Executive Coaching: The Age Factor

By Lois Tamir and Laura Finfer July 06, 2017

Leadership Excellence Consulting, New York, New York

Lifespan psychology suggests that executives in their 30s, 40s, and 50s represent
different maturational levels and professional experience. To date, research has not
explored the relationship between the age of an executive and the coaching process or
coaching outcomes. We hypothesized that executives in these age ranges would respond
differently to the executive-coaching engagement. We analyzed 72 executive-coaching engagements to evaluate the relationship of age to 4 variables: Responsiveness, Self­-reflection, Non-defensiveness, and Degree of Change. Results indicate that the age group 30 to 39 was significantly lower on Self-reflection and Degree of Change compared with executives in the
40 to 49 and 50 to 59 age groups. This may be a function of maturational elements, such as focused ideals and rule-driven behavior to achieve professional stature, and of organizational indicators that they are already placed in a high-potential, elite group. We suggest methods to stimulate both self-reflection and developmental growth unique to the 30 to 39 age group.

Keywords: executive coaching, lifespan, self-reflection, behavioral change

As practitioners of executive coaching, we pursued an investigation of an unexplored variable we suspected would impact the coaching process and outcomes: age. Although there is an abundance of early and classic lifespan literature that addresses adult-development themes (e.g., Erikson, 1950; Gould, 1972; Jaques, 1965; Levinson, 1978; Neugarten, 1976; Vaillant, 1977), the literature hardly ever references age as a variable relevant to coaching (two exceptions are Axelrod, 2005 and Peltier, 2011). However, in our practice, we observed a qualitative difference in the ebb and flow of coaching engagements with executives in their 30s compared with those 40 and older. For this study we investigated a population of 72 documented coaching clients, conducting an analysis of what actually happened during and at the conclusion of these engagements.

Three Age Groups

A comprehensive PsycNET search revealed no recent literature that captures the characteristics of each age decade. However, classic lifespan literature describes the ongoing maturation of the adult by age decades. The decade of the 30s is characterized as a period of intense activity to establish the foundation of a successful career and family (e.g., Levinson, 1978; Vaillant, 1977) and to internalize and master the rules that win approval from the societal context surrounding these efforts (e.g., Loevinger, 1966, 1979). Labouvie-Vief and Hakim-Larson (1989) explained that novice professionals overgeneralize and narrowly interpret these rules. Young adults are described as unidirectional in their focus toward achieving the successes they target, taking cues and counsel from mentors who support them.

Three themes dominate the classic descriptions of this decade. First is idealism. Adults in their 30s value principles about how the world should operate. Second, they adhere to newly acquired rules that define their professions and the professional environment. Third, they wrestle with ambiguity and lean instead toward absolutes. We observed these patterns in our work. For example, a newly minted general counsel, age 32, insisted on the application of strict legal parameters. In contrast, his business partners sought solutions that advanced the business agenda with sound legal ramifications. This dynamic elevated tensions and created logjams.

The decade of the 40s, in contrast, is characterized as the turning point from novice to mentor, with deeper appreciation for life’s puzzles and paradoxes (e.g., Levinson, 1978; Loevinger, 1966; Tamir, 1982a, 1982b, 1989). In an opinion piece in The New York Times, David Brooks (2016) wrote that this group sees the world with more compassion, grasping opposing ideas with greater ease and showing tolerance of ambiguity. This aligns with the literature written decades earlier. In our practice, for example, a 45-year-old CIO who led a massive change effort embraced the ambiguity associated with the resistance that inevitably surfaced. He resourcefully leveraged this resistance as a vehicle for dialogue and a springboard for influence.

The classic literature describes the decade of the 50s as a continuation of the maturation that materialized in the decade of the 40s, including cognitive and emotional flexibility (Labouvie-Vief & Hakim-Larson, 1989), greater tolerance of self and others, and the ability to synthesize discrepant content (Loevinger, 1966, 1979).

Executive Coaching and Age

To investigate the relationship between age and executive-coaching outcomes, we turn next to the coaching literature. Conclusive research on the impact of executive coaching is scant (Feldman & Lankau, 2005) for a number of reasons. First, there is a range of definitions of executive coaching (Greif, 2007; Hamlin, Ellinger, & Beattie, 2008; Ives, 2008; Peterson, 2011). Some are specific and elaborate, detailing roles, responsibilities, process, and methods (see Kampa & White, 2002). Other definitions are broad: “the facilitation of learning and development with the purpose of improving performance” (Bluckert, 2006). Second, approaches to executive coaching vary (Creane, 2006; Peterson, 2011; Whitmore, 2002; Zeus & Skiffington, 2000); this is in part because of the diverse backgrounds of executive coaches, which include different disciplines within psychology, management, training, and teaching (Grant, 2007). Third, executive coaching is a highly confidential process (Coutu & Kauffman, 2009), hence limiting the ability to conduct research. Fourth, success criteria vary (Greif, 2007; Peterson, 2011), are difficult to measure objectively (Greif, 2007), and are assessed in a multitude of ways (Greif, 2007; Passmore & Ellery-Travis, 2011; Peterson, 2011). Fmally, executive coaching is a long-term, complex, evolving process that is customized to the executive (Greif, 2007; Peterson, 2011) and geared to address the needs of multiple organizational stakeholders (Peterson, 2011). Many activities take place concurrently in the coaching context (e.g., organizational initiatives, people changes) that impacts the executive, his or her progress, and even the objectives of the engagement (Coutu & Kauffman, 2009; de Haan, Culpin, & Curd, 2011; Peterson, 2006).

Despite these obstacles, research suggests that executive coaching is a positive and productive experience. Surveys of outcome studies indicate that executive coaching is superior to peer coaching and to no coaching (Greif, 2007; Peterson, 2011). Factors that impact the effectiveness of executive coaching are the quality of the relationship with the coach (Baron & Morin, 2009; Bluckert, 2005; Bush, 2005; Creane, 2006; Dembkowski, Eldridge, & Hunter, 2006; Gyllensten & Palmer, 2007; McKenna & Davis, 2009), clarity about the goals and expectations of the engagement (Feldman & Lankau, 2005; Greif, 2007; Passmore, 2008; Peterson, 2011), and the motivation of the executive (Greif, 2007; Peterson, 2011).

The present study was designed to evaluate age differences in coaching process and outcomes, based on variables discussed in the coaching and lifespan literature. Held constant was the quality of the coach (the two authors, who are licensed Ph.D. psychologists, were originally trained and supervised by accomplished executive coaches such as David B. Peterson, Ph.D., and each has a track record of more than 25 years of trusted client relationships and positive coaching outcomes) and the structure of the coaching engagement (that included the assessment of strengths and development needs, goal setting, and evaluation based on those goals). These constants contribute to positive coaching outcomes (e.g., Greif, 2007; Peterson, 2006, 2011).

Age Ranges or Generations?

As a starting point, we evaluated whether age or generations made the most sense. Age decades do not correspond to generations (e.g., Millennials, GenX, Boomers), and there is no consensus about where these generations begin and end. Costanza and Finkelstein (2015) claimed that empirical evidence for generational differences is weak and no theory exists to support it. In fact, a large-scale study of personality differences yielded few significant generational differences (Foster, 2015) and a recent study of work values found greater support for the influence of age and experience compared to birth generation (Deal et al., 2013). Given the consistency of the classic lifespan literature and validity of that research, we distributed the sample into three age decades: 30 to 39, 40 to 49, and 50 to 59.

Coaching Process and Outcome Variables

We examined four dependent variables linked to the process and outcomes of coaching: Respon­siveness, Self-reflection, Non-defensiveness, and Degree of Change. We developed the definitions and criteria for these variables based on a combination of the coaching literature and our seasoned experience working with executives and supervising coaches.

First, Responsiveness aligns with two of Peterson’s (2006, 2011) “critical accelerators” for coaching. One accelerator is “Motivation,” defined as the drive to tackle specific development needs or learning objectives. The second, “Accountability” is personal commitment to development progress or lack thereof. Synthesizing the literature with our experience, we defined the behavioral criteria that represent Responsiveness as the degree to which the executive appreciates the coaching opportunity and dedicates the time and energy requisite to leadership development (see Table 1).

Second, Self-reflection goes deeper than Peterson’s concept of “Insight,” which he delin­eated as the understanding of what one needs to develop. Greif (2007) suggested that intro­spection and the willingness to scrutinize one’s own values and reasoning are keys to coaching success. Duval and Wickland’s (1972) model of self-awareness explained that self-reflection requires comparing the “real” self to the “ideal” self; those who acknowledge these discrep­ancies learn and develop. Similarly, Grawe (2004) suggested that acknowledging discrepancies between real and ideal behavior activates motivation to change. Integrating this research, Self-reflection was defined in this study to encompass insight, self-examination, and the willingness to question and reevaluate one’s approaches and standards. Based on our experi­ence, the behavioral criteria for Self-reflection (see Table 1) represent visible and concrete indicators communicated by the coaching participant.

Third, Non-defensiveness differs from Self-reflection in that it captures the emotional reaction to coaching content. Defensiveness constitutes a visible and negative emotional reaction when wres­tling with personal evaluation and change (e.g., Silvia & O’Brien, 2004). The non-defensive individual accepts responsibility for the role he or she plays in events and keeps the dialogue going, even in the face of difficult content. Grounded in this research, we operationalized the behavioral criteria for Non-defensiveness (see Table 1), which are based on our experience detecting the ways coaching participants express their emotional reactions.

Fourth, one of the primary goals of the coaching engagement is behavior change (Peterson, 2006); hence we looked at Degree of Change. For simplicity, this variable was operationalized as Low, Medium, or High. The degree to which the executive achieved the objectives of the coaching is based on the input of organizational stakeholders regarding their observations of the executive.


We hypothesized that executives in their 30s, because they tend to be more idealistic and rule-bound and prefer absolutes in lieu of ambiguity, would differ from those in their 40s and S0s along the four dimensions of Responsiveness, Self-reflection, Non-defensiveness, and Degree of Change; they would be less responsive, because the coaching would challenge their “rules”; less self-reflective, because they would hesitate to question their ideals; less non-defensive, because they would struggle with ambiguity; and less changeable, because as they are already earmarked as top talent in the organization, this designation would reinforce their rules and idealism, leading to less impetus to make adjustments.

In our practice we often use the Hogan Personality Inventory (HPI), Hogan Development Survey (HDS), and Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) at the outset of a coaching engagement, affording the opportunity to incorporate the data into this study. The HPI (Hogan & Hogan, 2007), based on the five-factor model of personality, measures seven leadership attributes characteristic of day-to-day behavior. The HDS (Hogan & Hogan, 2007) measures 11 personality attributes that surface under stress and that can interfere with effectiveness. The MSCEIT defines emotional intelligence as the abilities to read emotional cues, to integrate emotions with thought, to understand the causes of emotions, and to use emotions to achieve a goal (Mayer, Salovey, & Caruso, 2008).

Based on the review of the lifespan literature we expected relationships to emerge between age and select Hogan scales that tap into the same three defining characteristics of adults in their 30s: idealism, adherence to rules, and preference for absolutes. Specifically, we predicted that the HPI scale Prudence, a measure of conscientiousness and compliance with rules, would inversely relate to age. Similarly, we hypothesized that four HDS scales would inversely relate to age: Skeptical, which evaluates distrust and the degree to which someone deflects criticism and instead blames others, relates to the presence of defensiveness in that it prevents the executive from accepting and integrating information discrepant from his or her view of events and ideals; Cautious, which measures concern about following rules and avoiding errors; Diligent, which is related to Prudence in its focus on conscientiousness, precision, and inflexibility; and Dutiful, a measure of desire for approval and compliance. Hogan research (Foster, 2015), interestingly, indicated decreasing Dutiful scores across generations.

The MSCEIT subscales measure four components of emotional intelligence (Mayer, Salovey, & Caruso, 2008). A measure of ability rather than personality, the tool assesses the aptitude to process information about one’s own and others’ emotions, and the capability to use that information to guide behavior. Given that the MSCEIT


We examined 72 coaching engagements conducted by either one of the authors during the period 2008 to 2014 for which age data was available. The sample (see Table 2) consisted of 54% men and 46% women with a mean age of 44.5, primarily working at senior levels (81 %) within the financial services sector (57%). The typical engagement lasted 6 to 12 months (78%). The coaching consisted of one to two meetings per month with as-needed contact between sessions. Each engagement incorporated an assessment component at the outset that included any or all of the following: in-depth behavioral interview, interviews with the boss and human-resources sponsor, psychological inventories (HPI, HDS, and MSCEIT), and verbal 360-degree feedback. A verbal 360 is based on typically 10 to 12 confidential interviews conducted with the boss, colleagues, and direct reports of the executive; themes in terms of strengths and areas for development are distilled and discussed with the executive. The executive worked jointly with the coach to set goals. One-on-one coaching meetings integrated activity to expand insight, learn/practice skills, take real-world action, and reflect upon the actions and outcomes. Peterson’s (2011) description of development-process coaching captures the flow of these engagements. This approach requires expertise in learning and the psychology of human behavior integrated with experience in the business environment.

Each executive was coded High, Medium, or Low along the four dimensions of the coaching process/coaching outcome: Responsiveness, Self-reflection, Non-defensiveness, and Degree of Change. The criteria for evaluating these categories are outlined in Table 1. Each coach rated her own clients. We recognize that there is bias inherent in non-blind coding. Therefore, we took the following precautions. The coach justified each rating with behavioral examples. The non-coach scrutinized the data to ensure the behavioral examples adequately supported the rating. Where deemed insufficient, she challenged the coach to substantiate or modify ratings. (In many cases the non-coach was familiar with the executive from her own work in the client organization.) Personality and emotional-intelligence-inventory data were not accessed during the coding. No impasses were reached.

Based upon the small sample size, the data was evaluated by means of the Fisher’s exact test on contingency tables of the categorical data to examine the statistical relationship between the independent variable Age, coded as 30s, 40s, and SOs, and the process and outcome of the coaching engagement: Responsiveness, Self-reflection, Non-defensiveness, and Degree of Change. Because this data are also ordinal, we likewise applied the Spearman rank-order correlation. Last, we conducted regression analysis using Age as a continuous variable, examining the group in its entirety: 30s through SOs (N = 72), and within each decade separately: 30s (n = 13), 40s (n = 44), and SOs (n = 15).

Positive behavior change is one of the primary goals of coaching. Therefore, we looked at how Responsiveness, Self-reflection, and Non-defensiveness relate to or predict Degree of Change. Concurrently, we investigated the interrelationships among these four coaching-process and coach­ing-outcome variables by means of Spearman and regression analyses.

Most participants (n = 61) completed the HPI, HDS, and the MSCEIT. Therefore, we included regression analysis for the Hogan and MSCEIT scales in accordance with our hypotheses.


Coaching-Process/Coaching-Outcome Hypotheses: Responsiveness, Self-Reflection, Non-defensiveness, and Degree of Change Increase With Age

The Fisher’s exact test revealed a single significant age group difference (p < .OS) for the variable Self-reflection (see Table 3). The 30 to 39 group was significantly lower than the other age groups on this variable. While most (54%) were Medium on Self-reflection, none rated in the High category. The p value for the Spearman rank-order correlation coefficient reached a higher level of significance for this relationship (p < .001). Further, regression analysis revealed a significant relationship (13 = .0378, p < .OS) between the continuous variable Age and Self-Reflection (see Table 4).

Only the Spearman coefficient indicated a significant correlation for Degree of Change (p < .OS). Fifteen percent of the 30 to 39 group rated High on this variable, compared with 32% and 40% for the 40 to 49 and SO to 59 groups, respectively (see Table 3). This suggests that while change does occur for the 30 to 39 group, it is less dramatic than for their older counterparts.

No statistically significant age differences emerged on the measures Responsiveness and Non-defensiveness. Percentages indicate that the majority of individuals in the three age groups rated High on Responsiveness and are evenly distributed on Non-defensiveness (see Table 3).

Personality/Emotional Intelligence Hypotheses: Prudence, Skeptical, Cautious, Diligent, and Dutiful Decrease With Age

Regression analyses (see Table 4) revealed significant results (p < .OS) between Age and three of the five hypothesized Hogan Scales: Skeptical, Diligent, and Dutiful, all of which decrease with increasing age (see Table 5). Note that the variance accounted for is modest, with R2 values ranging from 8% to 15%. There were no significant Age differences for Prudence, Cautious, or the MSCEIT scales.

We then checked the relationships of the significant Hogan scales to the four coaching-process and coaching-outcome variables by means of linear regression. One significant finding emerged. Dutiful is negatively related to Self-reflection (13 = -11.93, p < .05) with R2 = .08.

Supplemental Analyses

Regression analyses conducted within each of the three decades (30s, 40s, and 50s) to ascertain the presence of a linear relationship between the four coaching variables and Age were not significant. This analysis therefore suggests that differences in the coaching process and outcomes occur across decades, not within them.

We looked at the interrelationships among Responsiveness, Self-reflection, Non-defensiveness, and Degree of Change using Spearman and regression analyses. Spearman results indicate signif­icant relationships between Change and each of the other three variables (Responsiveness at p < .001; Self-reflection and Non-defensiveness at p < .05). Regression analyses indicate significant relationships between Responsiveness and each of the other three variables (p < .001). No significant gender differences emerged in any analysis.


This study found support for two of the four hypotheses concerning coaching process/coaching outcome and age. For executives engaged in coaching, Self-reflection and Degree of Change increased with age, when analyzed by decade comparisons and using Age as a continuous variable. It is noteworthy that these relationships are not incremental within the decades but rather occur across the decades. Thus, decades represent a meaningful way to categorize these aspects of adult maturation.

Three of the five hypotheses addressing personality and age were supported. Skeptical, Diligent, and Dutiful decreased with age. This suggests that over the decades, executives who receive coaching become more open to criticism, flexible, and less dependent on the approval of others. The finding that Dutiful is negatively related to Self-reflection makes theoretical sense. The drive for compliance and approval likely overshadows independent critical thinking and self-scrutiny. While Skeptical and Diligent decreased with age, they did not vary statistically with the coaching-process and coaching-outcome variables. This suggests they tap into a construct distinct from the coaching variables. It is also possible that the coaching variables miss a key element of age-related change.

Construction of personality that dictates how the executive responds to the coaching engagement. Only one Hogan scale, Dutiful, correlated with a coaching variable, Self-reflection. It is possible, therefore, that this personality characteristic independently relates to the coaching experience or that there is an interaction that pairs the decrease in Dutiful over the lifespan with an individual’s propensity to self-reflect, gain insight, and develop mature leadership skills. This can be a promising avenue for future research.

We expected that the MSCEIT would not reveal changes by age. MSCEIT scale standard deviations reveal limited variability in the data, indicating that the sample represents a narrow group of high-potential, high-performing executives who generally excel in this arena. Responsiveness ratings were also high across the board, implying the data set is biased toward people who appreciated the opportunity to participate in a coaching engagement and the grooming it affords. Non-defensiveness was evenly distributed across the age decades. Perhaps this taps into a characteristic that remains stable over time.

Implications for Coaching 30-Somethings

Overall results suggest that 30 to 39-year-old executives undertaking coaching are distinct. They are less introspective and less amenable to profound change, compared to older executives. This result is supported by the lifespan literature (e.g., Loevinger, 1979; Tamir, 1989; Valliant, 1977). From a maturational perspective, for executives having just mastered the standards of their profession, behavior is rule-bound; they build a personal inventory of airtight values to guide what they do and how they perceive the world. Consequently, they are likely to miss subtlety and do not appreciate the power of nuance and paradox. They hold on to ideals not yet tarnished by reality, whereas executives in their 40s and 50s are already bruised by experience and are more likely to accept imperfection and ambiguity (e.g., Levinson, 1978). From a practical perspective, executives in their 30s are on a performance treadmill; focused and working to establish themselves, they have little time or inclination to reflect. Organizationally, they comprise a select group of high-potential talent and they know it: The organization has invested in their development via executive coaching. This reinforces their view that they are getting things right.

In view of these dynamics, we recommend two approaches to facilitate development for the 30 to 39 group. The first addresses self-reflection. It involves the executive experiencing a profound moment of truth by, for example, getting pummeled by bad results or negative feedback (such as falling out of favor, a failed project, poor 360 results). Sometimes this happens during the normal course of events. Other times, the manager/mentor/coach engineers valid, powerful, yet difficult feedback. This involves orchestrating an encounter to confront the executive with the poor behavior perceived by others and the consequences that can follow. The experience, which may precede or be part of the coaching engagement, can range in intensity from acknowledging ineffectual project leadership to the possibility of career derailment. The operative principal is that it grabs their attention and promotes a desire to dig themselves out by doing something differently.

For example, Heather, 33 years old, headed research for a business sector within a financial­services firm. She prided herself on a flawless image; immaculately groomed and well regarded in the industry, she produced well-written, insightful research reports. Clients sought out these reports, reviewing them in superlative terms. However, her staff of analysts frequently turned over, as they suffered under her relentless drive for perfection and punishing feedback. The moment of truth arrived when she was denied the level of managing director (MD) for a second year in a row. Informed that the MD promotion would be contingent upon retaining a team of analysts who thrived under her watch, now Heather eagerly demonstrated interest in learning how to motivate a team; coaching ensued. Despite wrestling with the coaching content, she succeeded in altering her style, accepting less-than-perfect output from the team and delivering positive feedback when warranted. The following year, she achieved MD.

The second approach pinpoints degree of change. It entails framing insight and development in concrete, formulaic “if-then” scenarios such as, “If you let go of this battle, you are more likely to build an advantageous relationship with X.” It has the look and feel of advanced “rules” for executive success, an approach that resonates with the 30s age group.

For example, Joseph, 37 years old, headed a technology function. He possessed a brilliant mind and generated inventive ideas about how to transform technology operations. His boss, the chief administrative officer, wanted him to bring these programs to fruition but they were not gaining traction. Joseph, a gentle, kind individual, was conflict avoidant. He valued getting along well with everyone. This style, however, prevented him from addressing the natural resistance to the change agenda that accompanies technology transformation. Joseph welcomed the opportunity to work with a coach because he was achievement oriented and strove to meet the requirements identified by his boss. Explaining how conviction and the power of his position could move the needle or how robust relationships would tolerate a higher level of aggressiveness did not convince Joseph. He had to experience, in a concrete manner, that certain phrases, gestures, and strategic encounters would achieve the desired effect. This “formulaic” learning experience, where coaching scripted the scenarios he was likely to encounter, resulted in enhancing his ability to influence.

Executives in their 30s who receive coaching are motivated and enthusiastic about developing their skills. They do not differ significantly from the other age groups on responsiveness to the coaching opportunity, nor are they outwardly defensive. They just do not dig deep and are unlikely to do so without the prompting one or both of these methods afford.

The scenario is different for executives in their 40s and SOs. These executives who engage in coaching are more comfortable with introspection and achieve higher degrees of change. As the lifespan literature indicates, they exhibit greater flexibility, both emotional and intellectual. Already professionally established, they have less to prove and can, therefore, embrace new paradigms with greater curiosity and openness. They recognize that the world is messy and that there are no hard-and-fast rules. Shades of gray make sense to them.

The identification of coaching-process variables represents another important contribution made by this study. Integrating the coaching literature with research on the psychology of change led us to the variables of Responsiveness, Self-reflection, Nondefensiveness, and Degree of Change. Future research can further refine these constructs and identify objective means to measure them. That way, researchers and practitioners can build independent measures into the evaluation of these engagements at key milestones and at their conclusion.


There are three important methodological limitations to this study. The first concerns sample size. Because the population of 30 to 39 year-olds (n = 13) and SO to 59 year-olds (n = 15) was small, there are limits to statistical analysis. With only 13 executives in the 30 to 39 range, the findings for this group could be an anomaly. Seventy-eight percent of these executives are from the financial-services sector, which is not representative of the total world of work. Future research can determine the degree to which these findings generalize.

It is also important to note that literature on the 50s decade is dated. When earlier research was conducted, a large proportion of adults in their 50s were preparing to exit from the workplace. This is no longer the case as people are choosing to retire later. According to the National Institute on Aging, a substantially larger proportion of people in the early to mid 50s expect to work after age 65 (National Institute on Aging, 2015). There is more to be learned about this decade and its impact on the workplace.

Second and more important, the coding of the data set is subject to risk of bias because it suggests awareness without explicitly invalidating the data. There are significant intercorrelations among the four coaching-process or coaching-outcome variables. This may represent a combination of coder bias and theoretical overlap among the constructs. In fact, these constructs as elicited from the literature were not designed to be independent of one another. Responsiveness, Self-reflection, and Non-defensiveness all contribute to Degree of Change. While it is tempting to recommend an objective third-party rater to address coding bias, the practical reality is that intimate knowledge of the client enabled us to evaluate nuanced thought and activity. A potential solution is to create a detailed behavioral-observation checklist that could be used by the coach, organizational stakeholders, and the executive him- or herself during the course of the coaching engagement and at its conclusion. Thus, multiple measures would increase reliability and counteract the coder bias inherent in this research.

An additional limitation of the coding of the dependent variables concerns the restricted range of High, Medium, and Low, effectively a 3-point scale. As coaches, we did not anticipate, at the time of the coaching engagements, that we would be analyzing the coaching content for a study. Therefore, we did not record the detailed information required for more finely articulated scales. The 3-point-scale structure allowed for greater ease of coding of the variables in the aftermath of the coaching. Future research, structured before the onset of coaching engagements, will allow for more fine-tuned precision and, hence, greater power. As noted above, it will also require further refinement of the dependent-variable definitions and associated behavioral criteria.

Last, the population included in this study, executives awarded the privilege of grooming by executive coaches, is not representative of the general population or of the population of executives who do not participate in coaching engagements. The study population is likely a group highly regarded by the companies they serve, seen as leaders with potential to move up the ranks. Therefore, results are not generalizable beyond this group.


This research represents a rare step investigating the effect of age on the coaching process and coaching outcomes. There is opportunity to develop additional techniques that optimize coaching outcomes for executives in different age categories. While we looked at an existing body of coaching content and outcome studies, future investigation can structure data collection from the start and throughout the engagement. The current study opens the door for dialogue.

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