CASE STUDY Talent Basics
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CASE STUDY A Talent Audit in the Industrial Sector Talent Basics: Xander van Lill Product and Research, JVR Africa Group CONTEXT ON ORGANISATION X AND THE ASSESSMENTS USED Organisation X is a small- to medium enterprise that operates in the industrial sector. Cognify, the Basic Traits Inventory (BTI), and Individual Work Performance Review (IWPR) were administrated at Organisation X to conduct an audit of the organisation’s current potential and performance. More information about each of the assessments used is provided below. The IWPR is a multidimensional and generic measure of individual work performance developed in South Africa assessing task performance, organisational citizenship behaviour, adaptive performance, leadership effectiveness, and counterproductive behaviours. Cognify is a game-based cognitive assessment measuring fluid intelligence (Gf), visual processing (Gv), quantitative reasoning (Gq), and reading and writing abilities (Grw) via six mini games. The BTI is a South African assessment of the Big Five factors of personality, namely extroversion, neuroticism, conscientiousness, openness to experience, and agreeableness. Cognify DIFFERENTIATING HIGH PERFORMERS Potential data was derived from an equal weighting strategy based on a general mental ability and meta personality trait (integrity) score. The integrity score was based on a hierarchical factor analysis conducted on traits Conscientiousness, Agreeableness, and Neuroticism in the BTI. An equal weighting strategy was adopted to reduce the possibility of adverse impact against candidates from previously disadvantaged groups (Cascio & Aguinis, 2019; Outtz, 2002). An overall performance score was derived from four performance factors on the IWPR, namely task performance, organisational citizenship behaviour, adaptive performance, and leadership effectiveness. The distribution of performance across individuals in a low vs high potential category are displayed in Figure 1. The low and high performing samples were split based on the median. Potential and 360 performance scores in Figure 1 were standardised to reflect a score out of nine (mean = 5; SD = 1.96). The average performance score for employees with higher potential was 6, whereas the average performance score for employees with lower potential was 4. The distribution of performance scores further JVR AFRICA GROUP | [email protected] | +27 11 781 3705 | jvrafricagroup.co.za
Transcript of CASE STUDY Talent Basics
CASE STUDY
A Talent Audit in the Industrial Sector
Talent Basics:
Xander van LillProduct and Research, JVR Africa Group
CONTEXT ON ORGANISATION X AND THE ASSESSMENTS USEDOrganisation X is a small- to medium enterprise that operates in the industrial sector. Cognify, the Basic Traits Inventory (BTI), and Individual Work Performance Review (IWPR) were administrated at Organisation X to conduct an audit of the organisation’s current potential and performance. More information about each of the assessments used is provided below.
The IWPR is a multidimensional and generic measure of individual work performance developed in South Africa assessing task performance, organisational citizenship behaviour, adaptive performance, leadership effectiveness, and counterproductive behaviours.
Cognify is a game-based cognitive assessment measuring fluid intelligence (Gf), visual processing (Gv), quantitative reasoning (Gq), and reading and writing abilities (Grw) via six mini games.
The BTI is a South African assessment of the Big Five factors of personality, namely extroversion, neuroticism, conscientiousness, openness to experience, and agreeableness.
Cognify
DIFFERENTIATING HIGH PERFORMERSPotential data was derived from an equal weighting strategy based on a general mental ability and meta personality trait (integrity) score. The integrity score was based on a hierarchical factor analysis conducted on traits Conscientiousness, Agreeableness, and Neuroticism in the BTI. An equal weighting strategy was adopted to reduce the possibility of adverse impact against candidates from previously disadvantaged groups (Cascio & Aguinis, 2019; Outtz, 2002). An overall performance score was derived from four performance factors on the IWPR, namely task performance, organisational citizenship behaviour, adaptive performance, and leadership effectiveness. The distribution of performance across individuals in a low vs high potential category are displayed in Figure 1. The low and high performing samples were split based on the median. Potential and 360 performance scores in Figure 1 were standardised to reflect a score out of nine (mean = 5; SD = 1.96). The average performance score for employees with higher potential was 6, whereas the average performance score for employees with lower potential was 4. The distribution of performance scores further
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suggests that the number of employees that received high-performance scores is greater in the higher potential category (n = 32%) compared to the lower potential category (n = 20%). Conversely, the number of employees that received low-performance scores is greater in the lower potential category (n = 28%) compared to the higher potential category (n = 12%).
FIGURE 1. DISTRIBUTION OF PERFORMANCE SCORES ACROSS LOW AND HIGH POTENTIAL CATEGORIES
32%
56%
12% 20%
52%
28%
HIGHERPOTENTIAL
LOWERPOTENTIAL
CALCULATING RETURN ON INVESTMENTOrganisation X shared information on the complexity, median salaries, tenure, and appointments per year on jobs in addition to the potential and performance data collected by JVR. This enabled JVR to calculate the gain in performance in Rands (ROI) if Organisation X were to use the proposed battery of assessments for selection decisions in the future. Note that a more conservative estimate (only supervisory ratings) than the 360 performance ratings reported in Figure 1 was used to calculate the validity coefficient used in Formula 1. Furthermore, the validity coefficient was calculated by using a larger sample of which Organisation X formed part. An adaptation of the Brogden-Cronbach-Gleser general utility equation was implemented by JVR to calculate return on investment (Cascio & Boudreau, 2011). Utility analysis quantifies the difference in performance between low and high performing staff in positions. It, therefore, reflects the difference in Rands between your top and low performers and helps you make decisions about how far you can go to improve the performance of your team via selection – to ensure you achieve a return on your HR investment. Formula 1 displays the elements of the equation.
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∆U = t × Ns × r × SDy × X - (Ns × C)
Formula 1:_
∆U Gain in performance in Rands from using a selection proceduret Tenure in roleNs Number of employees appointed in role per yearr Validity of selection procedure (ββ= 0.70)SDy Standard deviation of performance in RandsX ̅ Average standardised test score of selected candidatesC Cost of testing (R 750 per candidate)
_
*NOTE. GREEN represents the number of employees with high scores (7-9), YELLOW represents employees with medium scores (4-6), and RED represents employees with low scores (1-3).
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We used Cascio and Boudreau's (2011) guidelines/rules to determine the SDy for low, medium, and high complexity jobs. The application of the Brogden-Cronbach-Gleser formula revealed the following gain in performance in Rands:• R 417 100.51 over four years for low complexity jobs if selection decisions in Organisation X are based on
Cognify and the BTI. The amount is based on the premise that five high-performing applicants instead of five low-performing applicants are selected per year.
• R 491 318.60 over six years for medium complexity jobs if selection decisions in Organisation X are based on Cognify and the BTI. The amount is based on the premise that six high-performing applicants instead of six low-performing applicants are selected per year.
• R 1 481 754,82 over eight years for a high complexity job if selection decisions in Organisation X are based on Cognify and the BTI. The amount is based on the premise that one high-performing applicant instead of one low-performing applicant is selected per year.
The gain in performance in Rands, especially for high-complexity jobs, highlights the importance of making accurate selection decisions based on reliable and valid selection procedures, such as cognitive ability and personality assessments (Schmidt & Hunter, 1998; Schmidt et al, 2016). Metrics, such as gain in performance in Rands due to certain selection procedures, bolster human resource practitioners’ image as strategic partners and strengthen their claim to invest in people practices such as selection (Cascio & Boudreau, 2011).
ORGANISATIONAL DEVELOPMENT INITIATIVESThe talent audit enabled Organisation X to embark on several organisational development initiatives. Some of the initiatives are listed below.1. A Talent Audit Report was shared with the executives of the organisation. The report highlighted alignment
between current potential and performance. Under-performing (high potential; low performance) employees provided insights on opportunities for work redesign and/or personal development. Overperforming employees stimulated further investigations into factors, other than individual talent, that contribute to performance, such as work resources and leadership. A ranking of employees according to potential, while also displaying overall performance, further enabled the identification and promotion of high potentials from within the organisation. Internal promotions tend to increase organisational commitment among employees. It also helps organisations to capitalise on existing learning and development initiatives, which is an implicit return on investment not calculated in this case study (Van Lill & Coetzee, 2021).
2. Feedback was provided to managers on Team Summary Performance Reports based on data from the IWPR. The generic nature of the IWPR created a shared language to make sense of performance across the organisation. An organisation-specific benchmark accentuated individual performance differences. Top to bottom performers was rank ordered based on an overall performance score. The overall performance score was further broken down into its specific elements for individual performance feedback. The rank order enabled Organisation X to identify high-performers and strategically invest resources to retain top talent (Aguinis & O’Boyle, 2014). Possible risks, in terms of counterproductive performance, was flagged to the industrial psychologist. Evidence based on overall trends served as a point of departure for teams to deliberate about future team performance goals. Performance feedback and goal setting were also facilitated at the individual level.
3. Career Development Reports were generated for all employees that completed the assessments. Coaching was conducted with each employee based on the 10 personality aspects of the BTI (Van Lill & Taylor, 2021). The 10 personality aspects enabled a quick overview but detailed enough breakdown for feedback purposes. Organisation X decided to adopt Kolb’s experiential learning model during coaching to assist employees (1) to identify critical performance incidents, (2) reflect on the incident in terms of personality, (3) develop working hypotheses on how personality impacted performance, and (4) identify new behavioural habits to experiment with to achieve desired career goals (Turesky & Gallagher, 2011).
FUTURE RECOMMENDATIONSOrganisation X might consider including interest inventories in their future battery. Interest inventories, especially when used to calculate person-environment fit scores (Morgan et al., In Press), add incremental validity over cognitive ability when predicting performance (Schmidt et al., 2016). Interest inventories could also add great value for work redesign or the identification of learning opportunities for career development purposes in coaching.
NEED TO KNOW MORE?Contact us at [email protected] or call 011 781 3705 to set up an appointment.
JVR AFRICA GROUP | [email protected] | +27 11 781 3705 | jvrafricagroup.co.za
Aguinis, H., & O’Boyle, E. (2014). Star performers in twenty-first century organizations. Personnel Psychology, 67(2), 313–350. https://doi.org/10.1111/peps.12054
Cascio, W. F., & Aguinis, H. (2019). Applied psychology in talent management. Sage.
Cascio, W. F., & Boudreau, J. (2011). Investing in people: Financial impact of human resource initiatives (2nd ed.). Pearson Education.
Morgan, B., Van Lill, X., & Rajab, P. (n.d.). Using vocational interest in organisation selection and development. In X. Van Lill & N. Taylor (Eds.), Using psychometrics in selection. JVR Africa Group.
Outtz, J. L. (2002). The role of cognitive ability tests in employment selection. Human Performance, 15(1–2), 161– 171. https://doi.org/10.1080/08959285.2002.9668089
Schmidt, F. L., & Hunter, J. E. (1998). The validity and utility of selection methods in personnel psychology: Practical and theoretical implications of 85 years of research findings. Psychological Bulletin, 124(2), 262–274. https://doi.org/10.1037/0033-2909.124.2.262
Schmidt, F. L., Oh, I.-S., & Shaffer, J. A. (2016). The validity and utility of selection methods in personnel psychology: Practical and theoretical implications of 100 years. Working Paper, 1–73. https://doi. org/10.13140/RG.2.2.18843.26400
Turesky, E. F., & Gallagher, D. (2011). Know thyself : Coaching for leadership using Kolb ’ s Experiential Learning Theory. The Coaching Psychologist, 7(1), 5–14. https://www.researchgate.net/publication/285307039_ Know_thyself_Coaching_for_leadership_using_Kolb’s_Experiential_Learning_Theory
Van Lill, X., & Coetzee, M. (2021). Recruitment and selection. In Personnel psychology: An applied perspective (pp. 213–279). Oxford University Press Southern Africa.
van Lill, X., & Taylor, N. (2021). The manifestation of the 10 personality aspects amongst the facets of the Basic Traits Inventory. African Journal of Psychological Assessment, 3, 1–10. https://doi.org/10.4102/ajopa.v3i0.31
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