Th-SYM-2533-6 - Predicting Future Consistent Performance From Personality Facets

Track:
Validity of tests
What:
Symposium
When:
1 hour
Where:
E2.18
Discussion:
0
 
Employee Selection
Validity of tests
Th-SYM-2533-6
Predicting Future Consistent Performance
from Personality Facets
 
M. Guarini*, F. Sandø 1
1Research & Development, HUCAMA, Copenhagen, Denmark
 
Main Abstract Content:  
 
Purpose
Quantifying performance is complex as specific performance goals vary widely between and within organizations in response to specific demands. Yet quantifying cumulative effects over the life cycle of an employment is even more complex as performance changes over time for a variety of reasons.  
 
Design/Methodology
In two studies (N=202 and N=196) predictor data on a 24 facet measure of the Big 5 personality factors were gathered alongside monthly performance criterion scores for up to 16 months comprising Average handling time (AHT), Item Resolution (IR), Additional sales (HIT) and Customer satisfaction (CSAT). Performance measures of consistent performance and cumulative consistent performance were calculated and analysed using Mixed Model regression (Guarini & Sandø, 2016).
 
Results
The study showed that analysing single time point performance in isolation often revealed no significant differences. Differences only came to light when cumulative performance was considered. The longitudinal analyses showed high discriminatory power for fit scores (most p-values p<0.01) whereas explained variance R² (Xu, 2003) was moderate (0.15  
Limitations
Cross-validation of algorithms will be required to safeguard against chance effects.
 
Research/Practical Implications
The study illustrates how mixed models can be used to predict time dependent performance, and the added value of deploying empirically derived composite predictors based on the most valid of 24 personality facets.
 
Originality/Value
The approach outline delivers People Analytics in the real world maximising validity across multiple criteria and time points.
 
 
 
 
 
 
 

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