DATA ANALYTICS AND PROJECT MANAGEMENT PERFORMANCE IN NON-GOVERNMENT ORGANIZATIONS IN NAIROBI COUNTY, KENYA

Irene Nyindha, Dr. Mary Kamaara

Abstract


The main focus of this study was to establish the influence of data analytics on project performance in non-government organizations in Nairobi County, Kenya. Specifically, the study sought to determine the influence of quality data on project performance in non-government organizations in Nairobi County, Kenya and to analyze the influence of risk management on project performance in non-government organizations in Nairobi County, Kenya. This study used descriptive research design. This study targeted 325 registered NGOs in Nairobi County. The NGOs were the unit of analysis while senior managers formed the unit of analysis. The senior project managers were selected because they handle the organization decisions and are therefore well conversant with the influence of monitoring and evaluation data on project performance. The target population was 325 senior project managers in NGOs in Nairobi County. The study’s sample size was reached at using Krejcie and Morgan sample size determination formula. The study used simple random sampling to select 176 respondents. This study also used questionnaire to collect data relevant to this study. Quantitative data collected was analyzed using descriptive statistical techniques which are frequencies, mean, standard deviation. Inferential statistics which include Pearson correlation and the Regression Analysis Model were used to test the relationship between study variables. The significance of the model will be tested at 5% level of significance. Data was analysed using Statistical Package for Social Sciences (SPSS) software. The study results were presented through use of tables and figures. The study findings unveiled significant relationship between key variables and project performance in non-government organizations (NGOs) in Nairobi County, Kenya. Regression analysis demonstrated that quality data (β = 0.371, p < 0.05), and risk management (β = 0.238, p < 0.05) all significantly influence project performance. These findings underscore the importance of robust management practices, including strategic risk mitigation, data-driven decision-making, and alignment with organizational objectives, in optimizing project outcomes within the NGO sector in Nairobi County, Kenya. Therefore, the study concludes that a holistic approach that integrates these factors is essential for enhancing project performance and achieving desired outcomes within NGOs in Nairobi County, Kenya.

Key Words: Data Analytics, Project Performance, Non-Government Organizations, Quality Data, Risk Management 


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