Predictive Analysis – Employee Performance

Many companies face the challenge of employee productivity. A downfall in productivity depends on various factors like poor work performance, attrition, job dis-satisfaction, etc. In order to tackle/improve the employee productivity, companies are taking a deep dive into various tools for trying to predict employees’ credibility with the company. The aim of predictive analysis is to diagnose and control employee attrition and increase the employee performance/productivity on the basis of some relevant demographics, aptitude and behavioral assessment.

But are educational qualifications and the years of experience the only predictors of employee performance and attrition? Is there any other parameter that can predict single factor of good employee performance? What attributes/traits are required to be checked at the hiring of candidates for the right position in the company? Are there any demographic variables affecting employee’s performance and attrition?

A recent study was conducted at PMaps on a huge deck of live data-points of various organizations in BPO/BPM industry using R programming for predicting the parameters/traits that result in better employee performance in any company. In this study, a positive relationship is observed between the employee’s industry performance and call handling time. For this analytics, we have considered demographics such as whether the candidate is sole earning member of their family, whether the candidate wants to pursue higher education, candidate’s motivation etc. More than half of the candidates who appeared for this test were SSC or HSC passes and most of the candidates were having less than one-year of experience.

Further, of our assessed traits which are presence of mind, emotional control and attention to details were the main attraction of this analysis. If a candidate scores above average in the presence of mind section then the candidate has higher chances of giving better performance. On the contrary, if a candidate scores average in traits like presence of mind and emotional control and scores above average in attention to detail section, then this candidate has higher chances of giving lower performance.

It is also observed that if the motivation of the candidate is money, then there are higher chances of the candidate giving better performance. The candidate whose motivation is recognition or office environment and who also wants to pursue higher education, then there is high probability of this candidate giving low performance.

Based on the prediction, we can say that educational qualification and total experience are not only the predictors for candidate’s performance as well as attrition, there are also more important predictors such as behavioral traits and demographics without which the prediction cannot be comprehensive. Thus predictive algorithm proves to be the one stop solution for companies who are looking towards lower attrition rate and higher employee’s performance level.

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*Lower performers are the candidates whose performance rating/ranking is lower than the average performance rating/ranking.

–Nisha (Team-PMaps)

(Blog Reference: PMaps)