Examining Effects of Human Resource Analytics in Decision Making: A Case Study Ministry of Health HQ in Lusaka

Data Analytics has potential to change how companies compete through new business models, where decisions are automated in a way that guarantees speed, quality and flexibility. Despite this rush and the push to have enterprises embrace BDA, empirical evidence shows that majority of the firms have not benefited from their investments in DA. Despite the potential benefits of HRA, it has not received adequate attention from management researchers. The general objective of the study is to examine the effects of Human Resource Analytics on decision-making processes in the Ministry of Health. Research design is defined as the general plan of how the researcher goes about answering the research questions. A descriptive case study approach will be adopted to match the nature of the topic. The study will use open ended questionnaires and guided oral interviews. A sample will be drawn from HRM personnel to generate inferences about the target population. This helps in saving time and resources it would otherwise have taken to meet every individual in the entire population. Target population in this research comprises of all those potential participants that could make up the study group. In this research, the target population was 50. Purposive sampling of respondents was carried out. The respondents will be picked from various departments involved in various activities. This will be done in order to extract correct and accurate information because the problem at hand required such consideration. The basic idea of sampling is by selecting some of the elements in a population, we may draw conclusions about the entire population The reason why sampling is necessary is because of lower costs, greater accuracy of results, and greater speed of data collection and availability of population elements. The sample size refers to the number of elements or units that the researcher draws from the population of respondents for research exercise. In this study, the sample size of 50 respondents will be picked. And all 50 questionnaires will be distributed. These respondents will be purposely chosen by the researcher Data collection consisted of interviews from the selected HRM personnel both male and female. Data analysis is the process of editing and reducing accumulated data to a manageable size, developing summaries, looking for patterns and applying statistical techniques. The data collected will be analyzed using tables, figures. The researcher used both qualitative and quantitative method. According to the results in (Table 5.7), several limiting factors to the effective use of Human Resource Analytics (HRA) were identified. The highest reported constraint was poor system integration, with a mean score of 3.80 (±0.99), followed closely by lack of staff technical skills at 3.68 (±1.12). Lack of appropriate tools/software was also noted as a major barrier, scoring a mean of 3.62 (±1.16). Other relevant constraints included privacy and security concerns (3.54 ±1.18), infrastructure constraints (3.50 ±1.06), and inadequate training on HRA among staff, which was the least reported limitation, with a mean of 3.18 (±0.90). The results demonstrate varied levels of Human Resource Analytics (HRA) usage across core HR functions within the Ministry of Health in Lusaka. Among the four key areas assessed, the highest level of application was noted in monitoring employee performance, with 68% of the maximum possible score (Mean = 3.40). Similarly, the use of analytics to identify training needs followed closely with a mean of 3.38 (67.6%), reflecting a relatively strong uptake of HRA in skills development and capacity-building initiatives. Workforce planning recorded a moderate mean of 3.32 (66.4%). Conversely, tracking attrition was the least utilized function, with only 50% of the maximum score (Mean = 2.50). The crosstabulation results reveal substantial differences in the use of Human Resource Information Systems (HRIS) across various job roles within the Ministry of Health. HR Officers, Planners, and Administrators all reported 100% usage of HRIS in their roles. Among Analysts, 71.4% indicated use of HRIS, while 28.6% did not. Notably, respondents categorized under “Other” reported 0% usage, highlighting potential exclusion or limited exposure to HRIS tools in that category. The recommendations are that there is a need for an integrated system that will bring all areas of HR on board and also a need for capacity building HR.