Influence of Big Data Analytics on Performance of Donor Funded Health Projects in Kajiado County
DOI:
https://doi.org/10.47941/jepm.4054Keywords:
Real-Time Analytics, Data-Driven Decision-Making, Big Data Analytics, Donor-Funded Health Projects, Project PerformanceAbstract
Purpose: This study examined the influence of Big Data Analytics on the performance of Donor-funded health projects in Kajiado county. The specific objectives of the study were; to examine the influence of real-time analytics and data-driven decision-making on the performance of donor-funded health projects in Kajiado County, Kenya.
Methodology: The study targeted a population of 220 technical personnel drawn from donor-funded health projects in Kajiado County, from which a sample of 142 respondents was selected. Data for the study was collected using structured questionnaires and analyzed using descriptive statistics, correlation analysis, and multiple linear regression analysis. The data analysis was aided by SPSS software with the final findings presented in tables, charts and graphs.
Findings: The study established that real-time analytics and data-driven decision-making each had a positive and statistically significant relationship with project performance. Correlation analysis showed that real-time analytics (r = 0.722, p < 0.01) and data-driven decision-making (r = 0.783, p < 0.01) were strongly associated with the performance of donor-funded health projects in Kajiado County. Multiple regression analysis further confirmed that both variables exerted significant positive effects on project performance.
Unique Contribution to Theory, Practice and Policy: The study offers an empirical support for the position that organizations can improve their ability to adapt to changing project conditions through timely access to information. The study also offers practical guidance to project managers and programme officers to integrate analytics in planning, monitoring, evaluation, resource use and decision making during project implementation. At policy level, findings point to the need for stronger digital monitoring systems, better data management and the use of data evidence in reporting and managing donor funded health programmes.
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