Personality as a Predictor of General Job Performance and Sales Performance

The FFM of personality

Primary studies and meta-analyses have demonstrated that FFM personality factors are significant predictors of workplace outcomes, such as job satisfaction (Judge et al., 2002), job performance (Sackett et al., 2022), leadership effectiveness (Judge et al., 2002), and sales performance (Furnham & Fudge, 2008; Vinchur et al., 1998). The FFM encompasses five broad factors (McCrae & Costa, 2008). Conscientiousness refers to strength, purpose, and drive toward goal achievement. Neuroticism describes the intensity and frequency of negative emotions stemming from negative beliefs about life, oneself, and others. For clarification, the current study uses the reversed term “emotional stability” to denote neuroticism. Extraversion reflects outward energy directed toward the external world and the need for external stimulation. Agreeableness reflects a tendency to accommodate, consider, and respond to the perspectives and concerns of others. Openness refers to receptivity to a variety of internal and external sources of information and new experiences (Costa & McCrae, 2010).

General job performance and sales performance

Job performance generally refers to behaviors that contribute to and create value for an organization (Campbell & Wiernik, 2015). In contrast, sales performance is typically assessed with metrics or output indicators that capture performance outcomes. Campbell et al. (1993) argue that sales behaviors are complex and propose distinguishing between input and output measures of performance. Input measures reflect the behaviors required for successful sales outcomes and should encompass actions that employees can directly control (Rotundo & Sackett, 2002). Output measures, such as sales figures or other performance indicators, represent the results generated by these input behaviors.

Rotundo and Sackett (2002) identified three input behavioral domains of job performance: task performance (TP), organizational citizenship behavior (OCB), and counterproductive work behavior (CWB). TP involves proficiency in job-related technical activities (Borman & Motowidlo, 1993). OCB, or contextual performance, includes discretionary behaviors that enhance the organizational environment and support goal attainment (e.g., Borman et al., 2001; Dorsey, Cortina, & Luchman, 2010; Hoffman & Dilchert, 2012; Krijgsheld, Tummers, & Scheepers, 2022). In contrast, CWB encompasses intentional behaviors that harm an organization’s interests (Sackett & DeVore, 2001). Job performance is therefore a broader construct, which encapsulates a wide range of behaviors. Research suggests that measures of TP, OCB, and CWB can be aggregated into a composite termed general job performance (Viswesvaran, Schmidt, & Ones, 2005) measured by managerial ratings or self-assessments. Notably, self-assessments often suffer from leniency bias, as individuals tend to rate themselves more favorably, resulting in lower correlations with actual performance (Heidemeier & Moser, 2009). Consequently, managerial ratings are preferred to increase objectivity and reliability (Campbell & Wiernik, 2015).

In sales contexts, performance reflects both proactive and responsive efforts to address customer demand. In the current study, the terms outbound and inbound sales are used to distinguish between performance arising from outgoing versus incoming sales opportunities (Malizia et al., 2021). More broadly, general job performance and sales performance represent a distinction between behaviors and outcomes. General job performance captures the behaviors required for effective performance, whereas sales performance represents the tangible results of those behaviors.

Personality in relation to general job performance and sales performance

In sales contexts, extraversion and conscientiousness play significant roles in driving performance outcomes (Grant, 2013). Extraverted individuals are more likely to take initiative and exhibit leadership qualities, resulting in more favorable performance appraisals (Wilmot et al. 2019). Conscientiousness provides a stable foundation for consistent achievement of performance objectives. Together, these traits rank among the most robust predictors of performance across different occupational groups (Pletzer & Abrahams, 2025).

In contrast, the impact of emotional stability on sales performance appears to be less robust, suggesting a more nuanced contribution depending on context. As Dugan, Rouziou, and Bolander (2020) proposed, the influence of emotional stability may diminish over time in sales roles, indicating that its relevance is moderated by tenure or experience. As a result, it may play a limited role in predicting performance outcomes for tenured employees. Similarly, although agreeableness predicts interpersonal interactions and relationship building, evidence regarding its impact on sales performance has been inconsistent, with studies even reporting negative associations (Furnham & Fudge, 2008). The influence of openness to experience also appears minimal, as correlations with performance are often weak or nonsignificant (Barrick, Mount, & Judge, 2001; Minbashian, Earl & Bright, 2012), suggesting lower validity estimates in sales roles that emphasize routine processes and structured objectives. Thus, existing research highlights that not all personality dimensions are equally important for performance, and the validity may be contingent upon the demands and nature of the role. Based on this review, the following hypothesis is proposed.

Job performance, including sales behaviors, is inherently multidimensional, encompassing both observable outcomes and underlying behaviors (Campbell et al., 1993). In outbound sales, performance is evaluated using output indicators, which capture observable results but do not fully reflect the underlying behavioral processes that drive success (Campbell & Wiernik, 2015). Personality traits are relevant at both levels, influencing not only the attainment of sales targets but also the underlying behavioral patterns for effective sales performance. Conscientiousness facilitates goal-directed effort and persistence, supporting consistent attainment of sales objectives, whereas extraversion supplies the energy and sociability necessary to engage effectively with clients and prospects (Furnham & Fudge, 2008). The combination of extraversion and emotional stability is particularly valuable in sales roles characterized by frequent social interaction and exposure to rejection, as these traits support both proactive engagement and resilience in the face of setbacks (Kottirre, Blickle, & Wihler, 2025; Dugan, Rouziou, & Bolander, 2020). Additionally, agreeableness is crucial for developing relationships with both new and existing customers, a skill that is especially critical in outbound sales interactions (Malizia et al., 2021). Therefore, agreeableness, combined with emotional stability, may play a pivotal role in understanding success in outbound sales, addressing the dual challenges of relationship building and rejection management. Collectively, performance in outbound sales arises from a combination of traits that promote persistence, relational effectiveness, and emotional resilience. Based on this review, the following hypothesis is proposed.

The inconsistencies observed in the relationship between personality and different performance domains may stem from misalignments between predictors and performance criteria. Hough and Oswald (2023) discussed “predictor-criterion construct congruence,” emphasizing the importance of aligning personality predictors with performance constructs. Supporting this assertion, Sackett et al. (2022) confirmed that stronger predictions arise from a closer behavioral match between selection predictors and performance outcomes.

Research has suggested that introverted individuals excel in listening, which is critical for understanding customer needs (Chaker et al., 2024; Flynn, Collins, & Zlatev, 2023). The ability to manage relationships effectively is crucial in inbound sales contexts. In contrast, high assertiveness, often associated with extraversion, may impede performance in these settings. This impediment occurs because overly assertive salespeople may prioritize their own viewpoints over the customer’s needs. Furthermore, inbound sales performance is inherently reactive and driven by immediate customer requirements. As such, proactive and goal-oriented behaviors associated with conscientiousness may not align with the behaviors required for successful inbound sales. Therefore, conscientiousness is not expected to be associated with inbound sales performance.

The distribution of sales performance

In performance management, a common assumption is that individual performance follows a normal distribution (O’Boyle & Aguinis, 2012). In normal distributions, about 68% of employees perform within one standard deviation of the mean, indicating average performance, while approximately 16% exceed and 16% fall below that range. Only a small percentage (around 0.3%) are found three standard deviations from the mean (Haslam, 2016). This performance pattern is typically observed in low-complexity jobs, where performance closely aligns with production metrics (Aguinis & O’Boyle, 2014; Boisot & McKelvey, 2010; Hunter, Schmidt, & Judiesch, 1990).

In contrast, in the service-oriented economy, where performance metrics relate to providing or selling services rather than producing goods, Aguinis and Bradley (2015) suggest that traditional distributions may not accurately capture employee performance. They argue that more employees emerge as star performers due to greater individual control over performance, facilitated by flexible work arrangements and technology. Consequently, performance in this economy is more accurately represented by power-law distributions, which have infinite variance and can account for extreme performance outcomes (O’Boyle & Aguinis, 2012). Power-law distributions apply to various performance indicators, including sales and revenue metrics, with data frequently exhibiting severe skewness due to the absence of upper limits (Choulakian & Stephens, 2001). The “80/20 rule,” which posits that 80% of effects result from 20% of causes, illustrates this principle in practice across domains, such as wealth distributions (Bhatti et al., 2018) and stock market performance (Gabaix et al., 2003). O’Boyle and Aguinis (2012) found that 94% of sampled professionals, including academics and athletes, fit a power-law distribution better than a normal distribution. Similar findings from Hunter, Schmidt, & Judiesch (1990) suggested that high-complexity roles also conform to a power-law distribution rather than a normal distribution, justifying the exploration of alternative performance distributions. Based on this review, the following hypothesis is proposed:

Ethics and research data

Data collection was conducted from October 2019 to June 2021 as part of a commercial validation project designed to improve recruitment practices. Participants were informed about the purpose and scope of the study, and their consent was obtained prior to data collection. To ensure compliance with General Data Protection Regulation (GDPR) regulations, consent was initially incorporated into surveys and performance appraisals. Subsequently, a more detailed consent form outlining the study’s objectives, data access procedures, and participants’ rights to withdraw was provided. This form was developed in collaboration with the Norwegian Centre for Research Data (NSD), following established guidelines. All data were anonymized to ensure confidentiality throughout the research process.

Participants and procedure

The participants worked as advisors responsible for customer inquiries, sales activities, and administrative tasks within a banking and insurance organization. The sample comprised two advisor groups that differed in their sales responsibilities. The inbound group primarily managed incoming customer requests and associated sales but also engaged in outbound sales activities. In contrast, the outbound group was responsible for outbound sales targets while still managing a portion of inbound inquiries. Despite these differences, both groups shared similar administrative duties and overall sales objectives, which justified combining them for analysis, given the substantial overlap in job functions and responsibilities. The study applied convenience sampling, and participants were selected based on their availability and willingness to participate. Out of 350 invitations, 288 participants completed the personality test and were subsequently rated on performance by their manager. Managers rated the performance for approximately 10 employees each, dedicating 5–10 minutes per appraisal. All participants received automated personality report summaries with the option of discussing results with HR.

The sample consisted of 45% males and 55% females, averaging in the 41–45-year age range. Due to sick leave, absence, and COVID-19, complete sales performance data were not available for all advisors. Sales data included 226 outgoing and 193 inbound sales entries sourced from the client’s internal performance management system.

Measures

Measuring and Assessing Individual Potential (MAP) is based on the FFM and assesses five personality traits with 25 subscales using 200 items on a 4-point Likert scale, ranging from strongly agree to strongly disagree (Sjöberg & Sjöberg, 2019). Each main scale consists of 40 items, and each subscale (facet) contains eight items. In a Norwegian sample (N = 4,821), Sjöberg and Sjöberg (2019) reported reliability estimates: conscientiousness (α = .90), emotional stability (α = .89), extraversion (α = .90), openness (α = .86), and agreeableness (α = .87), with an average alpha for subscales of α = .75. In the current study sample (N = 288), reliability estimates were for conscientiousness (α = .77), emotional stability (α = .78), extraversion (α = .80), openness (α = .64), and agreeableness (α = .73). Because item-level data were unavailable, alpha values were calculated using the mean scores of the FFM facets (e.g., CO1–CO5), which reflected internal consistency among the facets rather than at the item level.

General job performance

General job performance was evaluated by managers using 38 statements, reflecting the job performance model comprising TP (Borman & Motowidlo, 1993), OCB (Organ, 1988), and CWB (Anglim et al., 2018; Robinson & Bennett, 1995). For TP (e.g., “The employee works hard”), OCB (e.g., “The employee is friendly towards others”), and CWB (“The employee has been rude to colleagues”), the CWB scale items were reverse-scored so that lower scores contributed to higher overall job performance scores. The performance appraisal comprised 17 items for TP, 8 for OCB, and 13 for CWB, with reliability estimates: TP (α = .93), OCB (α = .88), and CWB (α = .83). The mean score across the three measures was used as an indicator of the employee’s general job performance. To the authors’ knowledge, the job performance measure had not been used in previous peer-reviewed studies.

Sales performance

Inbound and outbound sales calls were recorded in the organization’s performance management system, allowing for objective monitoring of sales activity. This procedure reduced the subjective bias and potential inaccuracies associated with supervisor-rated performance measures. Sales performance was defined as the total number of successful sales calls completed over a six-month period. Outbound sales activities involved interactive and proactive efforts conducted via telephone, while inbound sales activities included handling requests from customers and following up on leads from colleagues. See Table 3 for descriptive statistics.

Statistical analysis

Statistical analyses were conducted using IBM SPSS Statistics, version 31.0, and R, version 4.5.1 (R Core Team, 2024). Spearman’s rank-order correlations and ordinary least squares (OLS) regression analyses were used. The Power Law package, version 1.00 (Gillespie, 2015), in R was used to compute fit lines for power-law distributions and goodness-of-fit statistics. Model fit for the power-law model was evaluated using a nonparametric bootstrap procedure with 500 simulations based on the Kolmogorov–Smirnov statistic.

Descriptive statistics were calculated for all variables under examination. The skewness of the dependent variables was assessed to evaluate distributional assumptions. The variables of inbound sales and outbound sales were moderately skewed. To improve residual normality and satisfy the assumptions of ordinary least squares regression, the inbound and outbound sales variables were log10-transformed before conducting the analyses in SPSS. The general job performance residuals were approximately normal, so no transformation was applied. Descriptive statistics and Spearman’s rank-order correlations were computed using the original, untransformed variables, consistent with Beck, Beatty and Sackett’s (2014) recommendation to apply non-parametric methods when outcome distributions are skewed.

Due to insufficient normative data from the unrestricted population and recent research suggesting that current practices for correcting validity in concurrent validation studies may lead to overcorrection (Sackett et al., 2022), no range restriction correction was applied. Validity for managerially rated performance was corrected for unreliability in the criterion (attenuation) using an estimate of 0.61 for non-managerial jobs, as proposed by Zhou et al. (2024).

Personality, general job performance, and sales performance

H1 stated that conscientiousness and extraversion are positively related to general job performance. Spearman’s rho correlations between the FFM factors and general job performance were computed, and positive associations between conscientiousness, extraversion, and general job performance were found. The observed correlations are reported in Table 1. Conscientiousness had the strongest association with general job performance (r = .27, p < .01), followed by extraversion (r = .14, p < .05); thus, the results were consistent with H1. Regression analysis partially supported H1, with only conscientiousness emerging as a significant predictor of general job performance (β = .31, p < .01). Interestingly, a significant negative effect was observed for openness to experience (β = –.14, p < .05), suggesting a potential suppression effect (see Table 2). Notably, openness to experience was not significantly correlated with job performance, but small to moderate correlations with conscientiousness and extraversion were observed, which is consistent with the suppression effect.

H2 stated that conscientiousness, extraversion, emotional stability, and agreeableness are positively related to outbound sales. Significant associations were found for conscientiousness (r = .15, p < .05), agreeableness (r = .20, p < .01), and emotional stability (r = .14, p < .05). Surprisingly, no effect was found for extraversion; thus, H2 was only partly supported. Moreover, the regression results revealed no significant effects. This pattern may be partly due to multicollinearity among predictors, which reduces the unique variance each predictor contributes to the model (Tabachnick & Fidell, 2013).

H3 stated that extraversion is negatively associated with inbound sales. Extraversion was negatively correlated with inbound sales (r = –.25, p < .01), and thus H3 was supported. Regression results revealed a relative contribution of extraversion (β = –.27, p < .01).

Distribution of objective performance

H4a stated that a power-law distribution fits sales performance data more accurately than a normal distribution. For outbound sales, comparative model analyses showed a superior fit for the power-law distribution, with log-likelihood = –283.21, Akaike Information Criterion (AIC) = 568.43, and Bayesian Information Criterion (BIC) = 570.92, surpassing the normal distribution (log-likelihood = –862.84, AIC = 1729.68, BIC = 1737.69). The power-law model effectively characterized values above the threshold (xmin = 10) with a scaling exponent (α = 2.89), highlighting the presence of outliers. A bootstrap goodness-of-fit test supported the statistical plausibility of the power-law model for the tail of the distribution (p = .18), with a nonsignificant p-value indicating that the model is consistent with the data (Clauset, Shalizi, & Newman, 2009).

A similar pattern emerged for inbound sales. The log-likelihood comparison favored the power-law model (–302.87) over the normal distribution (–1150.00), and the AIC (607.74 vs. 2303.99) and BIC values (609.74 vs. 2310.52) further supported the superior fit. The power-law model characterized values above the threshold (xmin = 135) with a scaling exponent (α = 3.29), slightly exceeding the commonly referenced threshold of (α = 3.00). A bootstrap goodness-of-fit test confirmed the plausibility of the power-law model for the tail (p = .16).

Overall, these findings supported H4a, demonstrating that a power-law distribution provides a more plausible and statistically superior representation of individual sales performance data than a normal distribution.

Performance principles

H4b proposed that approximately 20% of employees would be responsible for about 80% of total sales. For outbound sales, 2,320 units were sold, with the top 20% of employees (53 out of 246) accounting for 1,173 units, representing approximately 51% of total sales. The results indicate a “performance rule” of “20^c–51%” for outbound sales. For inbound sales, 19,434 units were sold among 193 employees, with the top 20% (43 employees) contributing to 52% of sales, suggesting a 20–52% “performance rule.” The findings align with a 20–50% distribution rather than the anticipated 20–80%, thereby partially supporting the hypothesis (see Table 3). A reviewer noted that dichotomizing criterion variables permits additional statistical analysis. Accordingly, Levene’s and Bartlett’s tests were conducted to compare the variance in personality categories between the top 20% performers and the bottom 80% performers. The results revealed no significant differences in variance.

Personality in relation to general job performance and sales performance

The primary aim of this study was to examine the relationship between personality traits, general job performance, and sales performance.

First, while findings vary by occupations, prior research has frequently identified conscientiousness and extraversion as meaningful predictors of job performance (Sackett et al., 2022; Schmidt & Hunter, 1998). In line with previous literature, the present findings offer additional empirical support for the association between conscientiousness, extraversion, and general job performance within sales roles. Notably, a suppression effect emerged for openness to experience, indicating shared variance with other predictors. As Tabachnick and Fidell (2013) note, multicollinearity complicates the identification of unique predictor contributions, making suppression effects more challenging to interpret. One plausible explanation is that openness to experience removes criterion-irrelevant variance, thereby improving the predictive validity of conscientiousness. A similar mechanism may apply to extraversion, although extraversion did not reach statistical significance in the full model.

The nature of sales roles may also contribute to the negative effects associated with openness to experience. Sales environments typically emphasize clear performance targets and adherence to rules and procedures. Traits linked to openness, such as creativity, preference for novelty, and unconventional thinking, may be less advantageous, or even counterproductive, in structured settings. Comparable patterns have been observed in other occupational contexts. For example, Skoglund et al. (2021) reported negative associations between openness to experience and performance in military environments.

Second, for outbound sales, the analysis indicated no support for extraversion. In contrast, conscientiousness, emotional stability, and agreeableness were positively associated with outbound sales performance. While the results for conscientiousness and emotional stability align with the existing literature (Dugan, Rouziou, & Bolander, 2020; Kottirre, Blickle, & Wihler, 2025), the role of agreeableness warrants further exploration. Prior research suggests that extraversion is crucial in jobs that demand interpersonal interaction (Wilmot et al., 2019). Our findings refine this perspective, highlighting the significance of agreeableness in fostering relational aspects that enhance sales performance, even in roles where initiating customer contact is a central task.

Third, a negative correlation between extraversion and inbound sales performance was found. The finding highlights that personality traits may not exert uniform effects across performance domains but instead operate based on how performance is conceptualized and measured. Effective inbound sales necessitate strong listening skills and the ability to clarify customer expectations. According to Chaker et al. (2024), introverted individuals excel in sales roles, which aligns with Flynn, Collins, & Zlatev’s (2023) assertion that listening is essential for building social relationships. Effective listening facilitates the processing of information and enables constructive responses, both of which are critical in inbound sales contexts where understanding customer needs is essential.

Overall, the findings support the notion put forth by Hough and Oswald (2023) regarding the necessity of aligning personality traits with specific performance criteria. This alignment is particularly critical in sales, where research often emphasizes extraversion as a key sales trait (Furnham & Fudge, 2008; Grant, 2013). The current findings indicate that other traits, such as emotional stability and agreeableness, may also play significant roles in shaping sales performance.

Distribution of sales performance

The secondary aim was to expand on the notion of star performers by assessing whether sales performance data were better modeled by a power-law distribution than by a normal distribution, thereby examining if a small proportion of individuals account for a disproportionately large share of sales performance outcomes.

First, the results indicate that sales performance aligns more closely with a power-law distribution rather than a normal distribution, a pattern consistent with O’Boyle and Aguinis (2012) assertion. The finding raises important conceptual and methodological considerations.

First, a power-law distribution differs from a normal distribution by featuring a longer tail, which captures high performers. The power-law analysis revealed that star performers could be identified in both the inbound and outbound groups. Interestingly, a comparative analysis of the variance in personality traits between high performers and the remaining performers revealed no differences. While the role of personality in identifying high performers remains uncertain, our results suggest that personality is predictive of sales performance, even in distributions characterized by power laws. To improve differentiation of performance levels and explore this issue more thoroughly, one suggestion is to separate normal and high performers by defining two distinct performance constructs within the same distribution, one for performance within the normal range and another for performance within the tail, suggesting a unimodal distribution (Ployhart, 2006). Notably, our rank-ordering revealed a 20/50 rule rather than the expected 20/80 rule, indicating that while a small percentage of employees significantly contribute to overall performance, their impact is less extreme than initially anticipated.

Second, Campbell and Wiernik (2015) argue that performance measures must be defined more precisely to avoid misinterpretation, since broad labels like job performance or sales performance can oversimplify important distinctions. A clarification between input and output measures is warranted to further understand the performance construct (Campbell et al., 1993). General job performance reflects input-based behavioral indicators rated by managers, whereas sales performance represents an output-based measure. The domains differ substantially because input measures capture the behaviors relevant for performing well, while output measures only capture the end results. To draw valid conclusions about how job performance is distributed, Beck, Beatty, and Sackett (2014) argue that performance measures must meet seven criteria. Specifically, performance measures should (a) capture actual behavior, (b) represent multiple behaviors combined, (c) include all types of performers, (d) cover the full range of performance levels, (e) be time-bounded, (f) focus on comparable job roles, and (g) be free from motivational distortion, that is, they should reflect true performance rather than behavior inflated by incentives or external pressures. When these criteria are met, the resulting performance distribution is expected to approximate normality. An important implication is that when outcome measures (e.g., sales results) are used as proxies for job performance, the observed distribution often appears highly skewed, even if the underlying distribution of performance behaviors is close to normal. This misalignment can lead to systematic misinterpretations of individual contributions to organizational performance.

Practical implications

First, conscientiousness was associated with both general job performance and sales performance, reinforcing its established importance in personnel selection practices. The relationship suggests that incorporating conscientiousness measures into selection procedures may help practitioners more effectively identify candidates with a higher likelihood of success in the role.

Second, although extroverted behaviors, such as being talkative, cheerful, and assertive, are linked to sales performance, the results highlight the importance of evaluating the specific performance domain rather than relying on general assumptions about trait performance relationships. The results are in line with Hough and Oswalds’s (2023) argument that personality traits relate to performance in domain-specific ways. Since personality traits exhibit convergent relations with different performance domains, a “pick and choose” strategy can be employed. To aid this process, personality-based analysis can be applied to align personality traits with the specific behavioral performance requirements of the role. The recommendation is in line with Tett, Toich, and Ozkum’s (2021) call for trait-based job analysis to explore personality dynamics in organizations.

Third, for practitioners seeking an empirical approach to validation, job component validation (JCV), a synthetic validation strategy, offers a viable alternative as suggested by Hoffman, Morris, and Luck (2009). JCV helps identify and validate the most critical components of a job, ensuring that candidates possess the traits necessary for performance. A notable advantage of JCV is that it does not require large-scale data collection, making it particularly suitable for roles with small sample sizes or newly established positions where performance data are limited. As such, JCV provides a practical and empirical pathway for linking job requirements to relevant predictor measures in contexts where traditional validation approaches may be infeasible.

Fourth, our analysis revealed that approximately 20% of employees generate about 50% of total sales in both inbound and outbound contexts, a distribution that is less extreme than initially hypothesized. To support selection and validation practices, a balanced approach that integrates output measures with input-based behavioral measures is likely to provide a fairer and more accurate understanding of performance, rather than selecting high performers based on output measures only. Retaining high performers remains important, but doing so should not compromise fairness, and practitioners should rely on both input behaviors and output data sources when identifying high-potential employees, consistent with the practices outlined by Beck, Beatty, and Sackett (2014). When organizations rely exclusively on output measures and tie rewards directly to those outcomes, the resulting distribution (e.g., 20/50 or 20/80 patterns) may not accurately reflect the underlying distribution of input behaviors. Furthermore, Awtrey et al. (2021) noted that distribution neglect is common among both practitioners and researchers. Distribution neglect refers to the tendency to misestimate or overlook distributional information by relying on heuristics rather than carefully examining performance distributions. Practitioners are encouraged to devote sufficient time to evaluating performance distributions directly. Attending distributional information supports more accurate and meaningful interpretations of individual performance and clarifies potential pitfalls in selection decisions and validation research.

Limitations

First, the study applied a concurrent validation design, with predictor and criterion data collected simultaneously. As noted by Sackett et al. (2022), predictive and concurrent validity studies may yield different results, as each design contributes differently to the validity estimate due to systematic biases.

Second, although faking personality measures are less of a concern in concurrent validity studies compared to predictive studies in operational settings, the incentive to present oneself desirably poses a limitation.

Third, other important predictors of performance in organizations, such as general mental ability, interests, and job knowledge were not included. Future research could explore the incremental validity of these additional predictors more extensively in sales and advisory roles using both input and output performance criteria.

Fourth, performance appraisals can be difficult to perform objectively, and the raters did not receive significant training prior to completing the appraisals. A lack of training may lead to increased rater bias (Rosales Sánchez, Díaz-Cabrera, & Hernández-Fernaud, 2019).

Fifth, while the study focused specifically on sales roles, prior research on validity generalization suggests that measures of general job performance may predict outcomes across different jobs that require similar skills (Sackett, 2022). Both input measures and output measures may exhibit varying degrees of generalizability depending on the organizational context and the specific tasks involved. Accordingly, differences in job characteristics, performance criteria, and employee demographics may limit the extent to which our findings can be directly applied to other roles or industries.

Future research directions

First, future research could apply personality-based job analysis as a foundation for criterion development, rather than relying solely on broad models of general job performance. Earlier work has provided support for personality-based job analysis (Goffin et al., 2011), and more recent research continues to advocate for its use (Tett, Toich, & Ozkum, 2021). Despite the availability of established instruments (e.g., Raymark, Schmit, & Guion, 1997), researchers still depend on traditional job analysis instruments and job descriptions to identify relevant traits for specific roles. This continued reliance represents a missed opportunity to leverage trait-based analyses, which may provide a more refined and theoretically aligned approach to criterion development (Tett, Toich, & Ozkum, 2021).

Second, future research could examine facet-level predictors within the broader personality domains and further investigate relationships with sales performance in comparable sales and advisory roles. Additionally, researchers could apply synthetic validation techniques to evaluate the effectiveness of specific predictor–performance relationships in situations where personality and performance data are difficult to obtain (Hoffman, Morris, & Luck, 2009).

Third, future studies could explore the possibility that sales performance metrics encompass two underlying constructs: typical performance and exceptional performance within individual performance distributions (Awtrey et al., 2021; Ployhart, 2006). Examining this distinction may improve the conceptual clarity of sales performance measures and inform more precise modeling approaches.