Fit matters

Research by the Korn Ferry Institute found one of the firm’s key placement tools, the Four Dimensional Executive Assessment (KF4D-Exec) to be flexible, adaptive, and valid in assessing various leadership roles and the ways they systematically differ.

Not all leadership roles are created equal. Some lead in organizations with fast change, volatile objectives, and unclear paths forward; others lead companies with well-known, stable goals achieved through established and known processes. Some lead in strategic ways; others are more tactical. Some leaders take on roles in which they must have and apply deep expertise, while others are far more focused on broad and fast learning. To better understand outcomes of assessment and placement of these different kinds of leaders and their differentiated roles, the Korn Ferry Institute recently studied one of the firm’s key placement tools, the Four Dimensional Executive Assessment (KF4D-Exec). We found it flexible, adaptive, and valid in assessing various leadership roles and the ways they systematically differ. Further, our research showed that leaders who were a close fit with traits and drivers in Korn Ferry’s customized and unique target profiles were up to 13 times more likely to be highly engaged in their jobs, making them more likely to be highly satisfied, emotionally invested, and willing to expend considerable discretionary effort in their posts.

The KF4D-Exec reflects the firm’s research-based view that optimally matching prospective leaders with roles and organizations is a complex process and best done while considering variability in leadership positions and organizations. In the KF4D-Exec assessment, we gather information from clients about their organizations and the role(s) to be filled to arrive at customized best-case target-score profiles on measures of leader traits and drivers, such as those shown in Figures 3 and 4. Our research confirms that the nature of organizations and roles moderates what “great looks like” in terms of traits, drivers, and competencies.

Consider the positions of the six sliders in a Korn Ferry online client exercise (Figure 1). These indicate that the client organization seeks a change agent who fosters stakeholder consensus in a fast-paced organization with volatile objectives. The role involves a mix of technical expertise and the ability to leverage others’ skills, talents, and expertise. It has a strategic more than a tactical orientation and involves less clarity and more ambiguity in goals and solutions. We will call this the Architect role.

 
Figure 1. The Architect role.
 
Figure 2. The Builder role.

Now consider the Builder role described by the sliders in Figure 2. This role is more tactical than that of the Architect; it requires more technical expertise and involves top-down authority more than consensus building in an environment with less ambiguity and more stable objectives compared to the environment of the Architect.

 
Figure 3. Selected trait target scores for two role types.

Our empirically developed algorithms support different optimal trait profiles for both the Architect and Builder roles, as shown in Figure 3. Best-case Architects should be decidedly comfortable with risk and ambiguity. They should be markedly adaptable, assertive, persistent, and achievement driven; they won’t emphasize a detail orientation (as measured by the Focus construct). On the other hand, best-case Builders should have less and generally low tolerance for ambiguity and risk; they should have a greater inclination toward detail orientation and exactitude (as measured by the Focus construct). Builders, like Architects, also should be persistent and achievement driven.

Figure 4 duplicates Figure 3 with a key difference: the inclusion of fictitious Candidate A. By comparing Candidate A’s response profile to the Builder and Architect target profiles, we can determine in which role Candidate A fits best. Candidate A has, for example, a score of -.50 on Adaptability, while the Architect role has a target score of +.92. In this case, Candidate A is (-.50 - .92) = -1.42 (standard deviation) units from the Architect target; she is closer but still (-.50 – (-1.28)) = +.78 units away from the Builder target. If we average the absolute value of each of these differences across all seven measures shown in Figures 3 and 4, we find Candidate A is, on average, .37 units away from the Architect target and .25 units away from the Builder target. In other words, Candidate A fits better in and likely would be more suited to a Builder role.

 
Figure 4. Fictitious candidate and selected trait scores for two role types.

We recently studied 2,001 managerial incumbents from mid-level “managers of managers” to top senior executives. We secured information about their roles on the variables shown in Figures 1 and 2. We administered the KF4D-Exec traits and drivers assessments to them as well as a measure of work engagement. Using algorithms developed and described elsewhere, we computed target traits and drivers scores (23 total scores) for each incumbent’s job role. We determined the extent to which incumbents fit with their own jobs using the process described above. We also grouped them into one of two groups, which reflected whether they had high work engagement scores or not (using the sample-based 80th percentile as a cutoff).

Data were used to ask the questions: If leaders fit highly with the target trait/driver scores for their job, are they more likely to be highly engaged? If so, how much more?

The results of statistical analyses were significant and robustly supported our expectation. Leaders who fit well into their traits/drivers targets were far more likely to be highly engaged. High-fit leaders compared to average-fit leaders were about 3.5 times—or 250%—more likely to be highly engaged. Compared to low-fit leaders, high-fit leaders were nearly 13 times—or 1,200%—more likely to be highly engaged, which is predictive of increased job performance and other desirable individual- and organizational-level outcomes. Additional results can be examined in Figure 5.

The results underscore the utility and value of the KF4D system and the KF4D target profiles. Leaders who strongly fit into target profiles are far more likely to be highly satisfied, emotionally invested, and able to expend considerable discretionary effort toward their jobs. The findings also confirm our view that one size does not fit all, and that considering both the nature of organizations and roles in conjunction with leader characteristics is a significantly useful way to match individuals to jobs.

 
Figure 5. High-engagement odds ratios for various levels of fit to KF4D target profiles.

Authors

  • Jeff Jones

    Manager of Research and analytics at the Korn Ferry Institute

  • James Lewis

    Senior Director, Research, Korn Ferry Institute