ArticlePDF Available

Learning agility: Its evolution as a psychological construct and its empirical relationship to leader success

  • Wisconsin Management Group

Abstract and Figures

The concept of learning agility has grown markedly in popularity during the past few years as an approach to assist human-resource professionals and organizational executives with their talent decisions. Nevertheless, there remains much confusion about what is learning agility, how to measure it, when to use it, and the extent of its relationship to leader success. The purpose of this article is to clarify this relatively new approach to high-potential talent identification and development. Initially, the historical roots of learning agility are traced. Its conceptual origin, formulation as a psychological construct, expansion as a leadership assessment, and theoretical underpinnings are described. Subsequently, 19 field studies investigating the empirical linkage between learning agility and leader success are reviewed. The findings of a meta-analysis show it has a robust relationship with both leader performance (r¯ = 0.47) and leader potential (r¯ = 0.48). Finally, five issues facing the application and study of learning agility are discussed. The goal is to increase practitioners’ understanding of this popular method of talent management as well as to spur additional scholarly research of the construct.
Content may be subject to copyright.
Kenneth P. De Meuse
Wisconsin Management Group, Minneapolis, Minnesota
The concept of learning agility has grown markedly in popularity during the past few
years as an approach to assist human-resource professionals and organizational execu-
tives with their talent decisions. Nevertheless, there remains much confusion about what
is learning agility, how to measure it, when to use it, and the extent of its relationship
to leader success. The purpose of this article is to clarify this relatively new approach to
high-potential talent identification and development. Initially, the historical roots of
learning agility are traced. Its conceptual origin, formulation as a psychological con-
struct, expansion as a leadership assessment, and theoretical underpinnings are de-
scribed. Subsequently, 19 field studies investigating the empirical linkage between
learning agility and leader success are reviewed. The findings of a meta-analysis show
it has a robust relationship with both leader performance (r0.47) and leader potential
(r0.48). Finally, five issues facing the application and study of learning agility are
discussed. The goal is to increase practitioners’ understanding of this popular method of
talent management as well as to spur additional scholarly research of the construct.
Keywords: learning agility, leadership development, leadership selection, high potentials,
talent management
To be fertile in hypotheses is the first prerequisite of discovery, and to be willing to throw them away the
minute experience contradicts them is the next.
—William James, 19th-century psychologist
The illiterate of the future will not be those who cannot read, but those who cannot learn.
—Alvin Toffler, writer and futurist
There is a long, rich history of learning research in psychology, dating back to the early experiments
of Ivan Pavlov and B. F. Skinner. The concept of learning agility is much more recent and has more
to do with the application of learning and performance success than simply making a connection
automatically between a stimulus and a response (cf. De Meuse, Dai, & Hallenbeck, 2010;Eichinger
The author wants to thank Kim Ruyle, Guangrong Dai, and Renee Garpestad for their insights and recommen-
dations on earlier drafts of the article.
Correspondence concerning this article should be addressed to Kenneth P. De Meuse, Ph.D., Founder and
President, Wisconsin Management Group, 1508 Archwood Road, Minnetonka,
Minnesota 55305. E-mail:
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Consulting Psychology Journal: Practice and Research © 2017 American Psychological Association
2017, Vol. 69, No. 4, 267–295 1065-9293/17/$12.00
& Lombardo, 2004). Learning agility focuses on human behavior, high-level cognitive processing,
and the selective transference of lessons learned in one setting and applying them to a uniquely
different one. It includes experimentation, self-reflection, leveraging individual strengths, continu-
ous improvement, mindfulness, and mentally connecting experiences obtained in one situation to
different challenges in another.
In 2000, Michael Lombardo and Robert Eichinger published a journal article entitled, “High
Potentials as High Learners.” In this article, they coined the term learning agility and presented their
initial findings on the relationship between learning agility and leadership potential. The premise of
their work was that potential cannot be fully detected from what an individual already can
demonstrate. Rather, it requires that the individual do something new or different. In their view,
potential involves learning new skills to perform in different, very often challenging, situations.
They contended that people differ greatly as learners from experience. It is this capacity to learn
from experience that differentiates high potentials from others. Lombardo and Eichinger (2000)
posited that successful leaders learn more effectively and are able to be more flexible (i.e., agile) in
novel organizational environments.
During the past 15 years, the popularity of the concept has increased dramatically throughout
the business world. A recent survey found that learning agility was the most frequently used
criterion to measure leadership potential, with 62% of the respondents citing it; cultural fit (28%),
emotional intelligence (24%), personality (14%), and intelligence (13%) were identified less often
(“Potential: Who’s Doing What,” 2015). Likewise, Church, Rotolo, Ginther, and Levine (2015)
found that more than one half of the companies they sampled used learning agility/ability as an
assessment for identifying high potentials (56%) and selecting senior executives (51%). A recent
Google search of learning agility registered 18.2 million entries whereas the much more established
term of emotional intelligence had fewer than 13 million entries.
Although learning agility has played a significant role in the practitioner world for many years,
the academic community only recently has become interested in studying it. Lately a number of
scholarly articles have been published examining the theoretical and empirical support for it as an
important determinant for high-potential talent (cf. De Meuse et al., 2010;Silzer & Church, 2009).
The focal article in a recent issue of the Journal of Industrial and Organizational Psychology was
entitled, “Learning Agility: In Search of Conceptual Clarity and Theoretical Grounding” (DeRue,
Ashford, & Myers, 2012). Following this article, there were nine commentaries reviewing learning
agility and its impact on high-potential talent (e.g., Arun, Coyle, & Hauenstein, 2012;Hezlett &
Kuncel, 2012;Mitchinson, Gerard, Roloff, & Burke, 2012).
The purpose of this article is to examine the evolution of the psychological construct of learning
agility. Its origin, formulation, and expansion are reviewed. Its theoretical underpinnings are
described and a model of its effect on leadership development and leader success is proposed.
Nineteen empirical studies are identified that examine the relationship between learning agility and
leader success. The methods in which those studies measured learning agility and assessed leader
success are provided. The correlations between learning agility and leader success are presented.
Subsequently, several observations with regard to the scientific state of learning agility are dis-
cussed. It is hoped this review will enhance the understanding of this popular practitioner concept
and stimulate additional scholarly research.
Tracing the Evolution of Learning Agility
During the late 1970s and early 1980s, scholars began to recognize that it was impossible to derive
an identifiable list of predisposing characteristics of successful leaders. Rather, leadership appeared
to be an interaction among a long list of individual traits, the environment, and gaining salient
management experience. However, researchers continued to have a limited knowledge of how
experience actually developed leaders. Not all job experiences seemed to be equal. The fundamental
questions were, first, “What experiences had the most developmental impact?” and, second, “Who
benefits the most from those experiences?” Without an understanding of how people learn and grow
from work experiences, organizations cannot fully leverage such experiences as developmental
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
tools. It was the frustration at being unable to generate a concrete list of necessary leader traits—as
well as an attempt to answer those two questions—that led to the beginnings of learning agility.
Its Origin as a Variable Related to Leadership
Doug Bray and his colleagues conducted a number of longitudinal studies at AT&T during the 1970s
and 1980s (Bray, Campbell, & Grant, 1974;Howard & Bray, 1988). Overall, they observed that
leaders who had been classified low on potential frequently were more successful than expected
when they were exposed to developmental opportunities and various work experiences. Likewise,
Robert Sternberg and his associates emphasized practical intelligence as a crucial component of
overall intelligence (Sternberg, 1985,1997;Sternberg et al., 1995). Those authors contended that
practical intelligence is the ability to solve everyday problems by using knowledge gained from
experience in order to purposefully adapt to, shape, and select the environment. In the cognitive and
educational sciences, researchers have performed expert-novice comparative studies to understand
what makes an expert. Several decades of research in nearly every discipline—music, art, sports,
medicine, and leadership— have found that experts are largely the result of deliberate practice (see
Ericsson, Krampe, & Tesch-Romer, 1993): not merely extensive practice but mindful, intentional,
and sustained effort.
During the 1980s and 1990s, the scientists at the Center for Creative Leadership (CCL)
performed a series of studies to understand how executives learn from their work experiences. The
CCL researchers interviewed approximately 200 executives in one investigation, asking them to
identify pivotal events in their careers. Specifically, they asked (a) what exactly happened and (b)
what did they learn from those events. Their findings are summarized in a book aptly titled The
Lessons of Experience (McCall, Lombardo, & Morrison, 1988). The researchers observed that
individuals differed greatly as learners from experience. Some learned more quickly and learned
more content than others. They noted that learning and development required that people move away
from their comfort zones, their habits, and their routines. The most meaningful developmental
experiences were challenging, stretching, difficult— uncomfortable! They were emotional, required
them to take risks, and tended to have real-life consequences (also see Lombardo & Eichinger,
2011). Their journeys often were unpleasant; learners had to be resilient and nondefensive (cf. Snell,
1992). Individuals had to possess a strong drive for growth. Overall, this research revealed that the
willingness and ability to learn from experience separated high-potential talent from others. The
importance of learning from experience for successful managers and executives has been observed
by many other leadership researchers as well (e.g., Bennis & Thomas, 2002;Day, 2000).
The CCL scientists also contrasted successful executives with ones who derailed. Using both
qualitative and quantitative methods, their research produced consistent findings across time,
hierarchical levels, national cultures, gender, and organizations (cf. Lombardo & Eichinger, 1989;
Lombardo, Ruderman, & McCauley, 1988;McCall, 1998;McCall & Lombardo, 1983;Morrison,
White, & Van Velsor, 1987;Van Velsor & Leslie, 1995). In general, the researchers found that both
successful and derailed executives had much in common. Both groups (a) were bright and ambitious,
(b) had been identified as high potentials early in their careers, (c) had noteworthy records of
achievement, and (d) were willing to sacrifice to advance their careers. In addition, both groups
possessed very few personal flaws. One derailment factor was identified repeatedly, however. The
researchers discovered that derailed executives were unable or unwilling to change and adapt. These
executives relied too heavily on a narrow set of skills developed early in their careers.
They also noted that successful executives usually had diverse experiences in a variety of work
settings. Derailed leaders, in contrast, had a number of prior successes but usually in very similar
organizational situations. The CCL scientists reported that for the majority of leaders who had
derailed, their technical superiority—which was a source of success at lower levels of leadership—
became a weakness as they ascended to higher levels, leading to overconfidence and arrogance.
Successful and derailed executives also differed in the way they dealt with mistakes. Those
executives who were successful overwhelmingly handled failure with poise and grace. They
admitted mistakes, accepted responsibility, and then attempted to correct the problems. On the other
hand, leaders who derailed tended to be defensive about their mistakes, attempting to keep them
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
undercover while they tried to fix them, or they tended to blame others for their predicament. Their
unwillingness or inability to learn from experience appeared to be the major reason the executives
derailed. Hence, the foundational elements of learning agility were identified.
Its Formulation as a Psychological Construct
In their 2000 journal article where they introduced the term learning agility,Lombardo and
Eichinger asserted, “Identifying those who can learn to behave in new ways requires a different
measurement strategy from those often used, one that looks at the characteristics of the learning
agile” (p. 321). At the time, many organizations classified high-potential leaders as possessing the
“right stuff.” Thus, the objective of most succession planning programs was to look for early signs
of those “right stuff” skills and competencies for those professionals beginning their careers. When
personal attributes are relative stable over long periods of time (e.g., intelligence, certain personality
traits), it makes sense to consider them. However, the authors asked, “What evidence exists that a
promising 25-year-old looks like a younger version of a 50-year-old successful executive?” (p. 321).
They then concluded that if individuals learn, grow, and develop across time, comparing the
leadership competencies of a 25-year-old with a 50-year-old is not very informative. From their
perspective, learning from experience plays a significant role with regard to how an individual
demonstrates what is termed high-potential leadership.
Lombardo and Eichinger (2000) defined learning agility as “the willingness and ability to learn
new competencies in order to perform under first-time, tough, or different conditions” (p. 323). They
formulated a conceptual framework of learning agility consisting of the following four factors (see
Figure 1):
People agility: the extent to which individuals know themselves well, learn from experience, treat others
constructively, and are cool and resilient under the pressures of change.
Change agility: the level to which individuals are curious, have passion for ideas, like to experiment with
test cases, and engage in skill-building activities.
Results agility: the extent to which individuals get results under tough conditions, inspire others to
perform beyond normal, and exhibit the sort of presence that builds confidence in others.
Figure 1. Original conceptual model of learning agility proposed by Lombardo and Eichinger (2000).
See the online article for the color version of this figure.
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Mental agility: the degree to which individuals think through problems from a fresh point of view and are
comfortable with complexity, ambiguity, and explaining their thinking to others.
In their study the authors created a multirater assessment to measure learning agility and
administered it to 217 employees. They found the relationship between ratings of “performance
potential” and each of the four dimensions of learning agility was as follows: (a) people agility, r
.52; (b) change agility, r.53; (c) results agility, r.50; and (d) mental agility, r.47. The
overall relationship between this criterion and the four ratings of learning agility was R
0.30 (p
Between 2000 and 2010, numerous claims were made with regard to the importance of learning
agility and leadership success. The mass media, blogs, and websites boldly contended that learning
agility was critical for success in today’s global, dynamic business world. Some alleged it was “the
most in-demand business skill of the 21st Century” (Delaney, 2013). The president of CCL declared
that “learning agility equals leadership success” (Ryan, 2009). Marketing brochures in talent-
management consulting firms asserted it was the single most important predictor of executive
Likewise, the business literature revealed similar stories. In his book Why Smart Executives
Fail,Sydney Finkelstein (2003) focused on a subset of derailed executives—CEOs. He summarized
his observations in terms of “the seven habits of spectacularly unsuccessful people” (p. 238). A few
of those habits relate directly to learning agility, such as having all the answers and relying on what
worked for them in the past. Marshall Goldsmith (2007) advised managers “what got you here won’t
get you there.” The prevailing view from all those sources was that to continue down the path of
success, leaders have to continually change, adapt, learn, grow, and develop.
During the past several years, a number of scholarly publications likewise have supported the
importance of learning from experience and the notion of learning agility. For illustration, DeRue
and Wellman (2009) found that leadership-skill development started to diminish when (among other
things) an individual lacked the requisite learning orientation. Benjamin and O’Reilly (2011)
observed the extent to which young managers navigated leadership transitions effectively depended
on their ability to learn from the challenges brought about by change. In addition, it is important to
remember that the roots of learning agility are derived directly from scholarly observations (e.g.,
Bray et al., 1974;Eichinger & Lombardo, 2004;McCall et al., 1988;Sternberg, 1997). De Meuse
and his colleagues (2010) reviewed this research in much detail. As an individual climbs the
organizational ladder, most job assignments are novel, ambiguous, challenging, and adverse (McCauley,
Ruderman, Ohlott, & Morrow, 1994). Consequently, individuals need to possess several attributes to
benefit from such diverse job experiences. Learning agility represents the amalgamation of those
The Expansion of Learning Agility as a Leadership Assessment
Since the time Lombardo and Eichinger (2000) proposed the construct of learning agility as a
possible indicator of high-potential talent, it has transformed into a pervasive leadership tool. Many
organizations today assess learning agility when making decisions about whom to hire for leadership
positions, whom to promote, whom to designate for global assignments, and whom to place into
emerging-leaders or high-potential programs. In addition, fundamental to leadership-development
efforts is an individual’s capability to deal with complexity, ambiguity, novelty, diversity, and
adversity (Hooijberg, Hunt, & Dodge, 1997;McCauley et al., 1994). Scores on the various facets
of learning agility provide diagnostic guidance on areas that need particular developmental attention.
In an effort to understand how learning agility is evaluated today, three different instruments are
reviewed. These three self-assessments were chosen because they were developed exclusively to
measure learning agility rather than evaluate the construct as a derivative of another set of personal
attributes (e.g., Occupational Personality Questionnaire, Hogan). Further, each of the assessments
has been validated by a professional team of researchers trained in psychometrics, methodology, and
statistics. The first assessment—viaEDGE
uses a measurement model that was developed initially
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
by Lominger in the early 2000s (a U.S. company later purchased by Korn Ferry International). A second
—was created by Leader’s Gene Consulting, a firm headquartered in Shang-
hai. The third and most recent assessment—Burke Learning Agility Inventory
—is marketed by EASI
Consult, a U.S.-based consulting company. Although the three assessments differ in the number of
factors each measures, all three define the construct of learning agility similarly.
The purpose of this review is not to endorse one instrument over another. Nor is the objective to
support the psychometric integrity of the manner in which they measure learning agility. Rather, the three
assessments represent different ways in which learning agility is commonly measured today. Although
the instruments all are “self-assessments,” each one applies a slightly different metric to measure the
construct, embodying the definition and evaluation format the company marketing the assessment uses.
viaEDGE Assessment
The approach used to measure learning agility, as well as the number of factors comprising the
construct, has changed over time. Originally, learning agility was assessed by a multirater instru-
ment called Choices
(Lombardo & Eichinger, 2000). A fifth factor—“self-awareness”—was
added when the viaEDGE self-assessment of learning agility was developed (De Meuse, Dai,
Zewdie, Page, Clark, & Eichinger, 2011). In the Choices multirater assessment, the concept of
“self-awareness” is embedded in the “people agility” factor. The importance of making it a
stand-alone factor appears to be supported by the research literature (Avolio & Hannah, 2008;
Reilly, Dominick, & Gabriel, 2014). For example, McCall (2010) argued that although experience
is crucial for development, it is not the whole picture. What really makes the difference is the
internalization and reflection of those lessons the individual learns from that experience. If indi-
viduals do not do this, they miss out on adding the new skill to their repertoire. Studies investigating
“after-event reviews” reinforce the notion that reflection, retrospection, and self-awareness are
crucial elements of experience-based leadership development (DeRue, Nahrgang, Hollenbeck, &
Workman, 2012;Ellis & Davidi, 2005). Consequently, internalizing the lessons learned from
experience and becoming self-aware of one’s capabilities and limitations would seem to be a vital
component of being a learning-agile individual (Dominick, Squires, & Cervone, 2010).
Likewise, the literature on 360-degree feedback has reinforced the importance of self-awareness
and leadership effectiveness. With multirater approaches, self-awareness typically is measured by
the extent to which self-ratings are congruent with the ratings given by other raters (London &
Smither, 1995;Yammarino & Atwater, 1997). A highly self-aware leader has a greater likelihood
of agreement with others’ ratings than someone who is low on self-awareness. Without self-
awareness, learning and development translate into mindless reactions to the environment (Briscoe
& Hall, 1999). According to Hogan, Hogan, and Kaiser (2010), lack of self-awareness is the single
biggest factor in managerial derailment.
This factor of learning agility was incorporated in the viaEDGE self-assessment (see Figure 2).
The Choices multirater assessment and the interview protocol (referred to as Learning From
) also were modified to incorporate this additional factor. De Meuse et al. (2011)
defined this fifth factor as,
Self-awareness: the depth to which individuals know themselves, recognizing their skills, strengths,
weaknesses, blind spots, and hidden strengths.
TALENTx7 Assessment
Another self-assessment of learning agility was launched in 2015. The authors defined learning
agility as “the ability and willingness to learn quickly, and then apply those lessons to perform well
in new and challenging leadership situations” (De Meuse & Feng, 2015, p. 3). This definition is very
similar to the one proposed by Lombardo and Eichinger (2000). However, based on a review of
recent research in the leadership and talent-management areas, the authors of the TALENTx7
Assessment incorporated the following two additional facets of learning agility: (a) “feedback
responsiveness” and (b) “environmental mindfulness.” See Figure 3. The research literature appears
to support both of these facets of learning agility.
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
With regard to “feedback responsiveness,” Sheldon, Dunning, and Ames (2014) found that
high-performing managers were much more likely to take corrective actions based on feedback than
low-performing ones. In other words, self-awareness was not enough. Many managers hold overly
optimistic perceptions about their expertise and performance; this is particularly prevalent among
those least skilled (Church, 1997). When given feedback, Sheldon et al. observed low performers
tended to disparage either the accuracy or the relevance of the feedback. Those individuals
expressed much more reluctance than top performers to pursue various paths to self-improvement.
Feedback seems to be especially important when situations are novel or ambiguous, such as in
role promotions or new organizational settings (Brett, Feldman, & Weingart, 1990;Morrison, 1993).
Figure 2. Revised model of learning agility, which includes a separate “self-awareness” factor (De
Meuse et al., 2011). See the online article for the color version of this figure.
Figure 3. Seven-factor model of learning agility (De Meuse & Feng, 2015). See the online article for
the color version of this figure.
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Obtaining others’ feedback can help identify lessons from experiences that otherwise would go
unrecognized if the individual were left to process and interpret the experiences on his or her own.
Scholars long have acknowledged the critical role feedback and reflection play in the leadership-
development process (Bennis, 1989;Shamir & Eilam, 2005).
Indeed, the importance of seeking and responding constructively to feedback has been discussed
by other researchers within the context of learning agility (cf. Carette & Anseel, 2012;Mitchinson
et al., 2012). McCall (1998) found that high-potential leaders accumulate a track record of success,
which can lead some of them to become overly confident in their own competencies and skills and
less open to feedback. According to De Meuse and Feng (2015), this additional element of learning
agility focuses directly on taking initiative to enhance skills and alter behaviors once self-awareness
occurs. It is defined as,
Feedback responsiveness: the extent to which individuals solicit, listen to, and accept personal feedback
from others, carefully consider its merits, and subsequently take corrective action for performance
Research also suggests that another factor identified by De Meuse and Feng (2015) likely plays
a role in learning agility. The concept of mindfulness has received considerable attention for a long
time in clinical psychology and the personality literature. During the past few years, it has received
some consideration in the industrial-organizational-psychology and talent-management communi-
ties as well (cf. Hyland, Lee, & Mills, 2015). According to a recent article in the Journal of Applied
Psychology, mindfulness is “a state of nonjudgmental attentiveness to and awareness of moment-
to-moment experiences” (Hulsheger, Alberts, Feinholdt, & Lang, 2013, p. 310). According to Lee
(2012), leaders who give others their full, open, and nonjudgmental attention to the present moment
and situation are more effective than their counterparts.
In a model proposed by Shapiro, Carlson, Astin, and Freedman (2006), the practice of internally
attending to situations with an open and nonjudging attitude causes a significant change in
perspective. The authors called this concept “reperceiving.” When individuals are able to reperceive
through mindfulness, it distances them from the content of their awareness enabling them to see their
experience of the present moment with greater clarity and objectivity. Likewise, Daniel Kahneman
(2011) addressed the importance of heuristics in his book Thinking, Fast and Slow. Although there
are extraordinary benefits of fast, intuitive, and emotional thinking, it often leads to many perceptual
biases and faulty decisions. Slower, more deliberate, and more logical thinking (i.e., mindfulness)
guards individuals against the mental glitches that frequently get them into trouble. Researchers
have observed that mindfulness is associated with more effective interpersonal communication and
team management (Sadler-Smith & Shefy, 2007;Ucok, 2006) and resilience to adversity (Keng,
Smoski, & Robins, 2011).
Bazerman (2014) coined the rule of WYSINATI (i.e., “What You See Is Not All There Is”). He
asserted that successful leadership requires vigilance. Leaders frequently fail to notice when (a) they
are obsessed with other issues or crises, (b) they are motivated not to notice, and (c) other individuals
work hard to prevent them from noticing. According to De Meuse and Feng (2015), mindfulness is
proactive. It is being mentally engaged and aware of one’s environment; it occurs before an event
or behavior occurs. In contrast, reflection occurs after an event or behavior occurs. Both components
of learning agility would seem important.
Ruderman and Clerkin (2015) concluded that “mindfulness could be very helpful in developing
high potentials” (p. 697). Precisely how and why mindfulness facilitates growth in a leader is
unknown, however. Lazar and her colleagues (2005) observed that an 8-week mindfulness-training
program affected certain areas of the brain associated with learning, memory, cognition, empathy,
compassion, perspective taking, and emotional regulation. Overall, mindfulness may be a cognitive
skill that enhances an individual’s ability to learn from experiences; hence, it’s directly related to
learning agility. McCall and McCauley (2014) asserted that simply giving high-potential leaders
learning experiences does not guarantee they will grow in capability. De Meuse and Feng (2015)
contended that mindfulness provides a cognitive framework to help enable high potentials draw out
the meaning of work experiences. Research findings also suggest mindfulness is distinct from
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
constructs such as openness to experience and emotional intelligence (Baer, Smith, Hopkins,
Krietemeyer, & Toney, 2006). It can be defined as,
Environmental mindfulness: the level to which individuals are fully observant of their external surround-
ings, are attentive to changing job duties and requirements in new organizational roles, and approach
environmental changes in a nonjudgmental and in-the-moment manner.
Thus, environmental mindfulness focuses on external stimuli whereas self-awareness concen-
trates on internal stimuli. Although the facet of mindfulness may be related to the “people agility”
factor as well as “self-awareness,” it likely contributes additionally to an individual’s overall level
of learning agility. According to De Meuse and Feng (2015), a measure of “environmental
mindfulness” incorporated into an assessment provides unique information that is helpful when
ascertaining an individual’s learning agility.
Burke Learning Agility Inventory
The Burke Learning Agility Inventory assessment is based on a model that is similar to the
foundational elements of the viaEDGE and TALENTx7 instruments of learning agility (see De
Meuse et al., 2011;De Meuse & Feng, 2015). The authors defined learning agility as “the
willingness and ability to reconfigure activities quickly to meet changing demands in the task
environment” (Burke, Roloff, & Mitchinson, 2016, p. 2). They likewise posited that learning agility
was an integration of motivation and skill to learn from experience and that learning-agile
individuals adjust their behaviors as situations change. They concurred that leadership potential is
captured by measuring the capacity to learn new knowledge, skills, and behaviors that equip
individuals to respond successfully to future challenges (see Figure 4). Although the factor labels are
different, the underlying facets of learning agility that are measured seem similar to the above two
self-assessments. For example, rather than calling a factor “change agility” (viaEDGE) or “change
alacrity” (TALENTx7), it is referred to as “experimenting” by the Burke Learning Agility Inventory
or BLAI (see Table 1).
There are a few distinctive difference among the three measures, however. For example, the
BLAI uses two separate factors— collaborating and interpersonal risk-taking—to assess interper-
sonal relations. In addition, the factor labeled as flexibility in the BLAI appears to be conceptualized
somewhat differently. It is referred to as mental agility and cognitive perspective in viaEDGE and
the TALENTx7, respectively. In both of those assessments, the underlying focus is to measure the
degree to which an individual collects and processes data. The BLAI appears to focus not only on
how data are collected and processed but also on the extent to which an individual possesses
behavioral flexibility to perform differently across situations.
The largest difference among the three assessments involves how important the roles of
speed and information gathering are in learning agility, however. The BLAI measures these
concepts as separate factors. The first factor is defined as,
Speed: the degree to which individuals act on ideas quickly, so that those not working are discarded and
other possibilities are accelerated.
Performance Risk Taking
Interpersonal Risk Taking LEARNING AGILTY
Information Gathering
Feedback Seeking
Figure 4. Nine-factor model of learning agility (Burke et al., 2016). See the online article for the color
version of this figure.
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
The authors argued that the changing dynamics of today’s workplace require leaders to be able
to respond swiftly. In fact, Burke and his colleagues (2016) asserted that learning agility is not only
needed for managers and executives but by any employee who “wishes to thrive in the face of
change” (p. 1). A few other authors have agreed that cognitive speed is an important element of the
construct of learning agility (cf. DeRue et al., 2012). However, some researchers have found that
speed, which is a major component of intelligence, was unrelated to learning agility (cf. Connolly
& Viswesvaran, 2002;De Meuse, Dai, & Marshall, 2012).
In addition, the BLAI measures the factor information gathering. This aspect of learning agility
is defined as,
Information gathering: the extent to which individuals remain current in their areas of expertise by
attending training courses and conferences, seeking additional education, and becoming members of
professional organizations.
This factor appears to be related to the areas of mastery and learning (Dweck & Leggett, 1988),
as well as one’s learning-goal orientation (Dweck, 1986;VandeWalle, 2001). Learning-goal
orientation is viewed as an important motivational characteristic. Individuals who possess learning
as a goal seek to develop competence by gaining new skills and mastering tasks. In contrast,
individuals who have performance-goal orientation tend to avoid situations that reveal what they do
not currently know. Thus, Burke et al. (2016) would contend that high-learning agile individuals
would have a high score on “information gathering.”
Other Learning-Agility Assessments
All measures of learning agility use one of the following three methodologies: (a) structured,
behavioral interviews; (b) multirater surveys; or (c) online self-assessments. As mentioned, the three
instruments reviewed above all are self-assessments and approach the construct of learning agility
similarly. Nevertheless, there are other assessments in the marketplace. For example, CCL has
developed Prospector
—a multirater survey that measures only two factors of learning agility. The
Development Dimensions International (DDI) consulting firm markets the Leadership Potential
Inventory—a multirater survey that measures four factors of learning agility. The consulting firm
ChangeWise markets the Leadership Agility 360
—a multirater instrument that measures three
“action arenas” and four kinds of “leadership agility.” In addition, there are “homemade” instru-
ments that specific organizations have developed; these define and assess learning agility in a
slightly different manner. The advantages and disadvantages of such an assortment of definitions
and measures are discussed later in this article.
Table 1
Learning Agility Factor Comparisons Among Three Assessments
People agility Interpersonal acumen Collaborating
Interpersonal risk taking
Change agility Change alacrity Experimenting
Results agility Drive to excel Performance risk taking
Mental agility Cognitive perspective Flexibility
Self-awareness Self-insight Reflecting
Feedback responsiveness Feedback seeking
Environmental mindfulness ______________
Information gathering
Note. BLAI Burke Learning Agility Inventory.
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Exploring the Theoretical Underpinnings of Learning Agility
The necessity for leaders to alter managerial style as situations change has been recognized for
decades (e.g., Fiedler, 1967;Vroom & Yetton, 1973). Further, it has been widely accepted that
different competencies, behaviors, decision styles, and supervisory approaches are required when
leaders transition up the organizational ladder (Brousseau, Driver, Hourihan, & Larsson, 2006;
Charan, Drotter, & Noel, 2001;Tannenbaum & Schmidt, 1958). Successful managers evolve and
grow from their experiences. They are able to let go of old habits and ways of performing their jobs
and willingly latch on to new techniques and supervisory practices that are needed (Fiol & Lyles,
1985;Freedman, 1998). They are malleable; they can recast their identities. Perhaps, this is the key
reason why the application of learning agility has been so appealing in the business world.
In addition, research on executive leadership suggests strongly that “learning from experience”
is related to leadership effectiveness. A recent review of the literature on high-potential talent
reinforced the importance of a learning component to high-potential identification (Silzer & Church,
2009). Other scholars likewise have declared that building and diversifying one’s skill set and
engaging in continuous learning are essential for career success in today’s economy (Eby, Butts, &
Lockwood, 2003). Whether one calls the learning-agility factor “people agility” or “interpersonal
acumen,” a good leader must interact effectively with a diversity of people and understand their
strengths and weaknesses when assigning work (Goleman, 1995;Mumford, Zaccaro, Harding,
Jacobs, & Fleishman, 2000). Likewise, whether one uses the factor label “self-awareness” or
“self-insight” or “self-reflection,” the importance of knowing oneself and his or her capabilities and
limitations for leadership success seems well established (Anseel, Lievens, & Schollaert, 2009;
Bennis & Thomas, 2002;Day & Harrison, 2007).
A Model of Learning Agility
Despite the strong conceptual roots of learning agility, there remains much disagreement among
researchers and practitioners alike with regard to its precise definition, how to measure it, and how
it relates to other psychological constructs. In addition, there is lack of clarity about how learning
agility relates to leadership development and leader success. Most definitions of the construct
assert— either explicitly or implicitly—that learning from experience is a critical component
(DeRue et al., 2012;Lombardo & Eichinger, 2000). Likewise, most definitions include both an
ability and willingness component (Burke et al., 2016;De Meuse et al., 2010;Lombardo &
Eichinger, 2000). Finally, most definitions appear to imply that learning agility is important for
leadership roles (De Meuse & Feng, 2015). (This point will be addressed in more detail in the
Discussion section.) Thus, learning agility is defined here as “the ability to learn from experience,
and then the willingness to apply those lessons to perform successfully in new and challenging
leadership roles.”
Although the linkage of learning agility to leader success is implied repeatedly in the literature,
the nature of the relationship is unclear. Figure 5 presents a simple model, proposing that learning
agility directly affects leadership development, which in turn impacts leader success. The model also
proposes that learning agility affects leader success. Consequently, learning agility is posited to
enhance leadership development, as well as have a direct effect on leader success. The implication
of this model is that learning agility is a useful indicator of whom to place into emerging-leader
programs or on high-potential talent lists, because those employees likely will benefit most from
such developmental experiences. In addition, learning agility is a valuable predictor of success when
selecting individuals for leadership roles.
Figure 5. The relationship between learning agility, leadership development, and leader success.
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Learning Agility and the Big Five Personality Traits
Although learning agility is a behaviorally oriented construct according to many authors (Lombardo
& Eichinger, 2000;De Meuse et al., 2010), it likely is related to various personality traits. Figure
6presents hypothesized relationships between the Big Five personality factors and learning agility.
Some specific facets of learning agility probably are linked to one or more of those five core
personality traits as well. However, identifying which traits may be related to which specific facets
of learning agility is not possible at this time given the paucity of empirical research evidence. Each
of the Big Five personality traits is reviewed as it may relate to learning agility in the following
paragraphs. Future researchers can support or eliminate the proposed linkages.
Openness to experience. Openness is a general appreciation for art, adventure, unusual ideas,
imagination, inquisitiveness, and a variety of experiences. Individuals who are open to new
experiences are intellectually curious, experimentally inclined, and willing to try different things.
They are likely to hold unconventional beliefs. An individual who has a high overall openness score
is interested in learning and exploring new cultures, environments, and activities. Further, people
who are low on this trait are frequently much more traditional and may struggle with abstract
thinking. Hence, it is hypothesized that openness to experience is strongly related to overall learning
agility, particularly for the facets of change and mental agility.
Extraversion. Extraversion is characterized by pronounced activity with the external world.
Individuals who are extraverts enjoy interacting with people, participate in a breadth of activities,
and often are perceived as full of energy. They tend to be enthusiastic, action-oriented, assertive, and
possess high group visibility. In contrast, introverts have lower social-engagement and energy levels
than extraverts. Those individuals tend to be quiet, deliberate, and less involved in the social world.
Consequently, it is hypothesized that extraversion is related to those components of learning agility
pertaining to interpersonal interaction such as understanding people and cooperation that leverage
their behavioral inclinations and work preferences (e.g., people agility, interpersonal acumen,
Conscientiousness. Conscientiousness is the tendency to act dutifully, possess self-discipline,
and display a high level of thoughtfulness. It is related to the way in which people control, regulate,
and direct their impulses. Individuals with high scores on conscientiousness tend to be organized,
planful, procedural, and detail-oriented. In contrast, individuals who are high on learning agility tend
to embrace complexity; examine issues from a broad, high-level perspective; and tend to be
nonlinear thinkers. They are much more strategic than tactical. Thus, it is hypothesized that
conscientiousness is negatively related to the overall construct of learning agility. In particular, such
factors as cognitive perspective or mental agility are inversely correlated with conscientiousness.
Agreeableness. Agreeableness reflects individual differences with respect to social harmony.
Individuals who have a high agreeableness score value getting along with others. They generally are
kind, considerate, trusting, helpful, and altruistic. They are cooperative and willing to compromise
their interests with others. Individuals who are low in agreeableness, on the other hand, tend to be
more competitive and even manipulative. They often place self-interest above getting along with
others. At times their skepticism about others’ motives causes them to be suspicious, unfriendly, and
Openness to Experience
Conscientiousness LEARNING AGILTY
Figure 6. Hypothesized relationships between the Big Five personality traits and learning agility. See
the online article for the color version of this figure.
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
uncooperative. Consequently, it is proposed that agreeableness is positively correlated with learning
agility, especially those facets that focus on interpersonal relationships.
Neuroticism. Neuroticism is a trait characterized by sadness, moodiness, and emotional
instability. Individuals who are high on this trait tend to experience mood swings, anxiety, anger,
irritability, and depression. According to Eysenck’s theory of personality (1967), neuroticism is
interlinked with low tolerance for stress or aversive stimuli. Individuals who score high on
neuroticism are emotionally reactive and vulnerable to stressful situations. In contrast, individuals
who score low in neuroticism are less easily upset, less anxious, and more resilient. Research
indicates that individuals who are learning agile are continuously trying new activities, experiment-
ing, and stretching their capabilities. Frequently, they learn most from experiences in which they
fail: situations that are stressful. Therefore, it is hypothesized that neuroticism is negatively related
to learning agility (see Figure 6).
The Empirical Linkage Between Learning Agility and Leader Success
There are relatively few empirical studies that have examined the specific relationship between learning
agility and leader success despite the long history of conceptual research promulgating the idea that
effective leaders learn and evolve as they climb the organizational ladder. Regardless of the amount of
attention given to learning agility on websites and blog postings, and its increasing usage in the business
world, the scientific support of the importance of learning agility to leader success seems to be scanty.
Therefore, a concerted attempt was made to locate all studies that have collected data to investigate the
relationship between learning agility and leader success. All empirical studies were included regardless
of how learning agility was assessed or leader success was measured. In the following two sections, the
methodology used to identify the studies and observed results are presented.
Initially, an extensive literature search of the PsycINFO, ProQuest, and Google Scholar databases
was conducted. A cursory search of Google also was performed to capture any additional studies
that might have been overlooked. Only empirical studies collecting and analyzing data were
included. The goal was to identify any study—published or unpublished— examining the explicit
link between learning agility and leader success. In total, a pool of 19 field studies was identified.
Seven (37%) were published in academic journals, three (16%) were doctoral dissertations, and nine
(47%) appeared in technical reports and white papers. The specific outlet, number and type of
participants, the instruments used to measure learning agility and leader success, and results for each
study were recorded (see Table 2).
In total, 4,863 participants were used in the 19 studies. The majority of them were identified clearly
as managers and executives (n3,294; 68%). However, some of the participants appeared to be
individual contributors, with occupations such as engineer, physician, and law-enforcement officer
(n138; 3%). The remaining participants were classified by the authors of the studies as a
combination of both managers and nonmanagers (n1,431; 29%).
Several different instruments were used to measure learning agility. Eleven (58%) of the studies
used self-assessments, with viaEDGE used in six, the TALENTx7 and BLAI in one study each, and
authors for three of the studies having developed their own instrument to assess learning agility. A
total of nine studies applied multirater approaches to assess learning agility, the majority of them
using the Choices instrument. One study used a self-assessment, a multirater assessment, and an
interview protocol to measure the construct (Dai, De Meuse, & Lambrou, 2012).
Leader success was measured in a variety of ways. However, nearly all—15 of the 19
studies— used ratings of current performance or potential or both as the criterion. In most cases, the
immediate supervisor provided the ratings. In a couple of studies, objective outcomes were used. For
example, Dai, De Meuse, & Tang (2013; Study 2) contrasted learning-agility scores with (a) the
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Table 2
Empirical Studies Investigating the Relationship Between Learning Agility and Leader Success
Study Outlet Participants
Measure of Learning
Agility Measure of Success Results
Bedford (2011) Dissertation 294 individual contributors,
supervisors, managers,
and executives in 10
different companies
Self-developed 9-item
scale (coefficient
alpha .93)
Supervisory ratings of
1. Performance r.78 (p.01)
2. Potential r.77 (p.01)
Burke, Roloff, &
Mitchinson (2016)
White paper 130 candidates for
executive positions in
the wealth-management
Burke Learning
Agility Inventory
Rating of probability
of success made by
recruiting firm
r.42 (p.05)
Clark (2014) Technical report 20 global vice presidents in
viaEDGE self-
Multirater survey of
r.27 (ns)
Connolly (2001) Dissertation 107 law-enforcement
Choices multirater
Supervisory ratings of
1. Performance r.40 (p.001)
2. Promotability r.37 (p.001)
Dai, De Meuse, Clark,
& Cross (2011)
Study 1
Technical report 1,713 managers in global
pharmaceutical company
Choices multirater
Supervisory ratings of
1. Performance r.34 (p.001)
2. Potential r.40 (p.001)
Random sample of 76
One year later
1. Performance r.49 (p.01)
2. Potential r.45 (p.01)
Dai, De Meuse, Clark,
& Cross (2011)
Study 2
Technical report 451 cross-section of
employees in consumer-
products firm
Choices multirater
Current performance-
appraisal rating
r.37 (p.001)
(table continues)
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Table 2 (continued)
Study Outlet Participants
Measure of Learning
Agility Measure of Success Results
Dai, De Meuse, &
Lambrou (2012)
Technical report 12 physicians in a large
health-care network
Interview protocol Composite
promotability rating
given by hospital
r.36 (ns) Interview
Choices multirater
r.91 (p.01) Choices
viaEDGE self-
r.36 (ns) viaEDGE
Dai, De Meuse, &
Tang (2013) Study 1
Journal of Managerial Issues 101 managers in a global
consumer-products firm
viaEDGE self-
1. Supervisory ratings
of leadership
r.29 (p.01)
2. Total compensation r.38 (p.01)
3. CEO proximity r.25 (p.05)
Dai, De Meuse, &
Tang (2013) Study 2
Journal of Managerial Issues 83 district sales managers
in a global
pharmaceutical company
viaEDGE self-
1. Promotions during
10-year period
r.44 (p.01)
2. Average annual
salary increase
during 10-year
r.35 (p.01)
De Meuse (2016) Technical report 28 managers in a high-
potential program
Supervisory ratings of
overall performance
r.31 (p.10)
De Meuse, Dai, &
Marshall (2012)
Technical report 19 engineers and 17 project
managers in a global
industrial corporation
viaEDGE self-
Supervisory ratings of
overall performance
r.12 (ns) Engineers
r.35 (p.10) Proj. Mgrs.
Dries, Vantilborgh, &
Pepermans (2012)
Personnel Review 63 managers and
executives in 7 Belgian
organizations, spanning 4
industries (telecom,
distribution, ICT, and
Choices assessment
using only ratings
from direct
Supervisory ratings of
overall performance
r.35 (p.001) Hipo’s
r.59 (p.01) Non-Hipo’s
(table continues)
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Table 2 (continued)
Study Outlet Participants
Measure of Learning
Agility Measure of Success Results
Eichinger &
Lombardo (2004)
Human Resource Planning 140 managers and
individual contributors in
3 companies (2
insurance and 1
Choices multirater
Performance ratings
r.31 (p.001)
Feil & Dai (2013) Technical report 116 managers from variety
of industries
viaEDGE self-
Supervisory ratings of
1. Performance r.37 (p.01)
2. Potential r.29 (p.01)
Juhdi, Pa’wan, &
Milah (2012)
International Journal of Arts
& Science
329 nonmanagerial and
managerial employees
Self-developed 5-item
scale (coefficient
alpha .78)
Self-ratings of
1. Job engagement r.38 (p.01)
2. Organization
r.49 (p.01)
3. Turnover intention r.08 (ns)
4. Drive for high perf. r.55 (p.01)
5. Leadership spirit r.61 (p.01)
Lombardo &
Eichinger (2000)
Human Resource Management 217 employees (did not
specify level or industry)
Choices multirater
Ratings of
performance and
r.55 (p.001)
Miklos, Herb, &
Forbringer (2015)
White paper 23 health-care executives Multiple raters scored
assessment reports
on (a) speed of
learning, (b)
flexibility with
ideas, and (c)
composite of these
two factors
Supervisory ratings of
overall performance
ß.44 Learning speed
ß.37 Flexibility
ß.46 Composite
(table continues)
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Table 2 (continued)
Study Outlet Participants
Measure of Learning
Agility Measure of Success Results
Smith (2015) Dissertation 142 executive applicants in
finance industry
Learning Agility
Inventory—a self-
Overall evaluation by
executive search
r.43 (p.05)
Spreitzer, McCall, &
Mahoney (1997)
Journal of Applied Psychology 782 managers and
executives from 5
international firms
by supervisor
Supervisory ratings of
1. Performance r.73 (p.001)
2. Potential r.59 (p.001)
3. Job content
r.70 (p.001)
Note. Technically, the Spreitzer et al. (1997) article focused on the ability to learn from experience as a predictor of leader potential. It is included in this review because the 14
dimensions developed in the Prospector instrument correspond closely with the learning-agility construct. The Center for Creative Leadership also markets the instrument as a measure
of learning agility.
Data from the hold-out firm (Company 5) were not included in the results presented here.
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
number of promotions and (b) the average annual salary increases district sales managers had been
given during a 10-year period. Clark (2014) and Dai et al. (2013; Study 1) applied competency
ratings as a proxy of leader success. Burke et al. (2016) and Smith (2015) used a job candidate’s
overall evaluation given by an executive-search firm.
The degree of relationship between learning agility and leader success was measured by
analyzing a study’s correlation coefficient. A total of 40 correlation coefficients were reported in the
19 field studies, ranging from r.08 to .91. Of the 40 coefficients, 33 were statistically significant
at the p.05 level or higher. The following equation was used to compute the mean correlation
coefficient across all 19 studies:
This equation weights each of the 40 coefficients by the respective sample size used in the study
(Hunter & Schmidt, 2004). The overall mean correlation coefficient was r.47 (N10,404, p
.001), which suggests a relatively strong relationship between learning agility and the success of
As stated previously, 11 of the studies used self-assessments of learning agility whereas nine
studies used some form of multirater assessment (one study used both). The mean correlation
coefficient between learning agility and leader success for the studies using self-assessments was
r.46 (n3,302, p.001). The mean coefficient between learning agility and leader success for
the studies applying multirater assessments was r.48 (n7,090, p.001). Thus, there was only
a trivial difference in the findings depending on how the construct was measured.
Fifteen of the correlations examined the specific link between learning agility and leader
performance. Those coefficients ranged from a low of r.12 to a high of r.78, with the mean
correlation of r.47 (n4,023, p.001). With respect to leadership potential, there were 11
correlation coefficients. They ranged from r.29 to .91, with the mean coefficient of r.48 (n
3,396, p.001). See Table 2.
Some of the studies investigated the efficacy of learning agility relative to performance for
predicting potential. For example, Dries, Vantilborgh, and Pepermans (2012) contrasted a group of
32 managers and executives classified as high potentials in seven different organizations with a
carefully matched control group of 31 non-high-potential employees from those same companies.
Independently, each individual’s direct supervisor rated him or her on learning agility; the
performance-appraisal rating from the previous year also was collected. Not surprisingly, the authors
found that high performers were three times more likely to be identified as high potentials than their
low-performing counterparts. However, they also observed that being high on learning agility
increased an employee’s likelihood of being identified as a high potential by a factor of 18. They
concluded that “learning agility is an overriding criterion for separating high potentials from
non-high potentials” (p. 351) and recommended that “organizations should do well to incorporate
measures of learning agility into their high potential identification and development processes” (p.
Dai et al. (2013; Study 1) examined managerial career success and learning agility. Their study
used total compensation and hierarchical proximity (i.e., number of job levels below the CEO) as
indicators of career success. They found that both compensation and CEO proximity were signif-
icantly related to learning agility (r.38, p.01, and r.25, p.05, respectively). The
researchers also observed that learning agility accounted for significant variance in both career
outcomes after controlling for leadership competence. However, contrary to their hypothesis,
leadership competence did not predict career success over learning agility.
A few studies also investigated other variables that might be related to learning agility,
performance, potential, and leader success. For example, Connolly (2001) investigated learning
agility among law-enforcement officers and found that it predicted supervisory ratings of job
performance and promotability beyond what was explained by cognitive ability (intelligence) and
personality (the Big Five factors). In addition, the authors found that learning agility was not
significantly related to IQ or personality.
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Dai et al. (2013; Study 2) investigated promotion rates and average annual salary increases over
a 10-year period and contrasted them to learning agility. They observed that both promotion rate,
r.44, p.01, and average salary increase, r.35, p.01, were significantly related to learning
agility. The results suggest that those managers who were more learning agile ascended the
organizational ladder and increased their income faster than their relatively lower learning-agile
counterparts. Subsequently, the authors administered an emotional-intelligence assessment. They
discovered learning agility provided incremental validity beyond emotional intelligence in predict-
ing promotion rates (R
0.09, p.05) and annual salary increases (R
0.09, p.05).
However, once learning agility was accounted for, emotional intelligence did not explain any
additional variance.
Overall, the body of evidence suggests that learning agility has a fairly robust relationship with
both leader performance and potential. The majority of the correlation coefficients reported in the
19 studies were statistically significant. Participants were employed in a variety of industries,
ranging from financial services, consumer products, pharmaceutical, telecom, electronics, and health
care. The vast majority of participants were managers and executives, individuals occupying the
precise organizational positions learning agility is designed to select and develop. Further, the
instruments applied to assess learning agility and the methods used to measure leader success varied
substantially across the 19 studies.
Many years ago it was estimated that the price of a derailed executive could be as high as $2.7
million (Smart, 1999). This cost certainly has increased since then with escalating executive salaries
and shrinking talent pools. More importantly, the hidden costs of failed leadership in the form of
unmet business objectives, lost clients, and disengaged employees are nearly impossible to calculate.
Bad management at any level causes a number of organizational problems. Perhaps it is why one
of the most talked about concepts in the talent-management and leadership space during the past 15
years has been learning agility. Organizations around the globe have been using it to select and
develop their leaders. Numerous claims of its success can be found on websites, blogs, and
consulting-firm marketing brochures. The practitioner world seems enamored with the concept of
learning agility.
A key objective of this article is to apply a more impartial, scientific perspective when
evaluating the merits of learning agility. What theoretical support does learning agility have? How
does one measure it? Is there empirical evidence demonstrating the linkage between learning agility
and leader success? The prevailing results from the investigation include: (a) yes, scholarly research
supports that learning from experience, experimentation, reflection, mindfulness, flexibility, resil-
iency, responsiveness to feedback, and being sensitive to others’ needs are important for successful
transitions in management; (b) yes, learning agility can be—and has been—measured by a variety
of methods and assessments; and (c) yes, there are hard data and soft data to empirically support that
learning agility is related to the success of leaders.
Unfortunately, this review has also uncovered several issues that make the scientific study and
application of learning agility somewhat challenging. For example, there is no commonly accepted
definition of the term. Measures of learning agility— even the three self-assessments reviewed in the
article— differ substantially. Should the criterion to judge the efficacy of learning agility be leader
performance, leader potential, or outcomes associated with effective leadership? Indeed, one could
argue that the most appropriate criterion to apply is leadership development. To what extent can
learning agility be developed? Is learning agility required (helpful) for all organizational positions
or limited to formal leadership roles? Those issues impact both theory and practice. Each will be
addressed in the following sections.
Lack of Definitional Clarity
There are two distinctly different philosophies to the definition of learning agility in the
literature. Some scholars define the construct narrowly and emphasize primarily the speed of
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
learning and cognitive flexibility (DeRue et al., 2012). Others incorporate “speed of learning”
as a critical component when measuring the learning-agility construct (Burke et al., 2016). For
example, DeRue and his colleagues have defined learning agility as “the ability to come up to
speed quickly in one’s understanding of a situation and move across ideas flexibly in service of
learning both within and across experiences” (pp. 262–263). It appears those authors are
focusing primarily on scanning a situation rapidly, then understanding quickly what needs to be
performed. It is unclear the extent to which the authors are examining how fast an individual
can react, adapt, or respond to changing conditions (e.g., new job roles, duties, assignments) or
the extent to which individuals have the behavioral flexibility to perform differently once they
learn it.
In contrast, other researchers have defined learning agility more broadly and conceptualize
it in terms of a leadership metacompetency (De Meuse, Dai, Swisher, Eichinger, & Lombardo,
2012;Hezlett & Kuncel, 2012;Lombardo & Eichinger, 2000). Such leadership competencies as
dealing with ambiguity, problem-solving, conflict management, critical-thinking skills, and
open-mindedness are involved intimately with learning agility. Those authors posit that the
construct entails both learning from experience and subsequently applying that learning in new
environments or assignments. Thus, this definitional perspective comprises an ability element,
a willingness element, and a cognitive- and behavioral-flexibility element to learning from
Both of these philosophies have merit. Both philosophies are scientific. In some ways, it can
be viewed as using a “microscope” versus using a “telescope” to define and understand the
construct of learning agility. A microscope provides a detailed examination of a tiny grain of
the construct. A telescope, on the other hand, applies a different lens. The construct is viewed
more holistically in an attempt to understand it. It is important to remember that learning agility
as a construct is less than 20 years old. Relative to other established psychological constructs
such as intelligence, personality, motivation, and even leadership itself that have been studied
for many decades, learning agility is in its infancy. It continues to evolve. Scholars have debated
the extent to which mental ability, willingness, cognitive flexibility, and other facets of learning
from experience play a role. For example, if one posits that “speed of learning” is a component
of the construct, then intellect might be important (cf. DeRue et al., 2012;Gottfredson, 1997).
Yet some researchers have found intelligence to be largely unrelated to learning agility
(Connolly & Viswesvaran, 2002;De Meuse et al., 2012). On the other hand, if one postulates
that “willingness” is not a component (cf. DeRue et al., 2012), then one has to ignore the stream
of research findings showing the importance of goal orientation in motivating human learning
(Colquitt & Simmering, 1998;Dweck, 1986). Some researchers have specifically emphasized
willingness as an important element of learning from experience and learning agility (Arun et
al., 2012;Carette & Anseel, 2012;Dominick et al., 2010).
As of now, there is no standard definition of learning agility. Therefore, it seems prudent to
define learning agility more broadly to capture all of its complexity and nuances, recognizing there
may be some loss of conceptual clarity and scientific rigor. In addition, it is important to define
learning agility in a way that it adds value to leadership selection and developmental efforts within
organizations (Hezlett & Kuncel, 2012;Mitchinson et al., 2012). Most academic researchers, as well
as practitioners, agree on the following five points:
1. Conceptualize learning agility in terms of learning from work and life experiences;
2. View it as a multidimensional construct;
3. Suggest it can be used as a key predictor of leadership performance and potential;
4. Recommend learning agility should be considered as an important element in leadership
development; and
5. Encourage additional research to be conducted.
Hence, for parsimony and to capitalize on the construct’s ongoing utility for leadership
identification and development, we define learning agility as the ability to learn from experience,
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
and then the willingness to apply those lessons to perform successfully in new and challenging
leadership roles.
Lack of Consistency in the Measurement of Learning Agility
Given there is no agreed-upon definition of learning agility, it is not surprising there is no one
accepted measure of it. Once it reaches the maturity level of the construct of personality, it likely
will be clearly defined and commonly assessed. There are many widely accepted instruments to use
when measuring personality. Whether one uses the California Psychological Inventory
, 16PF
, or Myers-Briggs Type Indicator
, all will assess various psychological traits of an individ-
ual. The same is true when measuring cognitive ability and intelligence (e.g., Wechsler Adult
Intelligence Scale
, Stanford-Binet Intelligence Scale
). However, scientists have been studying
personality and intelligence for more than a 100 years. Various personality traits and areas of
intellect are clearly defined.
What makes the scientific measurement of learning agility particularly challenging is that
current assessments label similar factors by different names. Furthermore, those factors with similar
names are defined and assessed slightly differently. For example, let’s consider the three self-
assessments reviewed in this article. The viaEDGE assessment uses the factor name “mental agility”
and describes it as “the degree to which individuals think through problems from a fresh point of
view and are comfortable with complexity, ambiguity, and explaining their thinking to others.” The
TALENTx7 Assessment uses the factor name “cognitive perspective” and describes it as “the extent
to which individuals think critically and strategically, approach organizational situations from a
broad high-level viewpoint, and focus on multiple inputs rather than from only one or two
functional/technical perspectives.” The BLAI uses the factor name “flexibility” and describes it as
“the level to which individuals are open to new ideas and proposing new solutions.”
Although it is understandable that different assessment publishers have to honor copyright
restrictions, as well as their desire to distinguish their assessments from others on the market, it
makes the accumulation of scientific knowledge difficult. Most likely, items on those self-
assessments reflect the subtle (and not-so-subtle) differences in factor names. Consequently, it
inhibits the ability to draw conclusions about the importance of various factors across assessments
and across studies. In the future, researchers and practitioners alike will need to clarify and
standardize the underlying essence of those factors to determine the extent to which they are relevant
facets in the learning-agility construct.
Lack of Consistency in the Measurement of Leader Success
Not only is learning agility measured differently across studies, so is the criterion applied to evaluate
leader success. In the review, 15 of the studies used current leadership performance as the criterion
whereas 11 studies used leadership potential as the criterion. Interestingly, no study was located that
measured the effect of learning agility on “leadership development.” In some ways, it appears that
the most direct impact of learning agility is on a leader’s growth and evolution. How much
personal—as well as organizational and industry— knowledge, wisdom, and insight has the indi-
vidual gained over time?
Certainly, it would seem that potential (i.e., future success) is an appropriate metric of learning
agility. Many authors have asserted that learning agility is an early indicator of leadership effec-
tiveness (e.g., De Meuse et al., 2010;Lombardo & Eichinger, 2000;Spreitzer, McCall, & Mahoney,
1997). Indeed, many organizations measure learning agility as part of the annual talent-review
process to identify high-potential talent. However, the measurement of potential as a surrogate of
learning agility has some problems. Many factors outside of an individual’s control can influence
whether he or she is promoted (e.g., the availability of other roles) or succeeds in future positions
(e.g., one’s boss, access to mentors or coaching, an organization’s culture). Further, many personal
characteristics likely unrelated to learning agility may affect an individual’s future success (e.g.,
intellect, self-discipline).
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
To further complicate matters, there is no standard definition of leadership potential among
organizations (cf. Silzer & Church, 2009). Karaevli and Hall (2003) investigated 13 major corpo-
rations, including Boeing, Dell, Eli Lilly, Chase Manhattan, Hewlett Packard, Southwest Airlines,
and Sun Microsystems, and found that none used the same definition of potential. Nevertheless, the
basic question of whether one should judge the efficacy of learning agility in terms of talent potential
or job performance is appropriate to ask. On the one hand, the identification and development of
tomorrow’s leaders are vital for organizations. Hence, the use of learning agility to forecast potential
is relevant. On the other hand, however, the selection of leaders to hire and promote at the present
time likewise is critical. Research on executive leadership indicates that learning from experience is
strongly related to current leader effectiveness (e.g., McCall et al., 1988;Van Velsor & Leslie,
1995). Thus, the measurement of learning agility to gauge how individuals would perform near-term
also is germane.
As mentioned previously, the review of the 19 studies here yielded 15 correlation coefficients
examining the relationship between learning agility and performance and 11 coefficients investi-
gating the relationship between learning agility and potential. The mean coefficient for performance
was r0.47; the mean coefficient for potential was r0.48. Thus, these results suggest that both
performance and potential are about equally related to learning agility. Therefore, it appears that
either criterion is appropriate to use for judging the effectiveness of learning agility. Additional
research should be conducted to determine whether those findings continue to be supported. More
importantly, future researchers should try to isolate leadership development from leader perfor-
mance and potential when testing the effects of the learning-agility construct.
The Development of Learning Agility
Scholars have debated whether leaders are born or made for decades. However, the evidence today
is clear. “It is not a matter of whether leaders are born or made. They are born and made” (Conger,
2004, p. 136). Avolio, Rotundo, and Walumbwa (2009) estimated that 30% of leadership is genetic,
whereas 70% is developed. Regardless of the precise percentage, the research reviewed in this article
suggests that leaders do learn, grow, and develop. The role that learning agility plays in this
development and whether learning agility itself can be developed are important questions.
A fundamental assumption by proponents of learning agility is that it can be developed (cf. De
Meuse, 2015;Eichinger, Lombardo, & Capretta, 2010;Lombardo & Eichinger, 2011). If it could
not, individuals would be born with a specific level of the construct. And given that learning agility
is related to leader potential through its linkage with leadership development, many individuals
would be genetically destined to be employed in nonmanagerial positions throughout their careers.
The primary responsibility for talent management would be to identify those employees high in
learning agility and then assign them leadership roles. If the construct is defined in terms of a
metacompetency, however, there is much scientific evidence showing that leadership competencies
can be developed (e.g., London & Smither, 1995;McCall & Hollenbeck, 2002). The entire practice
of 360-degree assessment, feedback, and coaching is based on the premise that individuals can
enhance their competencies and improve their leadership effectiveness. Thus, it appears that
relatively low-agility leaders can develop and evolve to become successful leaders.
Nevertheless, there is very little empirical evidence that learning agility can be modified over
time, since scholars have become interested in examining the construct only recently. Only one
study was located that directly investigated changes in learning agility over time. In this study, 187
managers in a global pharmaceutical company had others rate their learning agility during the
summer of 2010 and again one year later. It was observed that the managers as a group increased
their learning agility one half of a standard deviation or roughly 12 percentile points (Dai, De Meuse,
Clark, & Cross, 2011). It was particularly noteworthy that the managers in the lowest third of
learning agility in 2010 increased the most, while managers in the upper third increased the least.
Caution should be exercised before drawing firm conclusions about these findings since the study
included no controls for a manager’s commitment to change, the extent of the boss’s support for
such change, or the culture and structure of the organization and its possible influence on learning
agility. Regression to the mean also might have played a role in the results. Obviously, much more
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
research is required before drawing any scientific conclusions about the degree to which learning
agility can be increased.
Learning Agility—Leadership Positions or All Jobs
Finally, there appears to be some disagreement whether learning agility is required for all positions
in the workforce or is limited primarily to formal leadership roles. Numerous studies have shown
that ability to learn from experience is what differentiates successful managers and executives from
unsuccessful ones. As managers climb the organizational ladder, new competencies become im-
portant to job success and former— once valuable— competencies often become impediments (cf.
Benjamin & O’Reilly, 2011;Charan et al., 2001;Goldsmith, 2007). Leaders must recognize how
higher leadership positions demand different skills and behaviors, and they must also possess the
flexibility (i.e., agility) to perform them.
Nonetheless, it should be recognized that being reflective, mindful, nimble, and open to change
would seem to be desirable personal qualities for all employees. Jobs today are more dynamic,
complex, and multifaceted than ever. Organizations are fluid, changing technologies, product lines,
company policies, work procedures, and personnel on an ongoing basis. The old paradigm of
stability, predictability, and permanency is obsolete. Therefore, employees need to change, adapt,
and be versatile. This focus on change is the foundation of adaptive performance. Research indicates
that employees who are adaptable and flexible generally perform better than their counterparts
(Pulakos, Arad, Donovan, & Plamondon, 2000;Shoss, Witt, & Vera, 2012). However, it is
important to note that “adaptability” and “flexibility”—although components of learning agility—
are not the same psychological constructs as learning agility.
In addition, it is highly probable that not all jobs require the same level of learning agility for
incumbents to be successful. For illustration, positions such as data-entry clerk, quality-control
worker, accountant, engineer, and scientist demand conscientiousness, precision, dutifully following
established protocols, and a high degree of functional expertise. Such highly technical and profes-
sional roles are very specialized. In contrast, leadership positions are more strategic and have fewer
proscribed tasks; they require the processing of information quickly, embracing ambiguity, adept
decision making, the ability to see the big picture on issues, and the willingness to take risks when
needed. In general, as one ascends the organizational hierarchy, these roles would seem to become
more prevalent as the importance of technical ability wanes and learning agility increases (see
Figure 7).
The point is that although all jobs require characteristics such as openness, adaptability, and
personal change, not all jobs appear to require learning agility. Interestingly, De Meuse et al. (2012)
found that for a sample of engineers the correlation between performance and overall learning agility
only was r.12 (ns; see Table 2). It also is important to note that some specific factors of learning
agility (e.g., those that pertain to risk-taking, experimenting, and career drive) may not be relevant
to technical jobs in general. Executives and talent-management professionals sometimes confuse
those fast-track, entrepreneurial specialists who drive innovation with those steady performers who
do their jobs dependably and reliably. They confuse organizational positions that need deep
Organizational Level
Required to be
Figure 7. Learning agility across the organizational hierarchy. See the online article for the color
version of this figure.
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
technical expertise and constant attention to detail with roles that require dealing with ambiguity,
being flexible, and understanding others’ needs, preferences, and values. They assume all employees
want to become managers and climb the corporate ladder. Naturally, all employees want to
contribute, grow their careers, and be successful. How they achieve those outcomes is very different,
however. To believe that all employees need to possess a high level of learning agility to be effective
is likely untrue. Additional research to support this viewpoint is needed.
More than a half century ago, Kurt Lewin professed that “there is nothing more practical than a good
theory” (Lewin, 1952, p. 169). In many ways, his message applies to the construct of learning
agility. Practitioners have been using learning agility to identify, select, and develop leadership
talent for many years. Authors of business books and various blogs, marketing websites, and some
management consultants have made many grandiose claims regarding its effectiveness. To advance
the practice of leadership identification and development, scholars should provide new ideas for
understanding and conceptualizing learning agility. Factors of the construct should be clarified and
agreed upon. Instruments designed to measure the construct should become more standardized.
Additional theory and empirical support will provide a scientific foundation to the claims made by
many individuals. Likewise, practitioners should provide scholars with key information and prob-
lems they are experiencing in talent management and leadership. Directors of talent in organizations
should provide access to high-potential employee data and performance, so a more rigorous process
can be applied to understanding the linkage between learning agility and leader success (or
Nevertheless, it is important to remember that learning agility is less than two decades old. The
review of 19 studies in this article found a relatively strong relationship between learning agility and
leader success. The measurement of learning agility is a quantum step forward from using “one’s
guts” to identify and select future leaders. As the construct matures, it will gain more clarity and
standardization. Additional research will be conducted examining its linkage with leader success.
It is hoped this article stimulates additional scholarly interest and research exploring the
construct of learning agility. In many ways, science simply has scratched the surface. More attention
needs to be given to (a) defining it, (b) identifying what factors are included in it, (c) developing
psychometrically sound measures to assess it, and (d) conducting empirical studies to support or
refute the many assumptions surrounding the construct. The identification and development of the
next generation of business leaders is critical in the global economy. Learning agility likely can play
a pivotal role to help organizations do it. However, it needs to be done correctly. Scholars and
practitioners should collaborate to ensure that such talent decisions are based on science rather than
hearsay, innuendo, or unproven managerial techniques.
* Denotes empirical study included in meta-analysis.
Anseel, F., Lievens, F., & Schollaert, E. (2009, August). Reflection as a strategy to enhance performance after
feedback. Paper presented at the Annual Meeting of the Academy of Management, Chicago, Illinois.
Arun, N., Coyle, P. T., & Hauenstein, N. (2012). Learning agility: Still searching for clarity on a confounded
construct. Industrial and Organizational Psychology: Perspectives on Science and Practice, 5, 290 –293.
Avolio, B. J., & Hannah, S. T. (2008). Developmental readiness: Accelerating leader development. Consulting
Psychology Journal: Practice and Research, 60, 331–347.
Avolio, B. J., Rotundo, M., & Walumbwa, F. O. (2009). Early life experiences and environmental factors as
determinants of leadership emergence: The role of parental influences and rule breaking behavior. The
Leadership Quarterly, 20, 329 –342.
Baer, R. A., Smith, G. T., Hopkins, J., Krietemeyer, J., & Toney, L. (2006). Using self-report assessment methods to explore
facets of mindfulness. Assessment, 13, 27–45.
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Bazerman, M. (2014). The power of noticing: What the best leaders see. New York, NY: Simon & Schuster.
*Bedford, C. L. (2011). The role of learning agility in workplace performance and career advancement
(Doctoral dissertation). Retrieved from
Benjamin, B., & O’Reilly, C. (2011). Becoming a leader: Early career challenges faced by MBA graduates.
Academy of Management Learning & Education, 10, 452–472.
Bennis, W. G. (1989). On becoming a leader. New York, NY: Basic Books.
Bennis, W. G., & Thomas, R. J. (2002). Geeks & geezers: How era, values, and defining moments shape leaders.
Boston, MA: Harvard Business School Press.
Bray, D., Campbell, R., & Grant, D. (1974). Formative years in business: A long-term AT&T study of
managerial lives. New York, NY: Wiley.
Brett, J. M., Feldman, D. C., & Weingart, L. R. (1990). Feedback-seeking behavior of new hires and job
changers. Journal of Management, 16, 737–749.
Briscoe, J. P., & Hall, D. T. (1999). Grooming and picking leaders using competency frameworks: Do they
work? An alternative approach and new guidelines for practice. Organizational Dynamics, 28, 37–52.
Brousseau, K. R., Driver, M. J., Hourihan, G., & Larsson, R. (2006). The seasoned executive’s decision-making
style. Harvard Business Review, 84, 110 –121, 165.
*Burke, W. W., Roloff, K. S., & Mitchinson, A. (2016). Learning agility: A new model and measure (Working
Carette, B., & Anseel, F. (2012). Epistemic motivation is what gets the learner started. Industrial and
Organizational Psychology: Perspectives on Science and Practice, 5, 306 –309.
Charan, R., Drotter, S., & Noel, J. (2001). The leadership pipeline: How to build the leadership powered
company. San Francisco, CA: Jossey-Bass.
Church, A. H. (1997). Managerial self-awareness in high-performing individuals in organizations. Journal of
Applied Psychology, 82, 281–292.
Church, A. H., Rotolo, C. T., Ginther, N. M., & Levine, R. (2015). How are top companies designing and
managing their high-potential programs? A follow-up talent management benchmark study. Consulting
Psychology Journal: Practice and Research, 67, 17–47.
*Clark, L. P. (2014). Learning agility and competencies: Does one predict the other? (Tech. Rep. No.).
Chappaqua, NY: Larry Clark Group.
Colquitt, J. A., & Simmering, M. J. (1998). Conscientiousness, goal orientation, and motivation to learn during
the learning process: A longitudinal study. Journal of Applied Psychology, 83, 654 –665.
Conger, J. A. (2004). Developing leadership capability: What’s inside the black box? Academy of Management
Executive, 18, 136 –139.
*Connolly, J. A. (2001). Assessing the construct validity of a measure of learning agility (Doctoral dissertation).
Retrieved from AAI3013189
Connolly, J. A., & Viswesvaran, C. (2002, April). Assessing the construct validity of a measure of learning
agility. Paper presented at the Society for Industrial and Organizational Psychology Conference, Toronto,
Ontario, Canada.
*Dai, G., De Meuse, K. P., Clark, L. P., & Cross, J. (2011). Criterion-related validation of the Choices
Assessment: Findings from two recent studies (Tech. Rep. No.). Minneapolis, MN: Korn Ferry International.
*Dai, G., De Meuse, K. P., & Lambrou, N. (2012). The relationship between learning agility and performance
outcomes for physicians (Tech. Rep. No.). Minneapolis, MN: Korn Ferry International.
*Dai, G., De Meuse, K. P., & Tang, K. Y. (2013). The role of learning agility in executive career success: The
results of two field studies. Journal of Managerial Issues, 25, 108 –131.
Day, D. V. (2000). Leadership development: A review in context. The Leadership Quarterly, 11, 581–613.
Day, D. V., & Harrison, M. M. (2007). A multilevel identity-based approach to leadership development. Human
Resource Management Review, 17, 360 –373.
Delaney, J. T. (2013, September 9). The most in-demand 21st century business skill. Retrieved from www.huff-
De Meuse, K. P. (2015). Enhancing your learning agility: A guidebook to accompany the TALENTx7 Assess-
. Minneapolis, MN: Wisconsin Management Group.
*De Meuse, K. P. (2016). Criterion-related validation study of the TALENTx7 Assessment
(Tech. Rep. No.).
Minneapolis, MN: Wisconsin Management Group.
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
De Meuse, K. P., Dai, G., & Hallenbeck, G. S. (2010). Learning agility: A construct whose time has come.
Consulting Psychology Journal: Practice and Research, 62, 119 –130.
*De Meuse, K. P., Dai, G., & Marshall, S. (2012). The relationship between learning agility, critical thinking,
and job performance: Engineers and project managers (Tech. Rep. No.). Minneapolis, MN: Korn Ferry
De Meuse, K. P., Dai, G., Swisher, V. V., Eichinger, R. W., & Lombardo, M. M. (2012). Leadership
development: Exploring, clarifying, and expanding our understanding of learning agility. Industrial and
Organizational Psychology: Perspectives on Science and Practice, 5, 280 –286.
De Meuse, K. P., Dai, G., Zewdie, S., Page, R. C., Clark, L. P., & Eichinger, R. W. (2011, April). Development
and validation of a self-assessment of learning agility. Paper presented at the Society for Industrial and
Organizational Psychology Conference, Chicago, Illinois.
De Meuse, K. P., & Feng, S. (2015). The development and validation of the TALENTx7 Assessment: A
psychological measure of learning agility. Shanghai, China: Leader’s Gene Consulting.
DeRue, D. S., Ashford, S. J., & Myers, C. G. (2012). Learning agility: In search of conceptual clarity and
theoretical grounding. Industrial and Organizational Psychology: Perspectives on Science and Practice, 5,
258 –279.
DeRue, D. S., Nahrgang, J. D., Hollenbeck, J. R., & Workman, K. (2012). A quasi-experimental study of
after-event reviews and leadership development. Journal of Applied Psychology, 97, 997–1015. http://
DeRue, D. S., & Wellman, N. (2009). Developing leaders via experience: The role of developmental challenge,
learning orientation, and feedback availability. Journal of Applied Psychology, 94, 859 –875. http://
Dominick, P. G., Squires, P., & Cervone, D. (2010). Back to persons: On social-cognitive processes and products
of leadership development experiences. Industrial and Organizational Psychology: Perspectives on Science
and Practice, 3, 33–37.
*Dries, N., Vantilborgh, T., & Pepermans, R. (2012). The role of learning agility and career variety in the
identification and development of high potential employees. Personnel Review, 41, 340 –358.
Dweck, C. S. (1986). Motivational processes affecting learning. American Psychologist, 41, 1040 –1048.
Dweck, C. S., & Leggett, E. L. (1988). A social-cognitive approach to motivation and personality. Psychological
Review, 95, 256 –273.
Eby, L. T., Butts, M., & Lockwood, A. (2003). Predictors of success in the era of the boundaryless career.
Journal of Organizational Behavior, 24, 689 –708.
*Eichinger, R. W., & Lombardo, M. M. (2004). Learning agility as a prime indicator of potential. Human
Resource Planning, 27, 12–15.
Eichinger, R. W., Lombardo, M. M., & Capretta, C. C. (2010). FYI for learning agility. Minneapolis, MN:
Lominger International, A Korn Ferry Company.
Ellis, S., & Davidi, I. (2005). After-event reviews: Drawing lessons from successful and failed experience.
Journal of Applied Psychology, 90, 857–871.
Ericsson, K. A., Krampe, R. T., & Tesch-Romer, C. (1993). The role of deliberate practice in the acquisition of
expert performance. Psychological Review, 100, 363–406.
Eysenck, H. J. (1967). The biological basis of personality. Springfield, IL: Charles C Thomas Publisher.
*Feil, J. K., & Dai, G. (2013). Validity of viaEDGE™ in predicting boss ratings of performance (Tech. Rep.
No.). Minneapolis, MN: Korn Ferry International.
Fiedler, F. E. (1967). A theory of leadership effectiveness. New York, NY: McGraw-Hill.
Finkelstein, S. M. (2003). Why smart executives fail: And what you can learn from their mistakes. New York,
NY: Portfolio.
Fiol, C. M., & Lyles, M. A. (1985). Organizational learning. Academy of Management Review, 10, 803–813.
Freedman, A. M. (1998). Pathways and crossroads to institutional leadership. Consulting Psychology Journal:
Practice and Research, 50, 131–151.
Goldsmith, M. (2007). What got you here won’t get you there. New York, NY: Hyperion.
Goleman, D. (1995). Emotional intelligence: Why it can matter more than IQ. New York, NY: Bantom Books.
Gottfredson, L. S. (1997). Why gmatters: The complexity of everyday life. Intelligence, 24, 79 –132. http://
Hezlett, S. A., & Kuncel, N. R. (2012). Prioritizing the learning agility research agenda. Industrial and
Organizational Psychology: Perspectives on Science and Practice, 5, 296 –301.
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Hogan, J., Hogan, R., & Kaiser, R. B. (2010). Management derailment. In S. Zedeck (Ed.), American
Psychological Association handbook of industrial and organizational psychology (Vol. 3, pp. 555–575).
Washington, DC: American Psychological Association.
Hooijberg, R., Hunt, J. G., & Dodge, G. E. (1997). Leadership complexity and development of the leaderplex
model. Journal of Management, 23, 375–408.
Howard, A., & Bray, D. (1988). Managerial lives in transition: Advancing age and changing times. New York,
NY: Guilford Press.
Hülsheger, U. R., Alberts, H. J. E. M., Feinholdt, A., & Lang, J. W. B. (2013). Benefits of mindfulness at work:
The role of mindfulness in emotion regulation, emotional exhaustion, and job satisfaction. Journal of Applied
Psychology, 98, 310 –325.
Hunter, J. E., & Schmidt, F. L. (2004). Methods of meta-analysis: Correcting error and bias in research findings
(2nd ed.). Newbury Park, CA: SAGE Publications.
Hyland, P. K., Lee, R. A., & Mills, M. J. (2015). Mindfulness at work: A new approach to improving individual
and organizational performance. Industrial and Organizational Psychology: Perspectives on Science and
Practice, 8, 576 –602.
*Juhdi, N., Pa’wan, F., & Milah, R. (2012). Examining characteristics of high potential employees from
employees’ perspectives. International Journal of Arts & Sciences, 5, 175–186.
Kahneman, D. (2011). Thinking, fast and slow. New York, NY: Farrar, Straus & Giroux.
Karaevli, A., & Hall, D. T. (2003). Growing leaders for turbulent times: Is succession planning up to the
challenge? Organizational Dynamics, 32, 62–79.
Keng, S. L., Smoski, M. J., & Robins, C. J. (2011). Effects of mindfulness on psychological health: A review of
empirical studies. Clinical Psychology Review, 31, 1041–1056.
Lazar, S. W., Kerr, C. E., Wasserman, R. H., Gray, J. R., Greve, D. N., Treadway, M. T.,...Fischl, B. (2005).
Meditation experience is associated with increased cortical thickness. NeuroReport, 17, 1893–1997.
Lee, R. A. (2012). Accelerating the development and mitigating derailment of high potentials through mind-
fulness training. The Industrial-Organizational Psychologist, 49, 23–34.
Lewin, K. (1952). Field theory in social science: Selected theoretical papers by Kurt Lewin. London, UK:
Lombardo, M. M., & Eichinger, R. W. (1989). Preventing derailment: What to do before it’s too late.
Greensboro, NC: Center for Creative Leadership.
*Lombardo, M. M., & Eichinger, R. W. (2000). High potentials as high learners. Human Resource Management,
39, 321–329.
Lombardo, M. M., & Eichinger, R. W. (2011). The leadership machine: Architecture to develop leaders for any
future. Minneapolis, NY: Lominger International, A Korn Ferry Company.
Lombardo, M. M., Ruderman, M. N., & McCauley, C. D. (1988). Explanations of success and derailment in
upper-level management positions. Journal of Business and Psychology, 2, 199 –216.
London, M., & Smither, J. W. (1995). Can multi-source feedback change perceptions of goal accomplishment,
self-evaluations, and performance-related outcomes: Theory-based applications and directions for research.
Personnel Psychology, 48, 803–839.
McCall, M. W., Jr. (1998). High flyers: Developing the next generation of leaders. Boston, MA: Harvard
Business School Press.
McCall, M. W., Jr.. (2010). Recasting leadership development. Industrial and Organizational Psychology:
Perspectives on Science and Practice, 3, 3–19.
McCall, M. W., Jr., & Hollenbeck, G. P. (2002). Developing global executives. Boston, MA: Harvard Business
School Press.
McCall, M. W., Jr., & Lombardo, M. M. (1983). What makes a top executive? Psychology Today, 17, 26 –31.
McCall, M. W., Jr., Lombardo, M. M., & Morrison, A. M. (1988). The lessons of experience: How successful
executives develop on the job. New York, NY: Free Press.
McCall, M. W., Jr., & McCauley, C. D. (2014). Experience-driven leadership development: Surveying the
terrain. In C. D. McCauley & M. W. McCall, Jr. (Eds.), Using experience to develop leadership talent:
How organizations leverage on-the-job development (pp. 3–15). San Francisco, CA: Jossey-Bass.
McCauley, C. D., Ruderman, M. N., Ohlott, P. J., & Morrow, J. E. (1994). Assessing the developmental
components of managerial jobs. Journal of Applied Psychology, 79, 544 –560.
*Miklos, S., Herb, K., & Forbringer, L. (2015). Learning agility in healthcare. Broadview Heights, OH: OE
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Mitchinson, A., Gerard, N. M., Roloff, K. S., & Burke, W. W. (2012). Learning agility: Spanning the
rigor-relevance divide. Industrial and Organizational Psychology: Perspectives on Science and Practice, 5,
Morrison, A., White, R., & Van Velsor, E. (1987). Breaking the glass ceiling: Can women reach the top of
America’s largest corporations? Reading, MA: Addison Wesley.
Morrison, E. W. (1993). Newcomer information seeking: Exploring types, modes, sources, and outcomes.
Academy of Management Journal, 36, 557–589.
Mumford, M. D., Zaccaro, S. J., Harding, F. D., Jacobs, T. O., & Fleishman, E. A. (2000). Leadership skills for
a changing world: Solving complex social problems. The Leadership Quarterly, 11, 11–35.
“Potential: Who’s doing what to identify their best?” (2015). New York, NY: New Talent Management
Pulakos, E. D., Arad, S., Donovan, M. A., & Plamondon, K. E. (2000). Adaptability in the workplace:
Development of a taxonomy of adaptive performance. Journal of Applied Psychology, 85, 612–624.
Reilly, R. R., Dominick, P. G., & Gabriel, A. S. (2014, May). Understanding the unique importance of
self-awareness in leader development. Paper presented at the Society for Industrial and Organizational
Conference, Honolulu, Hawaii.
Ruderman, M. N., & Clerkin, C. (2015). Using mindfulness to improve high potential development. Industrial
and Organizational Psychology: Perspectives on Science and Practice, 8, 694 –698.
Ryan, J. R. (2009, February 27). Learning agility equals leadership success. BusinessWeek Online.
Sadler-Smith, E., & Shefy, E. (2007). Developing intuitive awareness in management education. Academy of
Management Learning & Education, 6, 186 –205.
Shamir, B., & Eilam, G. (2005). What’s your story? A life-stories approach to authentic leadership development.
The Leadership Quarterly, 16, 395–417.
Shapiro, S. L., Carlson, L. E., Astin, J. A., & Freedman, B. (2006). Mechanisms of mindfulness. Journal of
Clinical Psychology, 62, 373–386.
Sheldon, O. J., Dunning, D., & Ames, D. R. (2014). Emotionally unskilled, unaware, and uninterested in learning
more: Reactions to feedback about deficits in emotional intelligence. Journal of Applied Psychology, 99,
Shoss, M. K., Witt, L. A., & Vera, D. (2012). When does adaptive performance lead to higher task performance?
Journal of Organizational Behavior, 33, 910 –924.
Silzer, R., & Church, A. H. (2009). The pearls and perils of identifying potential. Industrial and Organizational
Psychology: Perspectives on Science and Practice, 2, 377–412.
Smart, B. D. (1999). Topgrading: How leading companies win by hiring, coaching, and keeping the best people.
Upper Saddle River, NJ: Prentice Hall.
*Smith, B. C. (2015). How does learning agile business leadership differ? Exploring a revised model of the
construct of learning agility in relation to executive performance (Doctoral dissertation). Retrieved from
Snell, R. (1992). Experiential learning at work: Why can’t it be painless? Personnel Review, 21, 12–26.
*Spreitzer, G. M., McCall, M. W., Jr., & Mahoney, J. D. (1997). Early identification of international executive
potential. Journal of Applied Psychology, 82, 6 –29.
Sternberg, R. J. (1985). Beyond IQ: Toward a triarchic theory of intelligence. New York, NY: Cambridge
University Press.
Sternberg, R. J. (1997). Successful intelligence. New York, NY: Plume.
Sternberg, R. J., Wagner, R. K., Williams, W. M., & Horvath, J. A. (1995). Testing common sense. American
Psychologist, 50, 912–927.
Tannenbaum, R., & Schmidt, W. H. (1958). How to choose a leadership pattern. Harvard Business Review, 36,
Ucok, O. (2006). Transparency, communication, and mindfulness. Journal of Management Development, 25,
1024 –1028.
VandeWalle, D. (2001). Goal orientation: Why wanting to look successful doesn’t always lead to success.
Organizational Dynamics, 30, 162–171.
Van Velsor, E., & Leslie, J. B. (1995). Why executives derail: Perspectives across time and culture. Academy
of Management Review, 9, 62–72.
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Vroom, V. H., & Yetton, P. W. (1973). Leadership and decision making. Pittsburgh, PA: University of Pittsburg
Yammarino, F. J., & Atwater, L. E. (1997). Do managers see themselves as others see them? Implications of
self-other rating agreement for human resources management. Organizational Dynamics, 25, 35–44. http://
Received November 26, 2016
Latest revision received July 29, 2017
Accepted August 13, 2017
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
... Earlier research has revealed the importance of employee learning as a prerequisite to fine-tune one's expertise and to cope with rapid competences obsolescence ( Van der Heijden et al., 2016). As organizations become more complex and dynamic, individuals' ability and agility to learn from experience become more important: knowledge and skills of employees are to be constantly developed, in order to be in line with emergent changes (De Meuse, 2017). ...
... Recently, the concept of learning agility has attracted considerable attention from human resource professionals and consultants interested in talent identification and management (De Meuse, 2017;Lombardo & Eichinger, 2000). Organizations today are increasingly focused on talent as strategic asset and competitive advantage for achieving business success; consequently, talent management (TM) has become a topic of considerable debate in the academic literature and a central element of managerial discourse and organizational practices (McDonnell et al., 2017). ...
... Recently, several scholarly articles have been published examining the theoretical and empirical support for it as an important determinant for high-potential talent (Arun et al., 2012;De Meuse, et al., 2010;DeRue et al., 2012a;Mitchinson et al., 2012). Nevertheless, the scientific support of a direct linkage between learning agility and leader success seems to be scanty (De Meuse, 2019;De Meuse, 2017;DeRue et al., 2012b;Hezlett & Kuncel, 2012). ...
Full-text available
The unprecedented complexity and unpredictability of the current business scenario—amplified by the impacts of COVID-19 pandemic—require employees to constantly learn new skills and new ways of performing their jobs. Over the past decades the construct of learning agility has attracted considerable attention from human-resource professionals and consultants interested in talent identification. Organizations have then incorporated the construct into their model of high-potential selection and leadership development, and the term is becoming embedded into the talent-management (TM) lexicon. The specific contribution of the current systematic review is to provide a rigorous critique of the existing literature about learning agility and its applications to talent management, focusing on definition, measurement, and operationalization of the construct. In addition, the relationships between learning agility and other talent management constructs have been also investigated. A literature search on Scopus, Web of Science, and PsycINFO databases was performed. The review process has followed the international Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement guidelines. The initial search identified 250 titles. Fifty-two studies were assessed, and 10 empirical studies (qualitative and quantitative) were considered eligible. Despite the extensive usage of learning agility in organizations, the academic community only recently has become interested in studying the construct. TM research reinforced the importance of learning agility as a key indicator of potential, highlighting learning and growth competences as central components of potential. Nevertheless, a scientific approach to the concept remains still limited. Limitations, practical implications, and directions for future research are also discussed.
... The early development of learning agility emerged in the scholar-practitioner realm when researchers sought to understand how employees learned from experience (Baran, 2017;Bray et al., 1974;De Meuse et al., 2012;De Meuse, 2017Howard & Bray, 1988). According to De Meuse (2017), researchers such as Bray et al. (1974) began to examine how people learned from occupational experiences and how they developed throughout their career trajectory. ...
... However, Bray et al. (1974) observed that without understanding why and how people learn and develop from their occupational experiences, organizations were limited in codifying the experiences that shaped and developed leaders. Without understanding how leaders succeeded and failed, firms were limited in how they selected and predicted the next succession of potential leaders (Dai et al., 2013;De Meuse et al. 2012;De Meuse, 2017;Lombardo et al.,1988;McCall & Lombardo, 1983;McCall et al., 1988). Scholars criticized how organizations selected future leaders based on their past or current performance (known as end-state competencies that were centered on specific job roles in a stable environment) with little regard for selecting for competencies that would predict success in future positions in unpredictable environments Lombardo & Eichinger, 2000;McCall & Lombardo,1983). ...
... The studies found that successful executives who were deliberate about how they learned from their experiences demonstrated a capacity to extract lessons from previous experiences and apply them to new situations. A salient finding is that the second series of studies found that derailed executives failed to learn from experience because they relied heavily on the skills that made them successful in the first place and refused to adapt to the new norms of the environment (De Meuse, 2017;McCall & Lombardo,1983;Lombardo et al., 1988;McCall et al., 1988;Dai et al., 2013;Morrison et al., 1992;Van Velsor & Leslie, 1995). ...
Full-text available
The recent global pandemic in 2020 and numerous other political, economic, social, technological, environmental, and legal factors have heightened the importance of individuals developing emotional intelligence and learning agility. This phenomenological qualitative dissertation research study explored the perceptions of 35 management consultants in North America, South America, Europe, Asia, and Africa regarding learning experiences in new and challenging situations. Qualitative data were analyzed using an inductive and deductive thematic analysis. Two key findings emerged from this study: 1) Emotional intelligence competencies at the individual level facilitate learning new competencies quickly while flexibly integrating lessons from previous experiences into new and challenging situations; 2) Metacognitive Awareness, Self-Efficacy, and Psychological Safety influence learning quickly and flexibility from workplace experience. This study offers insights regarding how emotional intelligence competencies and learning agility enable individuals to transform themselves and adapt new learning behaviors in new and challenging situation and evolving business environments.
... Agile leaders are high-performing individuals (Dai et al., 2013;De Meuse, 2017;Lediju, 2016) who can think outside of the box, produce fast and applicable solutions, and provide flexibility between applications (Hollis, 2017). They are aware of the necessity of developing new skills in the face of rapid change and know how the organization can improve it. ...
... They turn to feedback for the agile leader to have selfawareness, improve their leadership skills and evaluate their performance. In this way, they can review their qualifications, while they perceive more clearly what the employees feel and their deficiencies (Anseel, 2017;De Meuse, 2017;De Meuse et al., 2012). Besides, the agile leader's encouragement of employees' cooperation and knowledge sharing and finding innovative solutions in uncertain situations (Jonier & Josephs, 2007), will provide the opportunity to make positive or negative suggestions that will involve the employees in the management process. ...
Full-text available
The research aims to reveal the effect of teachers’ agile leadership perceptions on their affective occupational commitment and how employee voice plays a mediating role in this effect. The study group of the research consists of 354 teachers working in Istanbul in 2021. The research is carried out according to the relational survey model. Correlation analysis is carried out and tested using the suggested mediation model based on the relationship between the variables to determine the relationship between variables. According to the research findings, the agile leadership characteristics of school principals positively affect their affective occupational commitment. Additionally, mediation analysis showed that employee voice is a partial mediator between agile leadership characteristics and affective occupational commitment. This research contributes to the theory by revealing the important effects of the agile leader in the school. In the light of the findings, the implications of the agile leader, employee voice, and occupational commitment of teachers were discussed, and suggestions were made for future research.
... De Meuse (2017) göre, yüksek değişim çevikliğe sahip olan kişiler değişime hazırlanmak için ilk olarak yenilik konusunu araştırmayla işe başlarlar. Konu hakkında bilgi edinerek ve eğitimler alarak yani kendilerini donanımlı hale getirerek örgütsel değişimde etkin rol alırlar (De Meuse, 2017). Diğer bir ifadeyle değişime kendilerini kolayca uyarlamak için kendilerini hazırlamaktadırlar (Yockey ve Kralowec, 2015). ...
Full-text available
In order to train future nurse leaders and nurses who are successful in their careers, it is predicted in nursing education that the measurement and improvement of learning agility of nurses starting from their student years will make nurses more successful and stronger individually and professionally. The CHOICES scale, which is one of the scales developed to measure learning agility, measures the learning agility of individuals with its 4 sub-dimensions. These four sub-dimensions are; Mental Agility, Agility in Human Relations, Agility in Change and Agility in Creating Results. It is important to use educational models that improve student learning agility in nursing education. Learning agility of nursing students can be improved with educational models like web-based applications and the internet, project-based learning model, flipped classroom model, simulation applications, clinical internship experiences, etc. which facilitate learning based on experiential learning. It is important to provide institutional support for the development of the learning agility of nursing students, to develop the learning agility of the educators separately and to integrate the practices that improve the learning agility for the students into the education system. It is expected that nursing graduates with high learning agility will be able to cope with the difficulties they will encounter in their future business life more easily and more motivated. Extended English summary is in the end of Full Text PDF (TURKISH) file. Özet Hemşirelik eğitiminde geleceğin hemşire liderlerini ve kariyerinde başarılı hemşireleri yetiştirmek için hemşirelerin öğrencilik döneminden başlayarak öğrenme çevikliğini değerlendirme ve geliştirme uygulamaları yapılmasının hemşireleri bireysel ve mesleki profesyonellik bakımından daha başarılı ve güçlü kılacağı öngörülmektedir. Öğrenme çevikliğini ölçmek için geliştirilen ölçeklerin başında gelen CHOICES ölçeği, 4 alt boyutuyla bireylerin öğrenme çevikliğini ölçer. Bahsedilen dört alt boyut; Zihinsel Çeviklik, İnsan İlişkilerinde Çeviklik, Değişimde Çeviklik ve Sonuç Yaratma Çevikliğidir. Hemşirelik eğitiminde öğrencilerin öğrenme çevikliğini geliştirici uygulamaların yapılması önemlidir. Web tabanlı uygulamalar, proje tabanlı öğrenme modeli, ters yüz sınıf modeli, simülasyon uygulamaları, klinik staj deneyimleri vb. öğrenmeyi kolaylaştırıcı ve yaşayarak öğrenmeye dayalı eğitim modelleriyle hemşirelik öğrencilerinin öğrenme çeviklikleri geliştirilebilir. Hemşirelik öğrencilerin öğrenme çevikliklerinin geliştirilmesi için kurumsal desteklerin verilmesi, eğitimcilerin öğrenme çevikliklerinin ayrıca ele alınması ve eğitimcilerin öğrenciler için öğrenme çevikliğini geliştirici uygulamaları eğitim sistemine entegre etmesi önemlidir. Öğrenme çevikliği yüksek mezun hemşirelerin gelecek iş yaşamlarında karşılaşacakları zorluklar ile daha kolay ve güdülenmiş şekilde başa çıkabilmeleri beklenmektedir.
... The model proposed here is suitable for employees at all seniority and proficiency levels. Organizational processes focusing on talent management often concentrate on senior management-for example in high-potential identification and succession-planning processes (Church et al., 2015;De Meuse, 2017). In the current model a wide range of types of employees would benefit from managing personal brand throughout their professional development: at the beginning of their careers, in the process of career change, while actively searching for a new position, or when not actively searching for a new position (passive candidates). ...
... To fulfill this role as professional caregiver requires flexibility and confidence to work outside the known paths. This can be linked to the concept of learning agility, which refers to the ability to learn from experience and the willingness to apply those lessons in a new and complex situation by pursuing self-directed learning, reflection, feedback-seeking and sensitivity to others' needs (De Meuse, 2017;Lee & Song, 2020). This can be achieved by creating a working environment that invests and supports the learning agility of each individual professional caregiver, with room for experimentation and feedback opportunities (Ghosh, Muduli & Pingle, 2020). ...
The PhD dissertation explored: 1) a multilayered image of the dementia experience and dementia care provision among labor migrant families, and 2) methodological pathways to contribute to more ethical research involving this population. The findings of this dissertation are based on five studies. The findings show that the experience of dementia and the dementia care trajectory is defined by the intersectional social position of older labor migrants and their families, inviting us to move beyond the binary division between migrants and non-migrants with “having a different culture” as the division line. This while recognizing the impact of having a migration background, a non-normative culture and religion on care provision. The current dementia care is provided by a complex and dynamic transnational network of informal and formal caregivers that also includes alternative care forms. This picture of care provision is sought by family caregivers as an answer to their unmet care needs: A “complexity-sensitive person-centered responsive care” considers the multilayered identity of the older migrant with dementia. This reflects individual and structural professional care gaps to provide inclusive dementia care. Understanding this complexity can advance the provision of better dementia care for older migrants with dementia. Therefore, a new conceptual lens to examine dementia care for a diverse population is suggested. This dissertation also contributes to the debate on how to conduct ethical research on dementia among older migrants by moving away from the culturalist frame where it is currently embedded with biased and narrow assumptions about this population as a result. This dissertation suggests therefore a further exploration of decolonial frameworks as compass for an ethical gerontological research praxis: a praxis that engages us into a process of awareness of and resistance to the historically rooted coloniality of mind in our own knowledge production.
Full-text available
Transformasi Digital adalah sebuah keniscayaan dan keharusan sebagai sebuah proses alami yang harus dilalui. Perubahan demi perubahan mengantarkan manusia pada titik yang semakin tinggi dengan berbagai inovasi yang diciptakannya. Mesin dan teknologi bukanlah menjadi pesaing yang pantas bagi manusia, mereka adalah ciptaan atas inovasi dan karya manusia agar pekerjaan semakin mudah dan memiliki kualitas dalam menjalani hidup lebih baik. Sehingga dengan kehadiran “teman” baru ini diharapkan paradigma dan persepsi atau cara pandangnya menjadi berbeda. Bersama “teman” ini akan memudahkan bagi manusia dapat terus melakukan eksplorasi dan penghayatan dengan banyak hal menciptakan pengetahuan baru yang akan menambah manfaat dan kualitas hidup bagi umat manusia. Sudah saatnya organisasi mengambil tempat yang tepat meletakkan “teman” ini dapat bersinergi untuk menghadapi VUCA (Volatility, Uncertainty, Complexity, dan Ambiguity) dalam design organisasi digital agar dapat meningkatkan agilitas organisasi dan juga SDM yang berada dalam ekosistem ini, serta dengan memahami data, melakukanan alisis dengan data, dapat dilakukan perkiraan-perkiraan untuk menghadapi tantangan dalam menjaga organisasi tetap mempertahankan keunggulannya di masa yang akan datang. Hal yang terpenting juga adalah bagaimana menyikapi perubahan budaya hingga melakukan perubahan menjadi budaya digital.
Purpose This study aims to focus on assessing the influence of human resource development (HRD) interventions and learning agility (LA) on organizational innovation (OI). Design/methodology/approach Based on the social exchange theory, the theoretical research model was developed in this study. This study used cross-sectional data to test the research hypotheses. In addition, partial least square structured equation modelling was used to analyse 413 sample responses from Indian managerial professionals. Findings The findings suggest that HRD interventions and LA have an effect on OI. Additionally, age as a control factor also influences OI. Practical implications The study’s findings show that an organization must use HRD interventions effectively to improve innovation. Additionally, learning agile employees also helps in bringing innovation to an organization. Originality/value This study is one of its kind in exploring LA for OI by using the existing LA scale. Further, this study is a significant contribution to the existing literature by using HRD interventions, LA and OI in an extensive research model.
Full-text available
During the pandemic era, both students and teachers have to struggle in the teaching and learning process. They have to adjust themselves to the new situation, in which technology application becomes an alternative in conducting the teaching and learning process. This condition requires agility. This study aims to explore the author's experiences in terms of learning agility during the Covid-19 pandemic era, especially in handling a learning management system (LMS) and the students’ anxiety in using the technology. Although the author had implemented blended learning before the pandemic era, when it came to fully online learning, many new things needed to be learned, such as using the LMS application, providing the materials, assessing the students, and motivating the students. Moreover, the author also had to adjust to the students’ conditions from different Yogyakarta areas. The method used in this study was qualitative, using a descriptive approach. The results showed that learning agility is one way to cope with the problems during emergency remote teaching. Nevertheless, this approach could lead to self-resilience. Keywords: agility, Learning Management System (LMS), motivation, resilience
Full-text available
Although learning agility has been used in many companies as an important consideration for selecting high potential talent, very little scholarly research has been conducted on this construct. This paper presents the results of two field investigations - one cross-sectional and one longitudinal. In Study 1, it was found that learning agility was significantly correlated with the following two objective career outcomes: (a) CEO proximity and (b) total compensation. The study also observed a positive relationship between learning agility and ratings of leadership competence. In Study 2, it was found that learning agility was significantly related to career growth trajectory. High learning agile individuals were promoted more often and received higher salary increases than low learning agile individuals over a period of ten years. Implications for talent management and leadership development are discussed.
Full-text available
Hyland, Lee, and Mills (2015) have provided a thorough and much needed overview of the construct of mindfulness within the context of industrial and organizational (I-O) psychology and have offered several reasons why mindfulness programs should be considered in the workplace. In this commentary, we focus on their suggestion that mindfulness may improve the development of high potentials through enhanced self-awareness. We agree that mindfulness is likely an effective tool to help high potentials succeed in an increasingly complex world. We come to this conclusion after conducting a rigorous review of the literature and talking to experts (Ruderman, Clerkin, & Connolly, 2014), learning various forms of mindfulness including completing the mindfulness-based stress reduction (MBSR) program, and our experiences conducting applied leadership research at the Center for Creative Leadership—a 45-year-old organization devoted exclusively to leadership development.
The theoretical framework presented in this article explains expert performance as the end result of individuals' prolonged efforts to improve performance while negotiating motivational and external constraints. In most domains of expertise, individuals begin in their childhood a regimen of effortful activities (deliberate practice) designed to optimize improvement. Individual differences, even among elite performers, are closely related to assessed amounts of deliberate practice. Many characteristics once believed to reflect innate talent are actually the result of intense practice extended for a minimum of 10 years. Analysis of expert performance provides unique evidence on the potential and limits of extreme environmental adaptation and learning.
Personnel selection research provides much evidence that intelligence (g) is an important predictor of performance in training and on the job, especially in higher level work. This article provides evidence that g has pervasive utility in work settings because it is essentially the ability to deal with cognitive complexity, in particular, with complex information processing. The more complex a work task, the greater the advantages that higher g confers in performing it well. Everyday tasks, like job duties, also differ in their level of complexity. The importance of intelligence therefore differs systematically across different arenas of social life as well as economic endeavor. Data from the National Adult Literacy Survey are used to show how higher levels of cognitive ability systematically improve individual's odds of dealing successfully with the ordinary demands of modern life (such as banking, using maps and transportation schedules, reading and understanding forms, interpreting news articles). These and other data are summarized to illustrate how the advantages of higher g, even when they are small, cumulate to affect the overall life chances of individuals at different ranges of the IQ bell curve. The article concludes by suggesting ways to reduce the risks for low-IQ individuals of being left behind by an increasingly complex postindustrial economy.
If people with potential are given the opportunity to engage in strategically relevant experiences, and something is done to ensure that they learn the lessons of those experiences, it increases the probability of having the leadership talent necessary to lead the business strategy. Each of the six elements-strategy, experience, talent, mechanisms for moving across boundaries, catalysts for promoting learning, and the resulting increased leadership ability ("the right stuff")-is a potential leverage point for improving the overall process of developing leadership talent. Some organizations have worked to put experience at the heart of development, or at least to use it more effectively. The chapter gives an outline of the information contained in other chapters of the book. The chapters provide numerous examples for each of the elements of the development-from-experience framework.