john lutz - pilot study five factor model profiles as predictors for derailer behavior

Running head: PILOT: PREDICTING DERAILER BEHAVIORS USING BIG 5 PROFILES 1

Pilot Study: Identifying Five Factor Model Profiles as Predictors for Derailer Behaviors

John Lutz

Queens University of Charlotte

Author note

This paper was written for the McColl School of Business MSOD program, fall 2015.

Contact: [email protected], 518-248-4132

© Copyright, 2015 by John Lutz. All rights reserved.

mailto:[email protected]

PILOT: PREDICTING DERAILER BEHAVIORS USING BIG 5 PROFILES 2

Abstract

Executive derailment holds severe consequences for both the manager that derails and the

organization that he derails in. The purpose of this pilot effort was to identify five factor model

personality profiles that correspond to workplace behaviors that lead to leadership derailment.

Data was collected from students from the McColl School of Business at Queens University of

Charlotte that were administered a five factor model profile assessment and a 360-feedback

instrument focused on derailer behaviors. A five factor model profile was derived for each of the

19 derailer behaviors proposed by the Center for Creative Leadership. Limitations in sample

population, instrument response, and lack of support in the literature limit the accuracy of the

identified personality profiles as predictors for derailer behaviors. This pilot is the first study to

seek empirical evidence of specific five factor model profile predictors for derailer behaviors.

Keywords: Executive derailment, preventing derailment, five factor model, workplace

behavior, Workplace Big 5 Profile, Schoolplace Big 5 Profile, Derailer 360


Pilot Study: Identifying Five Factor Model Profiles as Predictors for Derailer Behaviors

In modern speech, the term derailment conjures severe images. How can such a harsh

term be used to describe an occurrence in a manager’s career? In the same manner as an engine

can go careening off of its rails, so too can an aspiring manager find his or herself displaced from

their meteoric rise through an organization. This career derailment can be just as violent as its

namesake, individuals who have experienced naught but success as they progress in their career

can collide with the immovable, when they are perceived to not have the ability to do the job that

they have been promoted to do.

The individual manager derails themselves (Lombardo & Eichinger, 1989), as in the

individual is the root cause of their derailment; however, it is often a group within their

organization that perceives that they cannot meet the requirements of their current position and

make the decision to remove the manager from the position, demote them, or to prevent their

further promotion (Lombardo & Eichinger, 1989; Leslie & Van Velsor, 1996). Derailment

occurs not when a manager is placed in a no-win situation or when that manager betrays

organizational trust by committing fraud or breaches of integrity, rather, it occurs when that

manager’s behaviors do not align with the requirements of the situation that manager has been

placed in. Furthermore, derailment is not simply the act of getting passed over for a promotion

when the opportunity arises, it occurs when a manager can absolutely go no further in an

organization, even if they were expected to. As a manager rises through the ranks of his or her

organization, the stakes change, and there is considerably less room for error; which can increase

the likelihood of derailment occurring (Lombardo & Eichinger, 1989).

As early as the 1960s, the idea that an executive’s behavior can impact his or her

effectiveness was in popular literature and thinking. Peter Drucker’s 1967 book, The Effective


Executive, promoted the idea that there was not a cookie cutter form for an effective executive

manager and that the individual’s behavior when facing adversity would dictate their ability to be

effective (Drucker, 1967). Also in the latter half of the twentieth century, work by individual

researchers and consultants, and institutions such as the Center for Creative Leadership (CCL)

led to the identification of specific behaviors that can cause managers to derail. While derailment

attributed to the individual can be quite severe, managers can be proactive in preventing their

own derailment by recognizing and addressing potential derailer behaviors before things go

wrong. Identifying these derailer behaviors can be accomplished through assessment and

receiving feedback.

As successful managers are generally told exactly what they are doing right and not what

they are doing wrong, self-evaluation can be biased, even unintentionally (Gentry, Braddy,

Fleenor, & Howard, 2008). Three hundred and sixty degrees of feedback are recommended as

tools for managers to understand how their behavior is perceived by those around them

(Lombardo & Eichinger, 1989). Access to complete feedback allows for the exposure of

potential blind spots as well as reinforcement of goals the manager may already be working

towards developing.

Identifying an individual’s current attitudes towards the derailer behaviors could have an

immediate impact on how that individual understands the way that others perceive them.

Additional value could be added to a manager’s development by being able to predict how likely

they were to lean towards a derailer behavior in the future. Identifying potential predictors for

derailer behaviors is the purpose of this work.

The effort of identifying derailer behavior predictors will be accomplished by providing a

review of the literature on derailment behaviors and how personality can drive workplace


behavior, providing a detailed description of the methodology employed in this study, presenting

the study’s findings, discussing the results derived from those findings, discussing the limitations

inherent to this effort, and the next steps for research on this concentration.

Literature Review

In relation to the vast body of literature on leadership, the volume of work focused solely

on leadership derailment is minimal. This review will focus on several topics present in the

literature reviewed. These topics are: the definition of derailment, the causes of derailment,

preventing derailment, personality as a driver for derailment, the five factor model of personality,

and personality as a predictor for derailment behaviors. Although the literature presents these

topics in a variety of contexts, this review will focus on relating these topics to the relationship

between derailment and personality.

Defining Derailment

In an effort to better understand the concept of derailment, an operable definition must

first be established. The exact definition of derailment, mainly in who derailment can apply to,

evolved somewhat through the progression of the literature. Early thinking in the field of derailer

research promoted a narrow definition of derailment (Kovach, 1986; Lombardo & McCall,

1983). According to Lombardo and Eichinger (1989), derailment, by definition, was “reserved

for that group of fast-track managers who want to go on, who are slated to go on, but who are

knocked off the track. “Such managers [that derail] are demoted, plateaued early, or fired” (p. 1).

As work in the field continued, the scope of the definition grew to not only include those

executives who were on the fast track but also managers who have reached “at least the general

manager level” (Leslie & Van Velsor, 1996, p. 1).


Leslie and Van Velsor (1996) also further expanded the definition of derailment to a

derailed manager being one who leaves the organization against their will or who has plateaued

(during their ascension through the organization). Leslie and Van Velsor propose, in their

definition of derailment, that the manager being forced out of the organization or who has been

plateaued was in that position due to a “perceived lack of fit between personal characteristics and

skills and demands of the job” (p. 1).

Current literature favors an even broader definition of derailment in terms of who can

derail and at what level. Recent articles do not limit derailment to fast tracking executives or to

individuals at the general manager level; recent thinking suggests that derailment can occur for

any leader or manager who faces a changing status quo or transition in responsibilities (Carson,

Shanock, Heggestad, Andrew, Pugh, Walter, 2012; Martin & Gentry, 2011; Lipkin, 2013). The

operational definition of derailment used in this study is most closely related to the contemporary

definition; for the purpose of this study, derailment is not limited to those on the fast track but

any individual facing a situation requiring new behaviors.

Why Derailment Occurs

Alongside the concept of what derailment is, the causes of derailment also emerge in the

literature. The early thinking in the field, which limited derailment to fast track managers and

executives, asserts that derailment was caused by common themes that arose and hampered

executive effectiveness in adverse situations. McCall and Lombardo (1983) compared groups of

executives who derailed with a group of executives who succeeded. From that comparison,

McCall and Lombardo identified twelve shortcomings and behaviors on behalf of the individual

which led to derailment. These twelve reasons included skill shortcomings, behaviors such as

aloofness and arrogance, and situational shortcomings such as performance problems and


burnout (McCall & Lombardo, 1983). Along with their reasons for derailment, McCall and

Lombardo also asserted that derailment can occur when a behavior that was considered a

strength became a weakness, an idea which was carried forward into many other works in the

field (Lombardo & Eichinger, 1989; Lombardo, Ruderman, & McCauley, 1988; McCall &

Lombardo, 1983).

In Bentz’s (1985) work with executives from the Sears Corporation, he also cites

shortcomings on behalf of the executive as the major causes of derailment, including the lack of

certain skills (administration, disciplined judgement, and business knowledge), the inability to

cope, the failure to lead or influence, and overriding personality defects (an early allusion to

personality driving workplace behavior). The inclusion of the idea that a personality defect can

cause leadership derailment speaks to the concept that a manager can be highly skilled and

capable but may not possess the full range of capabilities allowing effective response to the

environmental changes which accompany a transition to a different level of management.

Echoing the assertion of Lombardo & McCall, Kovach, in her 1986 work identified two

major reasons for why executives derail, behavioral characteristics that lead to early success but

hinder at executive levels and the failure to acquire the necessary personal power to lead and

influence groups of people in large organizations (p. 45). Kovach expands on these two themes

by providing a linkage to leadership development theory and by asserting that the organization

also plays a part in keeping those leaders on track (1986). Kovach’s work is unique in the early

literature on derailment in that it identifies the difference between the fast track and an apparent

fast track that aspiring managers are placed on; those on the fast track are nurtured but for those

on the apparent fast track, the organization does not provide shooting stars with the necessary

tools to develop and thus do not help prevent derailment (p. 47).


Lombardo, Ruderman, and McCauley (1988) utilized the reasons for derailment

developed by previous authors in the field to develop the Executive Inventory Scale (EIS) which

consolidated the previously identified causes of derailment. The scales created for the EIS were:

handling business complexity, handling of subordinates, honor, personal drive for excellence,

organizational savvy, composure, sensitivity, and staffing (Lombardo, Ruderman, & McCauley,

1988, p. 210). The results of Lombardo’s, et al, work indicated that not only did these themes

provide a reason for why individuals derailed, but they could be also be used to predict

derailment (Lombardo, et al, 1988, p. 211).

Lombardo and Eichinger’s 1989 work, Preventing Derailment, identifies that derailment

occurs when an individual faces a new situation with old behaviors (p. 3). Lombardo and

Eichinger also echo the important assertion that derailment is preventable and that those in

danger of derailment can be helped if potential derailment behaviors are recognized. Lombardo

and Eichinger further reinforce that early strengths can become weaknesses and can cause an

individual to “slide into trouble” if the individual does not remain attentive to the changing

demands of a new position (1989, p. 8). The Lombardo and Eichinger 1989 work also presents a

list of derailment reasons or behaviors which are the basis for the nineteen derailer behaviors (or

career stallers and stoppers) that are presented in their work, For Your Improvement (Lombardo

& Eichinger, 1996). The nineteen derailer behaviors presented in For Your Improvement are the

basis for the Derailer 360 test instrument used in this study. Lombardo and Eichinger’s (1996)

nineteen derailer behaviors are

inability to adapt to differences

poor administrative skills

overly ambitious


arrogance

betrayal of trust

blocked personal learner

lack of composure

defensiveness

lack of ethics and values

failure to build a team

failure to staff effectively

insensitive to others

key skill deficiencies

non-strategic thinker

overdependence on an advocate

overdependence on a single skill

over-managing

performance problems

political missteps.

Lombardo and Eichinger’s 1989 work also supports the effectiveness of 360 degree

feedback for helping individuals identify potential derailer behaviors, and, like Kovach (1986)

supports the thinking in the field that increasing the variety of experience for managers can

reduce the potential for derailment.

In 1995, Leslie and Van Velsor, also from the CCL, produced a work inquiring as to if

the reasons for derailment had changed from the studies conducted earlier in the twentieth

century; furthermore they compared causes of derailment in both North American and European


leaders. Leslie and Van Velsor’s findings indicated that the majority of reasons for derailment

remained similar to previous reasons with the exception of the prevalence of an overdependence

on a mentor and a reframing of the concept of derailment due to differences with management

(1996, p. 32). Derailing due to mentor over-dependency was still cited as a possibility due to the

impact that mentors can have on aspiring managers and that differences with management could

translate into derailment by failure to adapt with organizational culture or changes in the

organizational environment (Leslie & Van Velsor, 1996). Another notable aspect of Leslie and

Van Velsor’s work was the assertion that derailment did not necessarily mean the end, that the

derailed individual can move on and recover; mainly by using the derailment as a learning

experience for future endeavors (1996, p. 1).

Lois Frankel’s 1994 article, Preventing Individual’s Career Derailment, cites research

conducted by the CCL as the basis of her work on derailment and asserts that derailment occurs

when situational requirements change but the individual’s behaviors do not. Frankel also makes

the assertion that promotions are not the only reason that an individual’s behaviors may not

match the situation, changes in organizational culture and lateral or physical moves could also

have a causal effect (1994, p. 298). Frankel suggests executive coaching as a method of helping

individuals identify and address potential derailer behaviors; for further reading on coaching as a

reformative measure for derailment, Alix Felsing of Queens University of Charlotte conducted

extensive research and reported her findings in her 2014 capstone project (2014).

In the literature the broadening of the definition or scope of who can derail does not cause

an apparent departure from the assertion of why derailment occurs. The early writings in the field

discuss derailment occurring when a manager’s or executive’s responsibilities change in such a

way that the individual is not prepared for nor is capable of effectively carrying out those new


responsibilities (Bentz, 1985; Kovach, 1986; Lombardo & McCall, 1983; Lombardo &

Eichinger, 1989). Echoing Frankel’s assertion that promotions are not the only cause for the

conditions of derailment to occur, the idea that derailment can occur for managers or leaders at

any level in an organization illuminates the fact that the individual’s inability to effectively

respond to changes in responsibilities or demands of a position is what fundamentally leads to

derailment (Carson, et al, 2012; Lombardo, Ruderman, McCauley, 1988; Martin & Gentry,

2010).

Building upon the broadening of scope for who can be affected by derailment, Shipper

and Dillard (2000) researched the impact of derailment across different phases of an individual’s

career. Shipper and Dillard supported CCL thinking that derailment was caused by workplace

behaviors; specifically they asserted that derailment was the result of the lack of effectiveness

concerning skills that are broken up into two categories, up-front skills and managerial skills

(2000). Shipper and Dillard do assert that derailment can be prevented and recovery can be

fostered through increasing the manager’s self-awareness and capabilities (2000, p. 341).

Just as the subject of leadership made its way into the realm of popular media, so too has

derailment; popular, non-academic, sources tend to treat derailment with relatively broad net

encompassing leadership failure. The causes of derailment cited by some authors can still be

related to the themes developed by CCL and other researchers. For example, derailment is given

causation from the derailment behaviors of being too busy to win, too proud to see, and being too

afraid to lose (Lipkin, 2013).

As the research of the CCL and the nineteen derailer behaviors are generally accepted in

the recent literature, there are other works, that provide differing perspectives on why leadership

derailment can occur. Researchers from the Oliver Wyman Learning Center published a work on


personal and organizational derailment at the c-suite level which cited additional derailer

behaviors such as the inability to take risks and the inability to think on one’s feet when the clear

solution to a problem does not exist (Dotlich, Cairo, & Rhinesmith, 2008, p. 47). This thinking

goes along with the idea that derailment can occur because of a situational change, especially in

times of crisis or adversity, when managers are placed in a position that requires immediate

action that may be outside their normal operating experiences; thus describing poor decision

making skills as a cause of derailment (Gentry, Katz, & McFeeters, 2009; Higgans & Freedman,

2013).

Preventing Derailment

A common theme in the literature reviewed was that managers and organizations can

prevent derailment. With the early work of CCL researchers regarding derailment as preventable

in nature, means for identifying potential derailer behaviors were created. An outcome of early

derailment research was to create assessments or instruments to help provide feedback on

derailer behaviors. In 1985, Lombardo published the Executive Inventory based upon the reasons

for derailment identified by earlier CCL work (Lombardo, et al, 1988). The significance of

instruments like the Executive Inventory is that managers who were on course for derailment

could utilize self-assessment to spot these behaviors and hopefully help prepare the manager for

the future.

As a tool to spot behavior, Lombardo and Eichinger developed a derailment checklist to

identify derailer behaviors. Once these blind spots were exposed using the derailment checklist,

development could then occur (1989, p.14). The work of Lombardo and Eichinger recommended

that in addition to self-assessment, obtaining 360 degree feedback would help potential derailers

get a better understanding of their blind spots (1989, pg. 14). The idea that once a derailer


behavior is identified, then it can be addressed is a major aspect of the literature in the field, from

the 1980s to today (Brookmire, 2012, Lombardo & McCauley, 1988; Nelson & Hogan, 2009;

Robertson, 2014).

A supporting strategy for uncovering and handling derailer blind spots identified in the

literature is the use of executive coaching. In the literature, works by Frankel (1989) and Nelson

and Hogan (2008) both support the efficacy of coaching to help the individual develop strategies

to address derailer behaviors and mitigate their impact. Furthermore, coaching is recommended

to help those who have already derailed to get back on track (Gaddis & Foster, 2015; Kovach,

1989; Shipper & Dillard, 2000).

A second major theme for preventing derailment present in the literature reviewed is

intentionally expanding a manager’s experience in order to help arm them for future situations.

Again, increasing the variety of experience for managers is a theme that emerged in the early

works in the field and continued on (Bentz, 1985; Gentry & Chappelow, 2009; Lombardo &

Eichinger, 1989). The strategy of increasing an individual’s level of experience is linked to the

inclusion of intentionally developing the individual in order to prevent derailment (Gaddis, 2014;

Frankel, 1994, Kovach, 1986). Kovach takes the relationship of development and derailment a

step farther by asserting that derailment can actually provide the experience to prevent derailing

again in the future (1989). Echoing Kovach’s assertion, the power of learning from the

experience of derailment as an aid to career recovery is proven effective for managers in the

early and middle phases of their career by the work of Shipper and Dillard published in 2000.

Personality Driving Derailer Behaviors

Embracing the thinking that derailment is caused by the inability to effectively respond to

changes in the demands of a position or situation, the logical question is why the impending


derailer wouldn’t be able to respond and make the necessary changes? Identifying the root causes

of derailer behavior is the focus of a theme existing in the literature in the early 2000s and

onward, behaviors or shortcomings that lead to derailment are caused by individual personality

(Gentry, Mandore, & Cox, 2007). The thinking that individual personality can drive work

behavior is supported by the idea that an individual’s personality can determine the behavioral

response to a given stimuli (Livesley, 2001). Hogan states that he “is convinced that effective

leadership is rooted in individual personality (1994, p. 10). As Hogan et al’s work progressed,

dysfunctional workplace behavior was attributed to the dark side of personality (Hogan &

Hogan, 2001).

In addition to the reasons for derailment cited by CCL researchers, Hogan & Hogan

(2001) introduced the idea that derailment, or managerial incompetence, can be a result of the

individual possessing at least some level of DSM-IV dysfunctional personality disorders

(American Psychiatric Association, 1994; Costa & Widiger, 1994). Hogan and Hogan used

DSM-IV personality disorders as the basis of the Hogan Development Survey or HDS, and

created an indication of potential derailment correlating to each disorder. The HDS derailment

indicators were based off of the respondent’s relation to the following aspects of personality

disorder:

borderline

paranoid

avoidant

schizoid

passive-aggressive

narcissistic


anti-social

histrionic

schizotypal

obsessive-compulsive

dependency (Hogan & Hogan, 2001, p. 42).

In their research, Hogan & Hogan used these scales in order to classify likelihood of

derailment based upon how derailed individuals or impending derailers scored against each

aspect of personality disorder (2001, p. 44). The key differentiator between the work of Hogan

and Hogan and previous literature in the field is the assertion that derailer behaviors are driven

by relationship to the DSM-IV personality disorders. The previous work by CCL researchers,

does not assert any specific connections between the derailer behaviors and specific aspects of

personality (Lombardo & Eichinger, 1989; Lombardo & Eichinger, 1996).

In his works, Hogan asserts that the manager’s personality drives their behaviors, and

thus a dysfunctional personality creates dysfunctional behavior. A more specific theme that

arises from Hogan’s works in the field is that as a result of the individual’s dysfunctional

personality having to interpret a situation ineffective or destructive behavior is be exhibited

(Hogan, 1994, Hogan & Hogan, 2001; Hogan & Holland, 2003, Hogan & Kaiser, 2005, Hogan

& Kaiser, 2008). Hogan et al’s work does not propose the assumption that all derailment is due

to the manifestation of psychopathy. Work by Hogan and additional researchers propose the idea

that not only does dysfunctional personality contribute to derailment behaviors, but derailment

behaviors can also be caused by good personality traits that have become a weakness (Burke,

2006; Dalal & Nolan, 2009). Hogan (1994) calls these good personality traits “the bright side” of

personality, in contrast to his dark side of personality.


The Five Factor Model

While Hogan’s (1994) dark side of personality is based around the DSM IV, the so called

bright side of personality is based around the Five Factor Model (FFM) of personality. Hogan

cites the FFM as a “relatively well defined and accepted taxonomy of personality (1994, p. 11);

this view is supported throughout the literature reviewed (Dalal & Nolan, 2009; Hogan &

Holland, 2003; Howard & Howard, 2010). Hogan goes on to state the FFM is used for the bright

side of personality because it provides insight to the “aspects of personality that can be seen in an

interview or in scores on a measure of normal personality” (1994, p. 11). To provide context for

how the FFM represents normal personality, it is valuable to understand its evolution as a

concept.

In an effort to standardize the description of what constitutes individual personality,

researchers challenged the contemporary psychological community of the early twentieth century

to develop groupings of words that described of individual personality traits out of the over four

thousand words that describe personality in the English dictionary (Allport & Odbert, 1936).

The response to Allport and Odbert’s challenge that is the basis of the current FFM was

presented by military researchers in the 1960s. Tupes and Christal (1961) published five factors

which described individual personality; those factors were: surgency (emotional reactivity),

agreeableness, dependability, emotional stability, and culture. Throughout the 1960s and into the

latter half of the twentieth century, including the advent of computer based factor analysis, the

five factors proposed by Tupes & Christal were validated and gained widespread acceptance

throughout the psychological community (Digman, 1990; McRae & Costa, 1987; Norman,

1963).


With the emergence of an accepted five factor structure for individual personality,

contemporary personality instruments were amended to incorporate it. Notably, the NEO

personality inventory was amended to include an additional two factors becoming the NEO + PI-

R personality assessment (McRae & Costa, 1987). To furthermore specify the NEO + PI-R

instrument to assess personality in the workplace, Howard & Howard of the Center for Applied

Cognitive Studies (CentACS) created the Workplace Big 5 Profile based upon the FFM (Howard

& Howard, 2010).

The FFM is generally represented as N E O A C; the CentACS Workplace Big 5 profile

(and the subsequent Schoolplace Big 5 Profile designed for students) gives the following names

to the five factors, or super-traits, of individual personality: (N) need for stability, (E)

extraversion, (O) originality, (A) agreeableness, and (C) consolidation (Howard, 2006). The

CentACS assessments measure each of the five super-traits on a continuum between zero to one

hundred and the United States norms indicate that the scores on each trait match what would be

expected for a normal distribution curve, the majority of scores center around fifty on the

continuum for each trait (Howard & Howard, 2010). Both the Workplace Big 5 Profile and

Schoolplace Big 5 Profile instruments are used in this study.

Using FFM Profiles to Predict Derailer Behaviors

Accepting that personality traits can be the root cause of derailer behaviors, and being

mainly rooted in Hogan’s, et al, contributions to the field, the literature asserts that assessment

and feedback can be accurate tools for illuminating blind spots and recognizing impending

derailer behavior (Dalal & Nolan, 2009, Hogan & Holland, 2003; Hogan & Kaiser, 2005, 2008;

Howard, 2006). As previously discussed, Hogan used the HDS to assess aspiring managers with

regards to dysfunctional personality (Hogan & Hogan, 2001); on the other hand however, the


Hogan Personality Instrument, or HPI, uses the light side of personality to predict the

effectiveness of work behaviors (not specific derailer behaviors). Like the Derailer 360

instrument used in this study, the HPI uses the five factor model to develop seven scales in which

participants are scored; those scales are adjustment, ambition, sociability, interpersonal

sensitivity, prudence, inquisitiveness, and learning approach (Hogan & Hogan, 1995).

While through Hogan’s recent work using both the HPI and HDS, the literature reviewed

supports that Hogan’s scales can be used to predict workplace behavior; there is very little

information on how personality either with the HDS, HPI, or assessments using the FFM can

connect to the nineteen derailer behaviors asserted in CCL literature. At the time of this writing,

searching for connections between the five factor model super traits and the nineteen CCL

derailer behaviors produced no peer reviewed publication.

Using the CentACS Workplace Big 5 Profile as a basis for an internet search pertaining

to derailer behaviors, a sample derailer report was found that suggests trait profiles which may

put an individual at risk for derailer behavior, but the basis for these relationships are not

provided (CentACS, 2010, p. 4). Table 1 illustrates the suggested CentACS super trait predictors

for derailer behavior. As a note, Table 1 uses the CentACS notation for scoring participants on

the continuum for each super trait, -- represents very low on the scale, - represents low on the

scale, = represents medium, + represents high on the scale, and ++ represents very high on the

scale (Howard & Howard, 2010). As can be seen in Table 1, the CentACS predictors do not

provide a full super-trait profile for each behavior, the reason for partial profiles were not given

in the literature.

Table 1

CentACS Big 5 Super Trait Profiles and Derailer Behaviors

Derailer Behavior Super Trait


N E O A C

Arrogance E- A- C+

Betrayal of Trust A-

Blocked Personal Learner O- A-

Defensiveness N+ O- A-

Failure to Build a Team E- A- C-

Failure to Staff N+/- E+/- O+/- A+/- C+/-

Insensitivity to Others N+ A-

Key Skill Deficiencies C-

Lack of Composure N++ A- C-

Lack of Ethics and Values N+ A- C-

Non-Strategic O-

Overdependence: Advocate N+ E- A+ C-

Overdependence: Skill O- C-

Overly Ambitious N+ E+ A- C+

Over Managing N+ E+ A- C+

Performance Problems C=

Political Missteps N+/- E+/- O+/- A+/- C+/-

Poor Administrator O+ A+ C-

Unable to Adapt N+ E+ O- A- C+

Literature Summary

The literature provides strong cases for why derailment occurs, both at the

individual and organizational level. A theme that echoed throughout the literature was that


behaviors which aided aspiring managers in earlier parts of their career could become

weaknesses as their careers progress and cause that manager to derail. The literature asserts that

the risk of derailment can be minimized or prevented all-together if these derailer behaviors are

proactively identified and addressed using assessment and feedback.. The literature also supports

that personality can be the cause of workplace behavior, both effective and ineffective. A gap is

present in the literature linking specific aspects of personality (i.e. traits from the five factor

model), to specific derailer behaviors.

Methodology

Approach Summary

The gap in the literature around specific super-trait predictors for individual derailer

behaviors provides a basis for the primary research question that this study seeks to answer; what

super-trait profiles indicate a tendency for each specific derailer behavior? An ancillary question

that arose from findings in the literature is whether or not the profiles derived while pursuing the

primary research question supports the CentACS derailer predictors. To answer the primary

question, a quantitative approach was used incorporating individual and 360 degree assessments

for collecting individual FFM profiles and derailment behavior tendencies. Participants were

asked to complete the Workplace or Schoolplace Big 5 Profile as well as complete the Derailer

360 alongside three or more raters of their own choosing. Individual participant scores for each

instrument were compared, and the profiles for those participants who’s scores demonstrated a

potential threat of displaying derailer behavior were used to observe if any consistent profile

emerged for each of the nineteen derailer behaviors.


The Participants

The participants of this research study were recruited exclusively from the Queens

University McColl School of Business; all undergraduate students, graduate students and faculty

members were invited to participate (several hundred individuals). All participation in this study

was voluntary in nature and participants were not compensated for their involvement, financially

or academically; informed consent was obtained for the use of all participant responses in data

analysis.

Out of all those invited to participate, 29 individuals volunteered and were included in the

study. Demographically, the subject pool consisted of:

7 males and 22 females,

29 Students,

7 BA students, 2 MBA students, and 20 MSOD students.

The 29 participants of this study completed both the Big 5 profile and had at least one response

provided (self or others) to the derailer 360. To maintain confidentiality, participant’s names

were removed during data analysis and were replaced with a subject number for both the Big 5

profile and Derailer 360 results; those numbers were linked so that the correct sets of data were

compared during data analysis.

Unlike the studies cited in the literature review, participants of this effort were not

recruited as someone who had derailed previously or who had received feedback that they were

an impending derailer; likewise, they were not recruited as being fast trackers or for being

exceptionally successful. The participants of this study were made up of individuals representing

a range of career status, ranging from those having little professional experience to being senior

managers at major corporations. The makeup of industries represented by the participants in this


study also varied; however, participant career level, employment status, and industry were not

official demographics requested during data collection.

The Instruments

The tools used for this study were the Workplace Big 5 Profile, the Schoolplace Big 5

Profile, and the Derailer 360. All three tools used in this study were administered using the

CentACS online platform. The Workplace and Schoolplace Big 5 Profiles were developed by

CentACS are validated instruments and have been in use for quite some time by consultants in

the CentACS network. The Derailer 360 was developed in 2014 by the author of this research

study as a means to help individuals gain feedback on how they and others perceive the

participant in leaning towards the nineteen derailer behaviors. While the internal reliability of the

Derailer 360 has been analyzed, the instrument has not been validated for repeatability; this

study marks the first real world application of the Derailer 360 since initial reliability analysis.

The items and internal reliability for each derailer behavior assessed in the Derailer 360 are listed

in Appendix A.

Both the Workplace and Schoolplace Big 5 profiles were made available to participants

so that students with limited professional experience could be included in the study. The

Schoolplace Big 5 profile reports results for the individual in the same format as the Workplace

Big 5 but has inventory items that are more relatable to participants whose work experience is

related to being a student. The Derailer 360 tool was the same item list for all participants, both

for self-rating and for rating by others.

Participant Response

For the 29 participants, responses for the Big 5 profiles were 100%, the responses to the

Derailer 360 were not. Participants were asked to provide three additional raters for the Derailer


360; while all participants provided additional raters, only a handful of participants actually had

three other raters respond in addition to their self-rating. Furthermore, some participants had

their raters respond but did not complete their self Derailer 360 rating or vice versa, where the

self-rating was the only one completed. The lack of response to the Derailer 360 was a road

block to the efficacy of the outcome study; however the data collected provided the opportunity

to pilot the process of answering the primary research question of what personality profiles

indicate a tendency for each derailer behavior.

To counteract the lack of responses to the Derailer 360 and to provide as many data

points as possible in piloting the analysis process, the Derailer 360 composite responses were not

used; for each Derailer 360 respondent, the self and others ratings were treated as separate data

sets. For example, for participant number two, their self-assessment and then their combined

assessment by others were treated as two separate points by which to compare derailer behaviors

to five factor personality profile. Using the individual scores from the self and others ratings

categories provided 51 sets of data rather than the 21 that would have been available had the

composite scores been used. Future application of the process being piloted in this study will

require complete Derailer 360 response.

The Data

By using the Derailer 360 self and other ratings as individual data points, 51 sets of data

were derived for use in the study (N= 51). Each data set used in the study included a five factor

model profile and corresponding scores for each of the nineteen derailer behaviors. The Derailer

360 scores presented a challenge in analysis; of the 969 individual Likert scale (0 to 5.0) scores

from the Derailer 360 results, only 11 scores were less than a 3.0 in a single derailer behavior

category. So that enough data could be made available to create samples of the subject


population that reflected a potential threat of displaying derailer behaviors, a score of less than

4.0 was considered to be at risk for that behavior. Using 4.0 as the cutoff point to consider an

individual at risk was an assumption based solely upon the responses collected and was not

based upon an empirical statistic.

Using a 3.9 or less on the Likert scale, sample groups of the subject population were

identified for each derailer behavior with the exception of blocked personal learner, only one

participant data set reflected a score of less than 4.0 for that behavior. Table 2 provides the

sample size available for each group of participants who were identified as at risk for each the

nineteen derailer behaviors.

Table 2

At Risk for Derailer Behavior Sample Sizes

Derailer Behavior n Derailer Behavior n

Arrogance 10 Non-Strategic 16

Betrayal of Trust 7 Overdependence: Advocate 18

Blocked Personal Learner 1 Overdependence: Skill 9

Defensiveness 11 Overly Ambitious 23

Failure to Build a Team 12 Over Managing 21

Failure to Staff 21 Performance Problems 24

Insensitivity to Others 8 Political Missteps 15

Key Skill Deficiencies 13 Poor Administrator 11

Lack of Composure 26 Unable to Adapt 12

Lack of Ethics and Values 10


While the sample sizes for each group of derailer behavior “at-risk” participants are not overly

large, the samples do provide a means of making an initial observation and the ability to pilot the

process of identifying a corresponding personality profile.

For participants scoring below 4.0 in a given derailer behavior, the five factor personality

profile super-trait scores were recorded. Tables 3 through Table 21 illustrate the super-trait

scores for each behavior:

Arrogance.

Table 3

Arrogance “at risk” Profiles (n=10)

Derailer

Score N E O A C

3.0 48 45 44 48 45

3.5 51 41 43 49 49

3.8 51 31 49 62 42

3.8 61 49 57 57 51

3.5 61 49 57 57 51

3.8 61 48 57 52 49

3.9 59 60 60 22 53

3.5 55 54 60 45 56

3.3 55 54 60 45 56

3.8 60 36 37 63 61

Betrayal of trust.

Table 4

Betrayal of Trust “at risk” Profiles (n=7)


Derailer

Score N E O A C

3.0 48 41 43 45 45

3.0 51 41 43 45 49

3.8 51 43 44 48 49

3.0 51 45 57 49 51

3.0 55 49 60 49 51

3.5 55 54 60 57 56

3.3 61 54 63 62 56

Blocked personal learner.

Table 5

Blocked Personal Learner “at risk” Profile (n=1)

Derailer

Score N E O A C

3.0 48 45 44 48 45

Defensiveness

Table 6

Defensiveness “at risk” Profiles (n=11)

Derailer

Score N E O A C

3.0 48 45 44 48 45

3.8 42 45 58 48 60

3.0 51 41 43 49 49

3.8 51 41 43 49 49

3.8 51 31 49 62 42


3.5 61 49 57 57 51

3.3 61 49 57 57 51

3.8 61 48 57 52 49

3.8 55 54 60 45 56

3.5 51 43 63 62 51

3.3 57 45 46 65 46

Failure to build a team.

Table 7

Failure to Build a Team “at risk” Profiles (n=12)

Derailer

Score N E O A C

3.5 48 45 44 48 45

3.8 54 52 61 55 39

2.8 51 41 43 49 49

3.9 51 41 43 49 49

3.3 51 31 49 62 42

3.8 51 31 49 62 42

3.8 61 49 57 57 51

3.8 54 51 49 48 50

3.8 52 53 56 48 48

3.8 55 54 60 45 56

3.5 51 43 63 62 51

3.9 51 43 63 62 51


Failure to staff effectively.

Table 8

Failure to Staff Effectively “at risk” Profiles (n=21)

Derailer

Score N E O A C

3.3 48 45 44 48 45

3.0 46 48 46 61 46

3.5 46 48 46 61 46

3.3 54 52 61 55 39

3.8 42 45 58 48 60

3.3 51 41 43 49 49

3.5 55 56 38 54 56

3.8 47 49 41 56 53

3.8 51 31 49 62 42

3.0 51 31 49 62 42

3.0 61 49 57 57 51

3.8 54 51 49 48 50

3.5 53 46 45 55 49

3.6 59 60 60 22 53

3.8 52 53 56 48 48

3.8 52 53 56 48 48

3.3 55 54 60 45 56

3.7 42 50 59 64 48

3.3 51 43 63 62 51

3.5 60 36 37 63 61

3.8 60 36 37 63 61


Insensitivity to others.

Table 9

Insensitivity to Others “at risk” Profiles (n=8)

Derailer

Score N E O A C

3.5 3.5 3.5 3.5 3.5 3.5

3 3 3 3 3 3

3.9 3.9 3.9 3.9 3.9 3.9

3.3 3.3 3.3 3.3 3.3 3.3

3.8 3.8 3.8 3.8 3.8 3.8

3.5 3.5 3.5 3.5 3.5 3.5

3.9 3.9 3.9 3.9 3.9 3.9

3.3 3.3 3.3 3.3 3.3 3.3

Key skill deficiencies

Table 10

Key Skill Deficiencies “at risk” Profiles (n=13)

Derailer

Score N E O A C

3.0 48 45 44 48 45

3.5 46 48 46 61 46

3.7 46 48 46 61 46

3.8 42 45 58 48 60

3.5 51 41 43 49 49

3.8 53 49 43 43 47

3.8 51 31 49 62 42

3.5 61 49 57 57 51


3.8 54 51 49 48 50

3.8 55 54 60 45 56

3.5 62 44 39 63 29

3.8 57 45 46 65 46

3.3 60 36 37 63 61

Lack of composure.

Table 11

Lack of Composure “at risk” Profiles (n=26)

Derailer

Score N E O A C

3.5 48 45 44 48 45

3.8 46 48 46 61 46

3.5 46 48 46 61 46

3.8 54 52 61 55 39

3.5 54 52 61 55 39

3.5 42 45 58 48 60

3.0 51 41 43 49 49

3.2 51 41 43 49 49

3.9 47 51 55 53 54

3.8 47 51 55 53 54

3.8 56 50 43 54 62

3.8 61 49 57 57 51

3.8 61 49 57 57 51

3.3 61 48 57 52 49


3.8 61 48 57 52 49

2.8 63 57 53 50 43

3.3 54 51 49 48 50

3.5 53 46 45 55 49

3.9 59 60 60 22 53

3.8 52 53 56 48 48

3.8 55 54 60 45 56

2.5 55 54 60 45 56

3.8 51 43 63 62 51

3.5 62 44 39 63 29

3.8 57 45 46 65 46

3.5 60 36 37 63 61

Lack of ethics and values.

Table 12

Lack of Ethics and Values “at risk” Profiles (n=10)

Derailer

Score N E O A C

3.3 48 45 44 48 45

3.5 46 48 46 61 46

3.8 51 41 43 49 49

3.8 61 49 57 57 51

3.5 61 49 57 57 51

3.5 61 48 57 52 49

3.8 61 48 57 52 49


3.5 55 54 60 45 56

3.5 55 54 60 45 56

3.3 51 43 63 62 51

Non-strategic

Table 13

Non-Strategic “at risk” Profiles (n=16)

Derailer

Score N E O A C

3.0 48 45 44 48 45

2.8 46 48 46 61 46

3.5 54 52 61 55 39

3.5 51 41 43 49 49

3.6 51 41 43 49 49

3.4 49 49 43 47 44

3.5 53 49 43 43 47

3.8 47 49 41 56 53

3.9 51 31 49 62 42

3.0 61 49 57 57 51

3.8 63 57 53 50 43

3.5 53 46 45 55 49

3.9 53 46 45 55 49

3.8 55 54 60 45 56

3.5 62 44 39 63 29

3.5 57 45 46 65 46


Overdependence on an advocate.

Table 14

Overdependence on an Advocate “at risk” Profiles (n=18)

Derailer

Score N E O A C

3.5 48 45 44 48 45

3.8 42 45 58 48 60

3.0 51 41 43 49 49

3.9 55 56 38 54 56

3.8 47 49 41 56 53

3.0 61 49 57 57 51

3.0 61 49 57 57 51

3.8 61 48 57 52 49

3.8 63 57 53 50 43

3.9 63 57 53 50 43

3.7 59 60 60 22 53

3.3 55 54 60 45 56

3.8 55 54 60 45 56

3.5 51 43 63 62 51

3.0 62 44 39 63 29

3.3 57 45 46 65 46

3.8 60 36 37 63 61

3.8 60 36 37 63 61


Overdependence on a single skill.

Table 15

Overdependence on a Single Skill “at risk” Profiles (n=9)

Derailer

Score N E O A C

3.5 48 45 44 48 45

3.8 46 48 46 61 46

3.9 55 56 38 54 56

3.8 61 49 57 57 51

3.8 61 48 57 52 49

3.8 55 54 60 45 56

3.8 62 44 39 63 29

3.8 57 45 46 65 46

3.8 60 36 37 63 61

Overly ambitious.

Table 16

Overly Ambitious “at risk” Profiles (n=23)

Derailer

Score N E O A C

3.0 48 45 44 48 45

3.8 46 48 46 61 46

3.8 46 48 46 61 46

3.5 54 52 61 55 39

3.5 54 52 61 55 39

3.8 49 50 62 61 29

3.8 51 41 43 49 49


3.8 49 49 43 47 44

3.1 55 56 38 54 56

3.8 53 49 43 43 47

3.8 51 31 49 62 42

3.7 51 31 49 62 42

3.8 41 51 66 58 64

3.5 61 49 57 57 51

3.5 61 49 57 57 51

3.8 63 57 53 50 43

3.3 54 51 49 48 50

3.8 53 46 45 55 49

3.7 59 60 60 22 53

3.7 52 53 56 48 48

3.5 55 54 60 45 56

3.3 57 45 46 65 46

3.7 60 36 37 63 61

Overmanager.

Table 17

Overmanager “at risk” Profiles (n=21)

Derailer

Score N E O A C

3.8 48 45 44 48 45

3.0 46 48 46 61 46

3.8 54 52 61 55 39


3.8 42 45 58 48 60

3.8 55 56 38 54 56

3.5 53 49 43 43 47

3.0 51 31 49 62 42

3.4 51 31 49 62 42

3.8 41 51 66 58 64

3.3 61 49 57 57 51

3 61 49 57 57 51

3.9 63 57 53 50 43

3.3 54 51 49 48 50

3.5 53 46 45 55 49

3.4 59 60 60 22 53

3.5 55 54 60 45 56

3.8 51 43 63 62 51

3.5 62 44 39 63 29

3.0 57 45 46 65 46

3.8 57 45 46 65 46

3.8 60 36 37 63 61

Performance problems.

Table 18

Performance Problems “at risk” Profiles (n=24)

Derailer

Score N E O A C

3.3 48 45 44 48 45


2.8 46 48 46 61 46

3.5 54 52 61 55 39

3.8 49 50 62 61 29

3.0 42 45 58 48 60

3.7 51 41 43 49 49

3.2 55 56 38 54 56

3.9 74 45 27 55 31

3.5 51 31 49 62 42

2.8 61 49 57 57 51

2.8 61 49 57 57 51

3.5 61 48 57 52 49

3.3 63 57 53 50 43

3.8 54 51 49 48 50

3.5 53 46 45 55 49

3.0 55 54 60 45 56

2.8 55 54 60 45 56

3.9 42 50 59 64 48

3.8 51 43 63 62 51

3.9 51 43 63 62 51

3.8 62 44 39 63 29

3.3 57 45 46 65 46

3.5 60 36 37 63 61

3.6 60 36 37 63 61


Political missteps.

Table 19

Political Missteps “at risk” Profiles (n=15)

Derailer

Score N E O A C

3.3 48 45 44 48 45

3.9 54 52 61 55 39

3.5 42 45 58 48 60

2.5 51 41 43 49 49

3.5 51 31 49 62 42

3.8 61 49 57 57 51

3.5 61 49 57 57 51

3.5 63 57 53 50 43

3.8 54 51 49 48 50

3.9 59 60 60 22 53

2.5 55 54 60 45 56

3.0 55 54 60 45 56

3.8 51 43 63 62 51

3.5 57 45 46 65 46

3.8 60 36 37 63 61

Poor administrator.

Table 20

Poor Administrator “at risk” Profiles (n=11)

Derailer

Score N E O A C

3.3 48 45 44 48 45


3.9 54 52 61 55 39

3.5 42 45 58 48 60

2.5 51 41 43 49 49

3.5 51 31 49 62 42

3.8 61 49 57 57 51

3.5 61 49 57 57 51

3.5 63 57 53 50 43

3.8 54 51 49 48 50

3.9 59 60 60 22 53

2.5 55 54 60 45 56

Unable to Adapt

Table 21

Unable to Adapt “at risk” Profiles (n=12)

Derailer

Score N E O A C

3.3 48 45 44 48 45

3.8 42 45 58 48 60

3.0 51 41 43 49 49

3.8 51 41 43 49 49

3.8 55 56 38 54 56

3.3 53 49 43 43 47

3.3 61 49 57 57 51

3.3 61 49 57 57 51

3.5 55 54 60 45 56


3.8 55 54 60 45 56

3.7 51 43 63 62 51

3.7 60 36 37 63 61

Findings

Data Analysis

Data analysis for this research effort was accomplished by identifying the frequency

distribution for big five super-trait responses for each derailer behavior. Using these frequency

distributions, the prevailing five factor model profiles were derived for each derailer behavior.

These derived five factor model profiles were the main output of this research effort. The

findings in this section are presented using the standard notation used by CentACS when

reporting Big 5 profile continuum results; results range from very low (--), low (-), medium (=),

high (+), and very high (++).

Arrogance.

From the ten data sets which were identified as being at risk for displaying the derailer

behavior of arrogance, the following profile was derived:

N=/+ E= O+ A= C=.

The frequency distribution for these super-trait responses are shown in Figure 1.

-- - = + ++

N 0 0 5 5 0

E 1 2 6 1 0

O 0 3 1 6 0

A 1 0 5 4 0

C 0 2 6 3 0

Figure 1. Arrogance Super-Trait Responses


Betrayal of trust.

From the seven data sets which were identified as being at risk for displaying the derailer

behavior of betrayal of trust, the following profile was derived:

N= E= O+ A= C=.


-- - = + ++

N 0 0 6 1 0

E 0 3 4 0 0

O 0 3 0 4 0

A 0 0 5 2 0

C 0 0 5 2 0

Figure 2. Betrayal of Trust Super-Trait Responses


The single data set which was identified as being at risk for displaying the derailer

behavior of blocked personal learner presented the following profile:

N= E= O- A= C=.

Defensiveness.

From the eleven data sets which were identified as being at risk for displaying the

derailer behavior of defensiveness, the following profile was derived:

N= E= O+ A= C=.


-- - = + ++

N 0 1 5 4 0

E 1 3 7 0 0

O 0 3 2 6 0

A 0 0 6 5 0

C 0 1 8 2 0

Figure 3. Defensiveness Super-Trait Responses



From the twelve data sets which were identified as being at risk for displaying the

derailer behavior of failure in building a team, the following profile was derived:

N= E= O+ A= C=.


-- - = + ++

N 0 0 11 1 0

E 2 4 6 0 0

O 0 3 3 6 0

A 0 0 7 4 0

C 0 3 8 1 0

Figure 4. Failure to Build a Team Super-Trait Responses

Failure to Staff Effectively

From the twenty one data sets which were identified as being at risk for displaying the

derailer behavior of failure in staff effectively, the following profile was derived:

N= E= O+ A=/+ C=.


-- - = + ++

N 0 2 15 4 0

E 2 4 13 2 0

O 0 6 6 9 0

A 1 0 10 10 0

C 0 3 13 5 0

Figure 5. Failure to Staff Effectively Super-Trait Responses


From the eight data sets which were identified as being at risk for displaying the derailer

behavior of being insensitive to others, the following profile was derived:

N= E= O+ A= C=.



-- - = + ++

N 0 0 5 3 0

E 1 2 4 1 0

O 0 3 1 4 0

A 1 0 4 3 0

C 0 0 7 1 0

Figure 6. Insensitivity to Others Super-Trait Responses

Key skill deficiencies.

From the thirteen data sets which were identified as being at risk for displaying the

derailer behavior of possessing key skill deficiencies, the following profile was derived:

N= E= O-/= A+ C=.


-- - = + ++

N 0 1 8 4 0

E 1 3 9 0 0

O 0 5 5 3 0

A 0 1 5 7 0

C 1 1 8 3 0

Figure 7. Key Skill Deficiencies Super-Trait Responses

Lack of composure.

From the twenty six data sets which were identified as being at risk for displaying the

derailer behavior of lacking composure, the following profile was derived:

N= E= O+ A+ C=.


-- - = + ++

N 0 1 15 10 0

E 0 5 19 2 0

O 0 6 8 12 0

A 1 0 17 8 0


C 1 3 17 5 0

Figure 8. Lack of Composure Super-Trait Responses


From the ten data sets which were identified as being at risk for displaying the derailer

behavior of lacking ethics and values, the following profile was derived:

N= E= O+ A= C=.


-- - = + ++

N 0 0 6 4 0

E 0 2 8 0 0

O 0 2 1 7 0

A 0 0 6 4 0

C 0 0 8 2 0

Figure 9. Lack of Ethics and Values Super-Trait Responses

Non-strategic.

From the sixteen data sets which were identified as being at risk for displaying the

derailer behavior of non-strategic thinking, the following profile was derived:

N= E= O- A= C=.


-- - = + ++

N 0 0 12 4 0

E 1 3 11 1 0

O 0 7 6 3 0

A 0 1 9 6 0

C 1 4 10 1 0

Figure 10. Non-Strategic Super-Trait Responses


From the eighteen data sets which were identified as being at risk for displaying the

derailer behavior of overdependence on an advocate, the following profile was derived:


N+ E= O+ A= C=.


-- - = + ++

N 0 1 7 10 0

E 0 5 9 4 0

O 0 7 3 8 0

A 1 0 9 8 0

C 1 2 9 6 0

Figure 11. Overdependence on an Advocate Super-Trait Responses


From the nine data sets which were identified as being at risk for displaying the derailer

behavior of overdependence on a single skill, the following profile was derived:

N+ E= O- A+ C=.


-- - = + ++

N 0 0 4 5 0

E 0 2 6 1 0

O 0 4 2 3 0

A 0 0 4 5 0

C 1 0 5 3 0

Figure 12. Overdependence on a Single Skill Super-Trait Responses

Overly ambitious.

From the twenty three data sets which were identified as being at risk for displaying the

derailer behavior of being overly ambitious, the following profile was derived:

N= E= O=/+ A=/+ C=.


-- - = + ++

N 0 1 16 6 0

E 0 4 16 3 0


O 0 6 8 8 1

A 1 1 11 10 0

C 1 6 12 4 0

Figure 13. Overly Ambitious Super-Trait Responses

Over managing.

From the twenty one data sets which were identified as being at risk for displaying the

derailer behavior of being an over manager, the following profile was derived:

N= E= O= A+ C=.


-- - = + ++

N 0 2 11 8 0

E 2 3 13 3 0

O 0 5 8 7 1

A 1 1 8 11 0

C 1 4 11 4 0

Figure 14. Over Manager Super-Trait Responses

Performance Problems.

From the twenty four data sets which were identified as being at risk for displaying the

derailer behavior of performance problems, the following profile was derived:

N= E= O+ A=/+ C=.


-- - = + ++

N 0 2 13 8 1

E 1 6 15 2 0

O 1 6 6 11 0

A 0 0 12 12 0

C 3 3 12 6 0

Figure 15. Performance Problems Super-Trait Responses


Political missteps.

From the fifteen data sets which were identified as being at risk for displaying the

derailer behavior of committing political missteps, the following profile was derived:

N= E= O+ A= C=.


-- - = + ++

N 0 1 8 6 0

E 1 3 9 2 0

O 0 3 4 8 0

A 1 0 8 6 0

C 0 3 8 4 0

Figure 16. Political Missteps Super-Trait Responses

Poor Administrator.

From the eleven data sets which were identified as being at risk for displaying the

derailer behavior of being a poor administrator, the following profile was derived:

N= E- O- A= C-/=.


-- - = + ++

N 0 1 6 4 0

E 0 6 4 1 0

O 0 6 1 4 0

A 1 0 6 4 0

C 2 4 4 1 0

Figure 17. Poor Administrator Super-Trait Responses

Inability to adapt.

From the twelve data sets which were identified as being at risk for displaying the

derailer behavior of being unable to adapt to differences, the following profile was derived:

N= E- O-/+ A= C=.



-- - = + ++

N 0 1 8 3 0

E 0 4 7 1 0

O 0 6 0 6 0

A 0 1 7 4 0

C 0 0 7 5 0

Figure 18. Inability to Adapt Super-Trait Responses

Derived profile summary.

The Big 5 profile derived for each derailer behavior is shown below in Table 22.

Table 22

Derived Big 5 Super Trait Profiles per Derailer Behaviors

Derailer Behavior Super Trait Profile

Arrogance N=/+ E- O+ A= C=

Betrayal of Trust N= E= O+ A= C=

Blocked Personal Learner N= E= O- A= C=

Defensiveness N= E= O+ A= C=

Failure to Build a Team N= E= O+ A= C=

Failure to Staff N= E= O+ A=/+ C=

Insensitivity to Others N= E= O+ A= C=

Key Skill Deficiencies N= E= O-/= A+ C=

Lack of Composure N= E= O+ A+ C=

Lack of Ethics and Values N= E= O+ A= C=

Non-Strategic N= E= O- A= C=

Overdependence: Advocate N+ E= O+ A= C=

Overdependence: Skill N+ E= O- A+ C=


Overly Ambitious N= E= O=/+ A=/+ C=

Over Managing N= E= O= A+ C=

Performance Problems N= E= O+ A=/+ C=

Political Missteps N= E= O+ A= C=

Poor Administrator N= E- O- A= C-/=

Inability to Adapt N= E- O-/+ A= C=

Results

The goal of this research effort was to answer the primary and ancillary research

questions; what personality profiles indicate a tendency for each derailer behavior and do the

personality profiles identified support the derailer predictors used by CentACS. The profiles

derived for each of the at-risk data sets are based upon relatively small sample sizes, but are

representative of the participants in this study. Deriving these profiles from the available data

provides a means for piloting this process for application to a larger participant sample.

The Big 5 profiles of the twenty nine participants in this study were well in line with the

Workplace and Schoolplace Big 5 Profile US population norms; at the time of this writing,

norms have not been established for the Derailer 360, but no data was collected regarding the

participant’s experience with derailment. To answer the primary research question and to verify

if the findings derived from this study are accurate indicators for derailment behaviors, the

findings are inconclusive and repeating this analysis on additional participant groups is required.

Furthermore, there is no support or opposition for these findings present in the literature, by

which to validate these findings.


The profiles derived in this study do provide data points for answering the ancillary

research question and comparing the list of super-trait predictors for derailment presented by

CentACS. Table 1, above, lists the super-trait scores / profiles which indicate a predictor for the

threat of each derailment behavior. This study provided a derived profile for each of the derailer

behaviors while the list from CentACS, for most behaviors, did not list an entire profile. Of the

list presented by CentACS, only the predictors for non-strategic thinking and performance

problems matched the derived profiles. No assumptions were made regarding the position of the

traits that were not included in the CentACS predictors.

Comparing the Derived Profiles to the CentACS Predictors

Arrogance.

The CentACS super-trait predictors for arrogance were E- A- C+, the profile derived

from this study was N=/+ E- O+ A= C=. The derived profile’s low extraversion super-trait score

supports the CentACS predictors; however, the medium accommodation and consolidation

scores do not.

Betrayal of trust.

The CentACS super-trait predictor for betrayal of trust was A-, the profile derived from

this study was N= E= O+ A= C=. The derived profile does not support the CentACS predictor.


The CentACS super-trait predictors for a blocked personal learner were O- A-, the profile

derived from this study was N= E= O- A= C=. The derived profile’s low originality super-trait

score supports the CentACS predictors; however, the medium accommodation score does not.

The blocked personal learner derailer behavior data set only consisted of a single participant

profile.


Defensiveness.

The CentACS super-trait predictors for defensiveness were N+ O- A+, the profile derived

from this study was N= E= O+ A= C=. The derived profile’s high originality super-trait score

supports the CentACS predictors; however, the medium need for stability and accommodation

scores do not.


The CentACS super-trait predictors for failure to build a team were E- A- C-, the profile

derived from this study was N= E= O+ A= C=. The derived profile does not support the

CentACS predictors.

Failure to staff effectively.

The CentACS super-trait predictors for failure to staff effectively were N+/- E+/- O+/-

A+/- C+/-, the profile derived from this study was N= E= O+ A=/+ C=. The derived profile’s

high originality and accommodation super-trait scores support the CentACS predictors; however,

the derived profile had an equal distribution of medium accommodation scores, as well as

medium need for stability, extraversion, and consolidation scores which do not support the

CentACS predictors.


The CentACS super-trait predictors for insensitivity to others were N+ A-, the profile


CentACS predictors.


Key skill deficiencies.

The CentACS super-trait predictor for key skill deficiencies was C-, the profile derived

from this study was N= E= O-/= A+ C=. The derived profile does not support the CentACS

predictors.

Lack of composure.

The CentACS super-trait predictor for lack of composure was N++ A- C-, the profile

derived from this study was N= E= O+ A+ C=. The derived profile does not support the

CentACS predictors.


The CentACS super-trait predictor for lack of ethics and values was N+ A- C-, the profile


CentACS predictors.

Non-strategic

The CentACS super-trait predictor for non-strategic thinker was O-, the profile derived

from this study was N= E= O- A= C=. The derived profile’s low originality super-trait score

supports the CentACS predictor.


The CentACS super-trait predictors for overdependence on an advocate were N+ E- A+

C-, the profile derived from this study was N+ E= O+ A= C=. The derived profile’s high need

for stability super-trait score supports the CentACS predictor; however, the medium

extraversion, accommodation, and consolidation scores do not support the CentACS predictors.



The CentACS super-trait predictors for overdependence on a single skill were O- C-, the

profile derived from this study was N+ E= O- A+ C=. The derived profile’s low originality

super-trait score supports the CentACS predictor; however, the medium consolidation score does

not.

Overly ambitious.

The CentACS super-trait predictor for being overly ambitious was N+ E+ A- C+, the

profile derived from this study was N= E= O=/+ A=/+ C=. The derived profile does not support

the CentACS predictors.

Over managing.

The CentACS super-trait predictor for being an over manager was N+ E+ A- C+, the

profile derived from this study was N= E= O= A+ C=. The derived profile does not support the

CentACS predictors.

Performance problems.

The CentACS super-trait predictor for performance problems was C=, the profile derived

from this study was N= E= O+ A=/+ C=. The derived profile’s low consolidation super-trait

score supports the CentACS predictor.

Political missteps.

The CentACS super-trait predictors for political missteps were N+/- E+/- O+/- A+/- C+/-,

the profile derived from this study was N= E= O+ A= C=. The derived profile’s high originality

super-trait score supports the CentACS predictor; however, the derived profile’s medium need

for stability, extraversion, accommodation, and consolidation scores do not support the CentACS

predictors.


Poor administrator.

The CentACS super-trait predictors for being a poor administrator were O+ A+ C-, the

profile derived from this study was N= E- O- A= C-/=. The derived profile’s low super-trait

score for consolidation supports the CentACS predictor; however, the derived profile had an

equal distribution of medium consolidation scores, as well as low originality and medium

accommodation scores which do not support the CentACS predictors.

Inability to adapt.

The CentACS super-trait predictors for the inability to adapt were N+ E + O- A- C+, the

profile derived from this study was N= E- O-+ A= C=. The derived profile’s low super-trait

score for originality supports the CentACS predictor; however, the derived profile had an equal

distribution of high originality scores, as well as medium need for stability, accommodation, and

consolidation scores which do not support the CentACS predictors.

Limitations

While this study does provide value in terms of piloting the process for deriving FFM

profiles and presenting comparative data for supporting or contradicting the CentACS super-trait

predictors, limitations were present that reduce the study’s overall contribution to the field of

derailment. These limitations specifically reduce the study’s effectiveness in providing accurate

five factor profiles which correspond to derailer behaviors. The limitations inherent to this study

are comprised of three major aspects, the Derailer 360 instrument, the participant population, and

the design demographics.

Derailer 360

As stated previously, the Derailer 360 is a new instrument that has not been, except for

initial reliability testing, validated in a real world application prior to this study. Due to this


factor, the repeatability of the instrument has not been analyzed and validated. This creates a

scenario where the Derailer 360 may require further revision to ensure that it provides

participants with a clear understanding of how they are perceived as displaying derailer

behaviors. Furthermore, the Derailer 360 responses used in this study were not totally complete,

with some responses missing self-ratings or ratings by others. These incomplete responses

reduce the value of the Derailer 360 results because they may provide biased responses and fail

to provide full “360 degree” feedback on the participant.

Participant Population

Along with the incomplete responses to the Derailer 360, the overall number of responses

is also a limitation of this effort. While there were fifty one data sets available for analysis, there

were only twenty nine usable Big 5 profiles. By not having a unique profile for every set of

derailer behaviors, the results were potentially skewed due to the lack of variation in FFM

profiles, and an opportunity is missed to have a unique profile correspondent to the remainder of

Derailer 360 score sets.

The participants used for this study were chosen for convenience rather than applicability

to derailment. All participants were students of the McColl School of Business, and with the

inclusion of undergraduate subjects, participant ages varied considerably, potentially including

subjects as young as nineteen. At age nineteen and even until the early thirties, an individual’s

personality may not be totally developed, which could lead to skewed results (Howard &

Howard, 2010).

Design Demographics

The design demographics for this study also created a limitation on the efficacy of its

output. The design population for this effort included undergraduate students, graduate students,


and staff at the Queens University of Charlotte McColl School of Business; however, no

requirements were set in terms of either career experience or experience with derailment.

Furthermore, no demographics were collected regarding participant occupation or industry. In

this case, the population surveyed may not be representative of the general population.

Another aspect of the design demographics which may have caused bias in the instrument

response was both the small number of required peer raters (three peers raters were requested)

and that no requirement was made for those raters to be in any specific roles relative to the

participant. With a limited number of peer responses combined with potentially subjective

responses due to personal relationship with those being rated, the Derailer 360 results were

potentially biased towards the positive end of the scale. Both of these factors were evident with

the relatively high scores observed on the Derailer 360 results, requiring the at risk point to be

moved to 4.0 on the Likert scale.

Future Research

Recognizing the limitations of this study does not merely provide a critical perspective on

its findings, but also provides a means for identifying avenues and strategies for future research.

Any future research effort should include mitigation of the limitations listed above. Over time

and through continued application and revision, the Derailer 360 instrument can be validated and

fine-tuned to provide as accurate as possible results for where an individual is perceived to stand

with regards to derailer behaviors. Along with increasing the sample size, obtaining a higher

response rate would also be a priority to add more variation to both the Derailer 360 responses as

well as the participant five factor model profiles.

Another opportunity for future research, as well as increasing the contribution of this type

of work to the field, would be to repeat this effort with multiple groups of participants in real


world applications. Expanding the scope of the participant sample could not only increase the

variation in instrument response but also increase variety in terms of Derailer 360 raters thus

decreasing bias.

Once limitations have been overcome or repeated application of this treatment to separate

participant groups has resulted in a validated list of five factor personality profiles which apply

to the general population, other potential research objectives emerge. Opportunities exist for

exploration into identifying personality profiles for derailment in specific demographics, i.e.

industry, career level, gender, etc. Further opportunity is present in identifying specific sub-trait

profiles which could be attributed to individual derailer behaviors. The results of these types of

research endeavors would lend themselves to identifying means for helping managers “stay on

the tracks” and prevent impending derailment by creating FFM profile specific guides for

addressing and combatting each derailer risk.

Conclusion

Derailment is a risk for those moving up in the world; it can leave significant impact to

both the individual and the organization in its wake. While derived from small sample sizes, the

findings of this research effort provided a pilot for the analysis process and an initial observation

into the five factor model profiles that prevailed for participants considered “at-risk” for each of

the nineteen derailer behaviors. This study also provided data points for comparison to five

factor model super-trait aspects currently used to predict derailer behaviors by CentACS. It is the

hope of the author that the data presented in this work, as well as data derived from future

research, can be used to help individuals avoid derailment by identifying and addressing blind

spots or ineffective behaviors before it is too late.


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Appendix A

1 Arrogance

α .939

Treats colleagues as equal.

Seeks to understand the perspectives of other people.

Typically accepts the feedback of others.

Open to new ideas or solutions from any other personnel or source, not only being

open to new ideas or solutions from certain personnel or sources.

2 Betrayal of Trust

α .904

Does not lie to others.

Will not sacrifice others for personal gain.

Does not go behind the backs of peers or superiors.

Avoids putting others down in public.

3 Blocked Personal Learner

α .923

Is committed to continuous improvement.

Is considered a curious person.

Shows interest in pursuit of knowledge.

Enjoys learning about the jobs of peers and direct reports.

4 Defensiveness

α .914

Is open to listening to feedback from others.

Takes responsibility for failures.

Refrains from pointing fingers and blaming others.

Appreciates others questioning their ideas.

5 Failure to Build a Team

α .932

Leads teams effectively.

Builds strong morale in teams

Allows team members to provide feedback.

Allows team members to have a say in how the team works.

6 Failure to Staff Effectively

α .924

Provides effective feedback to direct reports.

Establishes effective succession plans.

Values staff members with opposing viewpoints.

Handles negative personnel issues well.

7 Insensitive to Others

α .922

Listens well.

Considerate of others feelings.

Seeks first to understand rather than to be understood.

Considers how their actions affect others.


8 Key Skill Deficiencies

α .901

Can transition from the expert role to generalist role when required.

Is perceived as being self-aware.

Effectively makes difficult decisions.

Considered to be a strong communicator.

9 Lack of Composure

α .906

Has a reputation for not overreacting.

Hides frustration well.

Maintains composure in stressful situations.

Rises to the occasion during difficult circumstances.

10 Lack of Ethics and Values

α .958

Never disregards ethical standards during decision making.

Would not cheat to get ahead.

Does the right thing.

Sets the standard for ethical behavior in the workplace.

11 Non-Strategic

α .923

Actively plans beyond day-to-day operations.

Is considered a systems thinker.

Proactively scans the environment on a regular basis for new trends.

Has no problem seeing the big picture and connections across the whole system.

12 Overdependence on Advocate

α .900

Does not need to seek a mentor’s advice for every decision.

Handles problems on their own, without seeking the intervention of a mentor.

Weighs advice when received and does not blindly follow what they’re told.

Does not brown-nose.

13 Overdependence on Single Skill

α .908

Appreciates diverse skillsets.

Actively seeks to expand their skillset.

Does not approach every problem the same way.

Does not consistently repeat the same mistakes.

14 Overly Ambitious

α .801

Focuses on long term results.

Focuses on managing their team rather than their career.

Does not over delegate.

Does not get overwhelmed by taking on too many projects or responsibilities.


15 Over-Managing

α .932

Trusts the decisions of others.

Emphasizes teaching, not telling.

Actively listens to direct reports.

Utilizes feedback from employees when working on a project.

16 Performance Problems

α .891

Can manage a project from beginning to end.

Uses conflict constructively.

Does not shirk their responsibilities.

Does not jump to conclusions.

17 Political Missteps

α .936

Does not make comments which indicate personal biases.

Has treated direct reports and peers well on their way up through the organization.

Treats others respectfully.

Allows others speak their minds.

18 Poor Administrator

α .881

Can easily communicate important information.

Keeps good records of completed projects.

Possesses a high attention to detail.

Puts effort into memos and other documents.

19 Unable to Adapt to Differences

α .888

Does not have difficulty seeing a problem from more than one perspective.

Does not dwell on the unimportant parts of a problem.

Is not a rigid thinker.

Thinks about their actions before making a decision.

john lutz - pilot study five factor model profiles as predictors for derailer behavior

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