in the impor-tance of learning agility in today’s world.Our hope is that with more careful defi-nition and measurement, we might assessits impact more precisely and understandnuances and complexities in its develop-ment and effects. This article establishes anagenda for what we hope will be a fruitfulresearch stream for years to come.

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