Abstract: We have recently conducted a research on “Sales Hiring” with the view to predicting sales executive on job performance through scientific assessment. The research indicated a positive relationship between PMaps Sales Orientation Assessment™ scores and actual Sales Performance with a magnitude of .63 (coefficient of correlation i.e. r= 0.63; Chi value=11; p-value <.05). In simple term, it means all participants who scored high in PMaps Sales Assessment™ have performed better in a sales role. We later designed predictive algorithm for a client for predicting likely sales performance of candidate at the time of pre-hiring stage.
Brief: PMaps is India’s leading Analytics-driven Hiring Assessment company specializing in job-fitment services. A leading Life Insurance player in India approached PMaps for a Sales Assessment product that can measure Sales Attitude and Aptitude of candidates and predict their Sales Performance. PMaps first made some of their existing Sales Executives to appear for PMaps Sales Assessment ™ in order to measure their demographics, behavior, aptitude & skill dimensions. Test was conducted on multiple devices & in multiple languages on pan India basis to understand broad competencies driving the superior sales performance.
Norm group of participants: N= 166; N is evenly distributed in sales performance (refer chart A) 38% (N) with 3–7 yrs. of experience; 65% participants were graduates; 50% participants were from 18–23 yrs. age group.
After the test, PMaps asked the client to provide the performance rating of participants for last one year on seven rating scale where 1 = Low performer & 7 = Best Performer. Through correlation & validation studies, PMaps then established significant test of association between PMaps test scores & the participant’s Actual Sales Performance (refer-Chart B).
PMaps predictive model fared better in predicting performance of both High & Low Sales Performers as exhibited in Chart C. Our predictive model has predicted more than 63% of variance in actual sales performance (represented as Area Under Curve i.e. .63)
Prasad Jadhav (Team PMaps)
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