DESCRIPTIVE HUMAN RESOURCE ANALYTICS AND EMPLOYEE EFFICIENCY IN MULTINATIONAL OIL AND GAS COMPANIES IN NIGERIA

Abubakar, J. N.

Department of Business Administration, Faculty of Administration and Management, Rivers State University, Port Harcourt, Nigeria john.abubakar@ust.edu.ng

Tamunomiebi, M. D.  

Department of Business Administration, Faculty of Administration and Management, Rivers State University, Port Harcourt, Nigeria

and

Gabriel, J. M. O.

Department of Business Administration, Faculty of Administration and Management, Rivers State University, Port Harcourt, Nigeria

ABSTRACT

This study examined the relationship between descriptive human resource analytics and employee efficiency in multinational oil and gas companies in Nigeria. The study adopted the cross-sectional research survey design. Primary data was generated through structured questionnaire. The population for this study was 10,238 employees of five multinational oil and gas companies in Nigeria. The sample of 385 was determined using the Taro Yamen’s 1970 formula. The reliability of the instrument was achieved by the use of the Cronbach Alpha coefficient with all the items scoring above 0.70.  The hypotheses were tested using the Spearman’s Rank Order Correlation Statistics while the partial correlation was used to test the moderating effect. The tests were carried out at a 0.05 significance level. Findings revealed that there is a significant relationship between descriptive human resource analytics and employee efficiency in multinational oil and gas companies in Nigeria. Therefore, the study concludes that descriptive human resource analytics (HRA) positively enhance employee efficiency in multinational oil and gas companies in Nigeria. Thus, the study recommends that Management of multinational companies should ensure that the organization has robust systems in place to collect, store, and analyze HR-related data effectively. This may involve investing in modern HRIS (Human Resource Information System) platforms capable of integrating data from various sources such as performance reviews, training records, and employee surveys.

Keywords: Descriptive human resource analytics, employee efficiency, timeliness of work, target achievement, employee innovativeness.