Decoding employee loyalty: unravelling the Impact of human resource analytics in Uganda's commercial banking sector

Abstract

The study examined the effect of human resource analytics on staff retention in commercial banks in Uganda, a case of Finance Trust Bank, main branch. The study objectives included; (i) to evaluate the effect of HR data mining analytics on staff retention in Finance Trust Bank; (ii)to determine the effect of HR data interpretation analytics on staff retention in Finance Trust Bank and (iii) to examine the effect of HR performance management analytics on staff retention in Finance Trust Bank. The study design was a cross sectional design and the approaches used were both qualitative and quantitative. The study population was 65 people, a census was adopted; 53 respondents responded, thus a response rate of 82%. Questionnaires were the main tools used in data collection. The findings indicated that performance management analytics is the greatest contributor to employee retention in Finance Trust Bank (β = 0.566; p value = 0.001), data mining analytics is the second contributor to employee retention (β= 0.373; p value= 0.006), and data interpretation analytics is the least contributor to employee retention (β = 0.211; p value= 0.039). The study concluded that data mining analytics, data interpretation analytics and performance management analytics are all strong, positive and significant predictors of employee retention at the bank (R2 =.647; p value = 0.000). Conclusion were drawn and recommendations given.