The State of HR Analytics

Purpose: The purpose of this study is to assess the level of HR analytics maturity within the Nigerian oil and gas industry and identify the predominant level of maturity across descriptive, predictive, and prescriptive analytics. The study further examines the extent to which HR analytics maturity influences strategic decision-making and explores the organizational and technological factors that enable or hinder the development and adoption of advanced HR analytics capabilities. Theory: This study applies Bounded Rationality, the Technology Acceptance Model (TAM), and the Resource-Based View (RBV) as the theoretical framework guiding the study. Method: A quantitative research design was employed using a structured online questionnaire consisting primarily of five-point Likert scale items alongside supplementary open-ended questions used to provide contextual insights. Data were collected from 91 respondents across approximately ten organizations within the Nigerian oil and gas industry using purposive and snowball sampling techniques. The data were analyzed using descriptive statistics, reliability analysis, correlation analysis, multiple regression analysis, ANOVA, and mediation analysis in IBM SPSS Statistics. Result: The findings indicate moderate to relatively high HR analytics maturity, with predictive analytics emerging as the strongest association with decision quality and decision frequency. The findings further suggest a more advanced but uneven maturity pattern than commonly reported in developing economy contexts. The findings also indicate the presence of an analytics translation gap, referring to the disconnect between the availability of analytical capabilities and insights and their effective integration into strategic decision-making processes.